https://navigators.di.fc.ul.pt/w2/index.php?title=Special:Contributions&feed=atom&limit=50&target=CasimNavigators - User contributions [en]2024-03-29T00:14:25ZFrom NavigatorsMediaWiki 1.16.5https://navigators.di.fc.ul.pt/wiki/Project:REDBOOKProject:REDBOOK2021-11-18T17:52:57Z<p>Casim: </p>
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<div>{{Project<br />
|Acronym=REDBOOK<br />
|Title=Robust hardwarE-based Defences against Buffer Overflows and Other cybersecurity attacKs<br />
|Past Project=no<br />
|ResearchLine=Fault and Intrusion Tolerance in Open Distributed Systems (FIT), Timeliness and Adaptation in Dependable Systems (TADS)<br />
|Sponsor=FCT<br />
|Project Number=PTDC/EEI-HAC/31273/2017<br />
|Total award amount=215882<br />
|Coordinator=Pedro Ferreira<br />
|Partners=FCUL<br />
|month=oct<br />
|year=2019<br />
|Duration months=36<br />
|Keywords=runtime verification, non-intrusive system monitoring, cyber-physical systems, cybersecurity<br />
|Summary=For decades, numerous vulnerabilities have put computer systems and applications at risk. Several cybersecurity issues have been recurrent, being Buffer Overflows (BOs) vulnerabilities a primary attack method, which nowadays still accounts for more than 25% of the reported attacks. Such a high number clearly shows that classical software-based and compiler-assisted techniques for preventing exploitation of buffer overflow vulnerabilities did not succeed. Existing hardware-based methods (e.g., StackGhost)<br />
are too restricted and therefore they are not widely used. This project aims the design of an innovative hardware-based system monitoring architecture, introducing novel non-intrusive observation and runtime verification mechanisms for robust defence against<br />
cybersecurity hazards emerging either from accidental faults or from malicious attacks. Technical feasibility will be demonstrated for SPARC (aerospace applications) and ARM (telecommunications, including mobile) platforms.<br />
|Team Size=5<br />
|Researchers=Pedro M. Ferreira, António Casimiro, Ibéria Medeiros,<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Project:VEDLIoTProject:VEDLIoT2021-11-18T17:52:13Z<p>Casim: </p>
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<div>{{Project<br />
|Acronym=VEDLIoT<br />
|Title=Very Efficient Deep Learning in IOT<br />
|Past Project=no<br />
|ResearchLine=Fault and Intrusion Tolerance in Open Distributed Systems (FIT), Timeliness and Adaptation in Dependable Systems (TADS)<br />
|Url=https://vedliot.eu/<br />
|Sponsor=EU H2020 program<br />
|Project Number=957197<br />
|Total award amount=8000000<br />
|Coordinator=Univ. of Bielefeld<br />
|Partners=EMBEDL AB (SE), Chalmers (SE), Siemens (DE), Christmann (DE), Université de Neuchâtel (CH), Universität Osnabrück (DE), VEONEER (SE), Göteborgs Universitet (SE), RISE Research Institutes of Sweden (SE), FCiências.ID (PT), Antmicro (PL)<br />
|month=nov<br />
|year=2020<br />
|Duration months=36<br />
|Keywords=Machine learning, Distributed AI, Internet of Things, Embedded computing, Sensor networks, Interoperability, Heterogeneous computing, Cognitive edge computing<br />
|Summary=The ever increasing performance of computer systems in general and IoT systems, in particular, delivers the capability to solve increasingly challenging problems, pushing automation to improve the quality of our life. This triggers the need for a next-generation IoT architecture, satisfying the demand for key sectors like transportation (e.g. self-driving cars), industry (e.g. robotization or predictive maintenance), and our homes (e.g. assisted living). Such applications require building systems of enormous complexity, so that traditional approaches start to fail. The amount of data collected and processed is huge, the computational power required is very high, and the algorithms are too complex allowing for the computation of solutions within the tight time constraints. In addition, security, privacy, or robustness for such systems becomes a critical challenge.<br />
An enabler that aims at delivering the required keystone is VEDLIoT, a Very Efficient Deep Learning IoT platform. Instead of traditional algorithms, artificial intelligence (AI) and deep learning (DL) are used to handle the large complexity. Due to the distributed approach, VEDLIoT allows dividing the application into smaller and more efficient components and work together in large collaborative systems in the Internet of Things (IoT), enabling AI-based algorithms that are distributed over IoT devices from edge to cloud.<br />
In terms of hardware, VEDLIoT offers a platform, the Cognitive IoT platform, leveraging European technology, which can be easily configured to be placed at any level of the compute continuum starting from the sensor nodes and then edge to cloud. Driven by use cases in the key sectors of automotive, industrial, and smart homes, the platform is supported by cross-cutting aspects satisfying security and robustness. Overall, VEDLIoT offers a framework for the Next Generation Internet based on IoT devices required for collaboratively solving complex DL applications across a distributed system.<br />
|NavigatorsSite=FCUL<br />
|Team Size=3<br />
|Researchers=António Casimiro, Nuno Ferreira Neves, José Cecílio, Alysson Bessani<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Project:VEDLIoTProject:VEDLIoT2021-11-18T17:51:21Z<p>Casim: </p>
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<div>{{Project<br />
|Acronym=VEDLIoT<br />
|Title=Very Efficient Deep Learning in IOT<br />
|Past Project=no<br />
|ResearchLine=Fault and Intrusion Tolerance in Open Distributed Systems (FIT), Timeliness and Adaptation in Dependable Systems (TADS)<br />
|Url=https://vedliot.eu/<br />
|Sponsor=EU H2020 program<br />
|Project Number=957197<br />
|Total award amount=8000000<br />
|Coordinator=Univ. of Bielefeld<br />
|Partners=EMBEDL AB (SE), Chalmers (SE), Siemens (DE), Christmann (DE), Université de Neuchâtel (CH), Universität Osnabrück (DE), VEONEER (SE), Göteborgs Universitet (SE), RISE Research Institutes of Sweden (SE), FCiências.ID (PT), Antmicro (PL)<br />
|month=nov<br />
|year=2020<br />
|Duration months=36<br />
|Keywords=Machine learning, Distributed AI, Internet of Things, Embedded computing, Sensor networks, Interoperability, Heterogeneous computing, Cognitive edge computing<br />
|Summary=The ever increasing performance of computer systems in general and IoT systems, in particular, delivers the capability to solve increasingly challenging problems, pushing automation to improve the quality of our life. This triggers the need for a next-generation IoT architecture, satisfying the demand for key sectors like transportation (e.g. self-driving cars), industry (e.g. robotization or predictive maintenance), and our homes (e.g. assisted living). Such applications require building systems of enormous complexity, so that traditional approaches start to fail. The amount of data collected and processed is huge, the computational power required is very high, and the algorithms are too complex allowing for the computation of solutions within the tight time constraints. In addition, security, privacy, or robustness for such systems becomes a critical challenge.<br />
An enabler that aims at delivering the required keystone is VEDLIoT, a Very Efficient Deep Learning IoT platform. Instead of traditional algorithms, artificial intelligence (AI) and deep learning (DL) are used to handle the large complexity. Due to the distributed approach, VEDLIoT allows dividing the application into smaller and more efficient components and work together in large collaborative systems in the Internet of Things (IoT), enabling AI-based algorithms that are distributed over IoT devices from edge to cloud.<br />
In terms of hardware, VEDLIoT offers a platform, the Cognitive IoT platform, leveraging European technology, which can be easily configured to be placed at any level of the compute continuum starting from the sensor nodes and then edge to cloud. Driven by use cases in the key sectors of automotive, industrial, and smart homes, the platform is supported by cross-cutting aspects satisfying security and robustness. Overall, VEDLIoT offers a framework for the Next Generation Internet based on IoT devices required for collaboratively solving complex DL applications across a distributed system.<br />
|NavigatorsSite=FCUL<br />
|Team Size=3<br />
|Researchers=António Casimiro, Pedro M. Ferreira, Nuno Ferreira Neves, José Cecílio, Alysson Bessani<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Project:VEDLIoTProject:VEDLIoT2021-11-18T17:50:30Z<p>Casim: </p>
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<div>{{Project<br />
|Acronym=VEDLIoT<br />
|Title=Very Efficient Deep Learning in IOT<br />
|Past Project=no<br />
|ResearchLine=Timeliness and Adaptation in Dependable Systems (TADS)<br />
|Url=https://vedliot.eu/<br />
|Sponsor=EU H2020 program<br />
|Project Number=957197<br />
|Total award amount=8000000<br />
|Coordinator=Univ. of Bielefeld<br />
|Partners=EMBEDL AB (SE), Chalmers (SE), Siemens (DE), Christmann (DE), Université de Neuchâtel (CH), Universität Osnabrück (DE), VEONEER (SE), Göteborgs Universitet (SE), RISE Research Institutes of Sweden (SE), FCiências.ID (PT), Antmicro (PL)<br />
|month=nov<br />
|year=2020<br />
|Duration months=36<br />
|Keywords=Machine learning, Distributed AI, Internet of Things, Embedded computing, Sensor networks, Interoperability, Heterogeneous computing, Cognitive edge computing<br />
|Summary=The ever increasing performance of computer systems in general and IoT systems, in particular, delivers the capability to solve increasingly challenging problems, pushing automation to improve the quality of our life. This triggers the need for a next-generation IoT architecture, satisfying the demand for key sectors like transportation (e.g. self-driving cars), industry (e.g. robotization or predictive maintenance), and our homes (e.g. assisted living). Such applications require building systems of enormous complexity, so that traditional approaches start to fail. The amount of data collected and processed is huge, the computational power required is very high, and the algorithms are too complex allowing for the computation of solutions within the tight time constraints. In addition, security, privacy, or robustness for such systems becomes a critical challenge.<br />
An enabler that aims at delivering the required keystone is VEDLIoT, a Very Efficient Deep Learning IoT platform. Instead of traditional algorithms, artificial intelligence (AI) and deep learning (DL) are used to handle the large complexity. Due to the distributed approach, VEDLIoT allows dividing the application into smaller and more efficient components and work together in large collaborative systems in the Internet of Things (IoT), enabling AI-based algorithms that are distributed over IoT devices from edge to cloud.<br />
In terms of hardware, VEDLIoT offers a platform, the Cognitive IoT platform, leveraging European technology, which can be easily configured to be placed at any level of the compute continuum starting from the sensor nodes and then edge to cloud. Driven by use cases in the key sectors of automotive, industrial, and smart homes, the platform is supported by cross-cutting aspects satisfying security and robustness. Overall, VEDLIoT offers a framework for the Next Generation Internet based on IoT devices required for collaboratively solving complex DL applications across a distributed system.<br />
|NavigatorsSite=FCUL<br />
|Team Size=3<br />
|Researchers=António Casimiro, Pedro M. Ferreira, Nuno Ferreira Neves, José Cecílio, Alysson Bessani<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Timeliness_and_Adaptation_in_Dependable_Systems_(TADS)Timeliness and Adaptation in Dependable Systems (TADS)2021-11-18T17:48:32Z<p>Casim: </p>
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<div>{{ResearchLine<br />
|Acronym=TADS<br />
|Name=Timeliness and Adaptation in Dependable Systems<br />
|Leadership=António Casimiro<br />
|Core members=Pedro Ferreira, José Cecílio, Alan Oliveira, <br />
|Objectives=The objectives of this research line encompass the study of models, algorithms and platforms, which take into account the requirements of several classes of applications, with the aim of ensuring timely and safe operation. One of the major challenges to these objectives consists in assuming that applications, despite these demanding goals, can operate in open and unpredictable environments, like the Internet. The design of dependable and real-time applications is traditionally difficult, if not impossible, in this kind of environments. It is proposed to deal with this question in the context of intermediate or partial synchrony models, and by fitting the model and the resulting architectures with the appropriate paradigms and devices, namely accurate environment monitoring and quality of service (QoS) adaptation.<br />
|Objectives topics=* study of models, algorithms and platforms, yielding timely and safe operation<br />
* assume that applications can operate in open and unpredictable environments, but still require some form of timeliness guarantees <br />
* study intermediate synchrony and resilience models with accurate self-monitoring and capable of autonomous behaviour and dependable adaptation<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Project:AQUAMONProject:AQUAMON2020-11-17T15:20:29Z<p>Casim: </p>
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<div>{{Project<br />
|Acronym=AQUAMON<br />
|Title=Dependable Monitoring with Wireless Sensor Networks in Water Environments<br />
|Past Project=no<br />
|ResearchLine=Timeliness and Adaptation in Dependable Systems (TADS)<br />
|Url=https://aquamon.di.fc.ul.pt/<br />
|Sponsor=FCT<br />
|Project Number=PTDC/CCI-COM/30142/2017<br />
|Total award amount=239760<br />
|Coordinator=FCUL<br />
|Partners=FEUP, LNEC<br />
|month=oct<br />
|year=2018<br />
|Duration months=36<br />
|Keywords=Sensor networks, Dependability, IoT, Communication protocols, Forecasting<br />
|Summary=Continuous monitoring of aquatic environments using water sensors is important for several applications related to the prevention of accidents, to water resources and aquaculture management and recreational activities. Thus, it is fundamental to ensure the quality of the monitoring data in order to avoid false alarms or ignoring relevant events.<br />
However, operating these sensors in the water environment presents several challenges with clear consequences on data quality. For instance, sensors are constantly being subjected to factors that directly interfere with data quality, such as potentially strong currents and debris accumulation, and communication with sensors, affected by waves and more interferences.<br />
AQUAMON will develop a dependable monitoring platform for application in aquatic environments using wireless sensor networks, addressing some of these challenges. In particular, it will address data communication quality problems over water surfaces, due to waves and propagation characteristics over a water surface, transmission predictability, due to shared medium access contention, and data quality, caused by faults that affect both sensors and communication, creating data errors and data loss.<br />
|NavigatorsSite=FCUL<br />
|Team Size=7<br />
|Researchers=António Casimiro, Pedro M. Ferreira, Carlos Nascimento, José Cecílio, Gonçalo Jesus, João Penim, José Soares, <br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Project:AQUAMONProject:AQUAMON2020-11-17T15:19:54Z<p>Casim: </p>
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<div>{{Project<br />
|Acronym=AQUAMON<br />
|Title=Dependable Monitoring with Wireless Sensor Networks in Water Environments<br />
|Past Project=no<br />
|ResearchLine=Timeliness and Adaptation in Dependable Systems (TADS)<br />
|Url=https://aquamon.di.fc.ul.pt/<br />
|Sponsor=FCT<br />
|Project Number=PTDC/CCI-COM/30142/2017<br />
|Total award amount=239760<br />
|Coordinator=FCUL<br />
|Partners=FEUP, LNEC<br />
|month=oct<br />
|year=2018<br />
|Duration months=36<br />
|Keywords=Sensor networks, Dependability, IoT, Communication protocols, Forecasting<br />
|Summary=Continuous monitoring of aquatic environments using water sensors is important for several applications related to the prevention of accidents, to water resources and aquaculture management and recreational activities. Thus, it is fundamental to ensure the quality of the monitoring data in order to avoid false alarms or ignoring relevant events.<br />
However, operating these sensors in the water environment presents several challenges with clear consequences on data quality. For instance, sensors are constantly being subjected to factors that directly interfere with data quality, such as potentially strong currents and debris accumulation, and communication with sensors, affected by waves and more interferences.<br />
AQUAMON will develop a dependable monitoring platform for application in aquatic environments using wireless sensor networks, addressing some of these challenges. In particular, it will address data communication quality problems over water surfaces, due to waves and propagation characteristics over a water surface, transmission predictability, due to shared medium access contention, and data quality, caused by faults that affect both sensors and communication, creating data errors and data loss.<br />
|NavigatorsSite=FCUL<br />
|Team Size=6<br />
|Researchers=António Casimiro, Pedro M. Ferreira, Carlos Nascimento, José Cecílio, Gonçalo Jesus, João Penim<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Project:AQUAMONProject:AQUAMON2020-11-17T15:19:21Z<p>Casim: </p>
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<div>{{Project<br />
|Acronym=AQUAMON<br />
|Title=Dependable Monitoring with Wireless Sensor Networks in Water Environments<br />
|Past Project=no<br />
|ResearchLine=Timeliness and Adaptation in Dependable Systems (TADS)<br />
|Url=https://aquamon.di.fc.ul.pt/<br />
|Sponsor=FCT<br />
|Project Number=PTDC/CCI-COM/30142/2017<br />
|Total award amount=239760<br />
|Coordinator=FCUL<br />
|Partners=FEUP, LNEC<br />
|month=oct<br />
|year=2018<br />
|Duration months=36<br />
|Keywords=Sensor networks, Dependability, IoT, Communication protocols, Forecasting<br />
|Summary=Continuous monitoring of aquatic environments using water sensors is important for several applications related to the prevention of accidents, to water resources and aquaculture management and recreational activities. Thus, it is fundamental to ensure the quality of the monitoring data in order to avoid false alarms or ignoring relevant events.<br />
However, operating these sensors in the water environment presents several challenges with clear consequences on data quality. For instance, sensors are constantly being subjected to factors that directly interfere with data quality, such as potentially strong currents and debris accumulation, and communication with sensors, affected by waves and more interferences.<br />
AQUAMON will develop a dependable monitoring platform for application in aquatic environments using wireless sensor networks, addressing some of these challenges. In particular, it will address data communication quality problems over water surfaces, due to waves and propagation characteristics over a water surface, transmission predictability, due to shared medium access contention, and data quality, caused by faults that affect both sensors and communication, creating data errors and data loss.<br />
|NavigatorsSite=FCUL<br />
|Team Size=3<br />
|Researchers=António Casimiro, Pedro M. Ferreira, Carlos Nascimento, José Cecílio, Gonçalo Jesus, <br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Project:AQUAMONProject:AQUAMON2020-11-17T15:18:31Z<p>Casim: </p>
<hr />
<div>{{Project<br />
|Acronym=AQUAMON<br />
|Title=Dependable Monitoring with Wireless Sensor Networks in Water Environments<br />
|Past Project=no<br />
|ResearchLine=Timeliness and Adaptation in Dependable Systems (TADS)<br />
|Url=https://aquamon.di.fc.ul.pt/<br />
|Sponsor=FCT<br />
|Project Number=PTDC/CCI-COM/30142/2017<br />
|Total award amount=239760<br />
|Coordinator=FCUL<br />
|Partners=FEUP, LNEC<br />
|month=oct<br />
|year=2018<br />
|Duration months=36<br />
|Keywords=Sensor networks, Dependability, IoT, Communication protocols, Forecasting<br />
|Summary=Continuous monitoring of aquatic environments using water sensors is important for several applications related to the prevention of accidents, to water resources and aquaculture management and recreational activities. Thus, it is fundamental to ensure the quality of the monitoring data in order to avoid false alarms or ignoring relevant events.<br />
However, operating these sensors in the water environment presents several challenges with clear consequences on data quality. For instance, sensors are constantly being subjected to factors that directly interfere with data quality, such as potentially strong currents and debris accumulation, and communication with sensors, affected by waves and more interferences.<br />
AQUAMON will develop a dependable monitoring platform for application in aquatic environments using wireless sensor networks, addressing some of these challenges. In particular, it will address data communication quality problems over water surfaces, due to waves and propagation characteristics over a water surface, transmission predictability, due to shared medium access contention, and data quality, caused by faults that affect both sensors and communication, creating data errors and data loss.<br />
|NavigatorsSite=FCUL<br />
|Team Size=3<br />
|Researchers=António Casimiro, Pedro M. Ferreira, Carlos Nascimento,<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Project:ADMORPHProject:ADMORPH2020-11-17T15:17:34Z<p>Casim: </p>
<hr />
<div>{{Project<br />
|Acronym=ADMORPH<br />
|Title=Towards Adaptively Morphing Embedded Systems<br />
|Past Project=no<br />
|ResearchLine=Fault and Intrusion Tolerance in Open Distributed Systems (FIT), Timeliness and Adaptation in Dependable Systems (TADS)<br />
|Url=http://admorph.eu<br />
|Sponsor=EU H2020 program<br />
|Project Number=871259<br />
|Total award amount=4499000<br />
|Coordinator=Univ. of Amsterdam (NL)<br />
|Partners=Thales Netherland (NL), Sysgo S.A.S (FR), Univ. Luxembourg (LU), Lunds Univ. (SE), UTRC (IE), Q-Media (CZ), FCUL (PT)<br />
|month=jan<br />
|year=2020<br />
|Duration months=36<br />
|Keywords=System of systems, Embedded systems, Monitoring and control systems, Systems engineering, sensorics, actorics, automation<br />
|Summary=Due to the increasing performance demands of mission- and safety-critical Cyber Physical Systems (of Systems) – after this referred to as CPS(oS) – these systems exhibit a rapidly growing complexity, manifested by an increasing number of (distributed) computational cores and application components connected via complex networks. However, with the growing complexity and interconnectivity of these systems, the chances of hardware failures as well as disruptions due to cyber-attacks will also quickly increase. System adaptivity, foremost in terms of dynamically remapping of application components to processing cores, represents a promising technique to fuse fault- and intrusion tolerance with the increasing performance requirements of these mission- and safety-critical CPS(oS). In the ADMORPH project, we evaluate this hypothesis using a novel, holistic approach to the specification, design, analysis and runtime deployment of adaptive, i.e., dynamically morphing, mission- and safety-critical CPS(oS) that are robust against both component failures and cyber-attacks. To this end, we will address four aspects that are instrumental for the realization of these adaptively morphing systems: (i) the formal specification of adaptive systems; (ii) adaptivity methods like strategies for maintaining safe and secure control of CPS(oS); (iii) analysis techniques for adaptive systems to, e.g., perform timing verification of adaptive systems to avoid timing violations after system reconfigurations; and (iv) run-time systems for adaptive systems that realize the actual run-time system reconfigurations to achieve fault and intrusion tolerance. The developed methodologies, methods and tools will be evaluated using three industrial use cases taken from the radar surveillance systems, autonomous operations for aircrafts, and transport management systems domains.<br />
|NavigatorsSite=FCUL<br />
|Team Size=4<br />
|Researchers=António Casimiro, Pedro M. Ferreira, Alysson Bessani, Nuno Ferreira Neves,<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Publication:Gon%C3%A7aloJesusPhDThesisPublication:GonçaloJesusPhDThesis2020-10-02T12:18:31Z<p>Casim: Created page with "{{Publication |type=phdthesis |title=A dependability framework for WSN-based aquatic monitoring systems |author=Gonçalo Jesus |Project=Project:AQUAMON, |ResearchLine=Timeliness..."</p>
<hr />
<div>{{Publication<br />
|type=phdthesis<br />
|title=A dependability framework for WSN-based aquatic monitoring systems<br />
|author=Gonçalo Jesus<br />
|Project=Project:AQUAMON, <br />
|ResearchLine=Timeliness and Adaptation in Dependable Systems (TADS)<br />
|month=nov<br />
|year=2019<br />
|abstract=Wireless Sensor Networks (WSN) are being progressively used in several application areas, particularly to collect data and monitor physical processes. Moreover, sensor nodes used in environmental monitoring applications, such as the aquatic sensor networks, are often subject to harsh environmental conditions while monitoring complex phenomena. Non-functional requirements, like reliability, security or availability, are increasingly important and must be accounted for in the application development. For that purpose, there is a large body of knowledge on dependability techniques for distributed systems, which provides a good basis to understand how to satisfy these non-functional requirements of WSN-based monitoring applications. Given the data-centric nature of monitoring applications, it is of particular importance to ensure that data is reliable or, more generically, that it has the necessary quality.<br />
The problem of ensuring the desired quality of data for dependable monitoring using WSNs is studied herein. With a dependability-oriented perspective, it is reviewed the possible impairments to dependability and the prominent existing solutions to solve or mitigate these impairments. Despite the variety of components that may form a WSN-based monitoring system, it is given particular attention to understanding which faults can affect sensors, how they can affect the quality of the information, and how this quality can be improved and quantified. Open research issues for the specific case of aquatic monitoring applications are also discussed.<br />
One of the challenges in achieving a dependable system behavior is to overcome the external disturbances affecting sensor measurements and detect the failure patterns in sensor data. This is a particular problem in environmental monitoring, due to the difficulty in distinguishing a faulty behavior from <br />
the representation of a natural phenomenon. Existing solutions for failure detection assume that physical processes can be accurately modeled, or that there are large deviations that may be detected using coarse techniques, or more commonly that it is a high-density sensor network with value redundant sensors.<br />
This thesis aims at defining a new methodology for dependable data quality in environmental monitoring systems, aiming to detect faulty measurements and increase the sensors data quality. The framework of the methodology is overviewed through a generically applicable design, which can be employed to any environment sensor network dataset.<br />
The methodology is evaluated in various datasets of different WSNs, where it is used machine learning to model each sensor behavior, exploiting the existence of correlated data provided by neighbor sensors. It is intended to explore the data fusion strategies in order to effectively detect potential failures for each sensor and, simultaneously, distinguish truly abnormal measurements from deviations due to natural phenomena. This is accomplished with the successful application of the methodology to detect and correct outliers, offset and drifting failures in real monitoring networks datasets.<br />
In the future, the methodology can be applied to optimize the data quality control processes of new and already operating monitoring networks, and assist in the networks maintenance operations.<br />
|school=Departamento de Informática, Faculdade de Ciências, Universidade de Lisboa<br />
|advisor=António Casimiro, Anabela Oliveira<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Tiago_OliveiraTiago Oliveira2020-10-02T12:02:34Z<p>Casim: </p>
<hr />
<div>{{Person<br />
|name=Tiago Oliveira<br />
|role=Past member<br />
|advisor=Alysson Bessani<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Ricardo_MendesRicardo Mendes2020-10-02T12:02:16Z<p>Casim: </p>
<hr />
<div>{{Person<br />
|name=Ricardo Mendes<br />
|role=Past member<br />
|advisor=Alysson Bessani<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Kleomar_AlmeidaKleomar Almeida2020-10-02T12:01:32Z<p>Casim: </p>
<hr />
<div>{{Person<br />
|name=Kleomar Almeida<br />
|email=kleomar@lasige.di.fc.ul.pt<br />
|phone=(+351) 937726416 / (+351) 916537952<br />
|role=Past member<br />
|advisor=José Rufino, Ricardo Pinto,<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Jo%C3%A3o_PintoJoão Pinto2020-10-02T12:01:15Z<p>Casim: </p>
<hr />
<div>{{Person<br />
|name=João Pinto<br />
|email=jpinto@lasige.di.fc.ul.pt<br />
|role=Past member<br />
|advisor=António Casimiro, Naercio Magaia<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Carlos_NascimentoCarlos Nascimento2020-10-02T12:00:58Z<p>Casim: </p>
<hr />
<div>{{Person<br />
|name=Carlos Nascimento<br />
|email=cnascimento@lasige.di.fc.ul.pt<br />
|role=Past member<br />
|advisor=António Casimiro, Pedro M. Ferreira,<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Rui_Pedro_CaldeiraRui Pedro Caldeira2020-10-02T12:00:41Z<p>Casim: </p>
<hr />
<div>{{Person<br />
|name=Rui Pedro Caldeira<br />
|email=rcaldeira@lasige.di.fc.ul.pt<br />
|url=http://lasige.di.fc.ul.pt/~rcaldeira<br />
|phone=(+351) 21 750 00 00 - Ext: 26335<br />
|role=Past member<br />
|advisor=José Rufino, Ricardo Correia Pinto,<br />
|shortbio=Finishing his masters degree in Computer Science, Rui collaborates with [http://lasige.di.fc.ul.pt LaSIGE] (Large-Scale Informatics Systems Laboratory) under the [http://www.navigators.di.fc.ul.pt/wiki/Project:KARYON Karyon] and [http://www.navigators.di.fc.ul.pt/wiki/Project:READAPT READAPT] projects since September 2012. His research interests revolve around Computer Networks, Embedded and Real-Time Systems, Wireless Sensor Networks and Time and Space Partitioned Systems.<br /><br />
<br /><br />
'''Current Contributions:'''<br /><br />
*[http://www.navigators.di.fc.ul.pt/wiki/Project:KARYON Karyon Project:]<br /><br />
**Deliverable 3.2: [http://goo.gl/YQGJTb http://goo.gl/YQGJTb]<br /><br />
**Deliverable 3.3: [http://goo.gl/hxZcmE http://goo.gl/hxZcmE]<br /><br />
**Deliverable 3.5: [http://goo.gl/DWSsX9 http://goo.gl/DWSsX9]<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Tiago_CorreiaTiago Correia2020-10-02T12:00:13Z<p>Casim: </p>
<hr />
<div>{{Person<br />
|name=Tiago Correia<br />
|email=tcorreia@lasige.di.fc.ul.pt<br />
|role=Past member<br />
|advisor=António Casimiro, Naercio Magaia<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Eric_VialEric Vial2020-10-02T11:57:35Z<p>Casim: </p>
<hr />
<div>{{Person<br />
|name=Eric Vial<br />
|role=Past member<br />
|advisor=António Casimiro, Nuno Ferreira Neves,<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Lu%C3%ADs_MarquesLuís Marques2020-10-02T11:57:05Z<p>Casim: </p>
<hr />
<div>{{Person<br />
|name=Luís Marques<br />
|role=Past member<br />
|advisor=António Casimiro,<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Fernando_RamosFernando Ramos2020-10-02T11:56:18Z<p>Casim: </p>
<hr />
<div>{{Person<br />
|name=Fernando M. V. Ramos<br />
|email=fvramos@ciencias.ulisboa.pt<br />
|url=http://www.di.fc.ul.pt/~fvramos/<br />
|role=Past member<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Gon%C3%A7alo_JesusGonçalo Jesus2020-10-02T11:55:44Z<p>Casim: </p>
<hr />
<div>{{Person<br />
|name=Gonçalo Jesus<br />
|role=Past member<br />
|advisor=António Casimiro, Anabela Oliveira<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Carlos_M%C3%A3o_de_FerroCarlos Mão de Ferro2020-10-02T11:55:04Z<p>Casim: </p>
<hr />
<div>{{Person<br />
|name=Carlos Mão de Ferro<br />
|email=cjferro@fc.ul.pt<br />
|role=PhD student<br />
|advisor=António Casimiro, Francisco Martins<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Rohit_KumarRohit Kumar2020-10-02T11:53:33Z<p>Casim: Created page with "{{Person |name=Rohit Kumar |email=rkumar@fc.ul.pt |role=PhD student |advisor=António Casimiro, }}"</p>
<hr />
<div>{{Person<br />
|name=Rohit Kumar<br />
|email=rkumar@fc.ul.pt<br />
|role=PhD student<br />
|advisor=António Casimiro, <br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Project:VEDLIoTProject:VEDLIoT2020-10-02T11:36:31Z<p>Casim: Created page with "{{Project |Acronym=VEDLIoT |Title=Very Efficient Deep Learning in IOT |Past Project=no |Sponsor=EU H2020 program |Project Number=957197 |Total award amount=8000000 |Coordinator=U..."</p>
<hr />
<div>{{Project<br />
|Acronym=VEDLIoT<br />
|Title=Very Efficient Deep Learning in IOT<br />
|Past Project=no<br />
|Sponsor=EU H2020 program<br />
|Project Number=957197<br />
|Total award amount=8000000<br />
|Coordinator=Univ. of Bielefeld<br />
|Partners=EMBEDL AB (SE), Chalmers (SE), Siemens (DE), Christmann (DE), Université de Neuchâtel (CH), Universität Osnabrück (DE), VEONEER (SE), Göteborgs Universitet (SE), RISE Research Institutes of Sweden (SE), FCiências.ID (PT), Antmicro (PL)<br />
|month=nov<br />
|year=2020<br />
|Duration months=36<br />
|Keywords=Machine learning, Distributed AI, Internet of Things, Embedded computing, Sensor networks, Interoperability, Heterogeneous computing, Cognitive edge computing<br />
|Summary=The ever increasing performance of computer systems in general and IoT systems, in particular, delivers the capability to solve increasingly challenging problems, pushing automation to improve the quality of our life. This triggers the need for a next-generation IoT architecture, satisfying the demand for key sectors like transportation (e.g. self-driving cars), industry (e.g. robotization or predictive maintenance), and our homes (e.g. assisted living). Such applications require building systems of enormous complexity, so that traditional approaches start to fail. The amount of data collected and processed is huge, the computational power required is very high, and the algorithms are too complex allowing for the computation of solutions within the tight time constraints. In addition, security, privacy, or robustness for such systems becomes a critical challenge.<br />
An enabler that aims at delivering the required keystone is VEDLIoT, a Very Efficient Deep Learning IoT platform. Instead of traditional algorithms, artificial intelligence (AI) and deep learning (DL) are used to handle the large complexity. Due to the distributed approach, VEDLIoT allows dividing the application into smaller and more efficient components and work together in large collaborative systems in the Internet of Things (IoT), enabling AI-based algorithms that are distributed over IoT devices from edge to cloud.<br />
In terms of hardware, VEDLIoT offers a platform, the Cognitive IoT platform, leveraging European technology, which can be easily configured to be placed at any level of the compute continuum starting from the sensor nodes and then edge to cloud. Driven by use cases in the key sectors of automotive, industrial, and smart homes, the platform is supported by cross-cutting aspects satisfying security and robustness. Overall, VEDLIoT offers a framework for the Next Generation Internet based on IoT devices required for collaboratively solving complex DL applications across a distributed system.<br />
|Team Size=3<br />
|Researchers=António Casimiro, Pedro M. Ferreira, Nuno Ferreira Neves, <br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Carlos_M%C3%A3o_de_FerroCarlos Mão de Ferro2020-07-08T17:56:24Z<p>Casim: Created page with "{{Person |name=Carlos Mão de Ferro |email=cjferro@fc.ul.pt |role=PhD student |advisor=António Casimiro, }}"</p>
<hr />
<div>{{Person<br />
|name=Carlos Mão de Ferro<br />
|email=cjferro@fc.ul.pt<br />
|role=PhD student<br />
|advisor=António Casimiro, <br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Publication:Casimiro2020TIEPublication:Casimiro2020TIE2020-07-04T16:32:30Z<p>Casim: </p>
<hr />
<div>{{Publication<br />
|type=article<br />
|title=Model-Based Stealth Attack to Networked Control System Based on Real-Time Ethernet<br />
|author=Paolo Ferrari, Emiliano Sisinni, Paolo Bellagente, Stefano Rinaldi, Marco Pasetti, Alan Oliveira de Sá, Raphael C. S. Machado, And Luiz F. R. da C. Carmo, António Casimiro, <br />
|ResearchLine=Fault and Intrusion Tolerance in Open Distributed Systems (FIT), Timeliness and Adaptation in Dependable Systems (TADS)<br />
|month=jun<br />
|year=2020<br />
|abstract=Industrial control systems (ICS) include networked control systems (NCS), which use Real-Time Ethernet (RTE) protocols since many years, well before the Time Sensitive Networking (TSN) initiative debut. Today, Ethernet based control systems are used all across Industry 4.0, including in critical applications, allowing for straight integration with IT layers. Even if it is known that current RTE protocols do not have strong authentication or ciphering options, it is still very challenging to perform undetected cyber-attacks to these protocols while the NSC is in operation, in particular because such attacks must comply with very strict and small temporal constraints. In this paper, a model based attack is proposed for service degradation of NCS. The attack is carried out in real-time and it can remain undetected for the entire plant life. The attack can be applied to any RTE protocols and, without loss of generality, a detailed analysis of stealth techniques is provided for a specific real use case based on PROFINET. The experimental results demonstrate the feasibility of the proposed attack and its high effectiveness. The paper also points out some possible future investigation directions in order to mitigate the attack.<br />
|journal=IEEE Transactions on Industrial Electronics<br />
|note=DOI: 10.1109/TIE.2020.3001850<br />
|volume=Early Access<br />
|pages=1&ndash;1<br />
|publisher=IEEE<br />
|url=DOI: 10.1109/TIE.2020.3001850<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Publication:Casimiro2020TIEPublication:Casimiro2020TIE2020-07-04T16:30:26Z<p>Casim: </p>
<hr />
<div>{{Publication<br />
|type=article<br />
|title=Model-Based Stealth Attack to Networked Control System Based on Real-Time Ethernet<br />
|author=Paolo Ferrari<br />
|ResearchLine=Fault and Intrusion Tolerance in Open Distributed Systems (FIT), Timeliness and Adaptation in Dependable Systems (TADS)<br />
|month=jun<br />
|year=2020<br />
|abstract=Industrial control systems (ICS) include networked control systems (NCS), which use Real-Time Ethernet (RTE) protocols since many years, well before the Time Sensitive Networking (TSN) initiative debut. Today, Ethernet based control systems are used all across Industry 4.0, including in critical applications, allowing for straight integration with IT layers. Even if it is known that current RTE protocols do not have strong authentication or ciphering options, it is still very challenging to perform undetected cyber-attacks to these protocols while the NSC is in operation, in particular because such attacks must comply with very strict and small temporal constraints. In this paper, a model based attack is proposed for service degradation of NCS. The attack is carried out in real-time and it can remain undetected for the entire plant life. The attack can be applied to any RTE protocols and, without loss of generality, a detailed analysis of stealth techniques is provided for a specific real use case based on PROFINET. The experimental results demonstrate the feasibility of the proposed attack and its high effectiveness. The paper also points out some possible future investigation directions in order to mitigate the attack.<br />
|journal=IEEE Transactions on Industrial Electronics<br />
|note=DOI: 10.1109/TIE.2020.3001850<br />
|volume=Early Access<br />
|pages=1&ndash;1<br />
|publisher=IEEE<br />
|url=DOI: 10.1109/TIE.2020.3001850<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Publication:Casimiro2020TIEPublication:Casimiro2020TIE2020-07-04T16:28:52Z<p>Casim: </p>
<hr />
<div>{{Publication<br />
|type=article<br />
|title=Model-Based Stealth Attack to Networked Control System Based on Real-Time Ethernet<br />
|author=Paolo Ferrari; Emiliano Sisinni; Paolo Bellagente; Stefano Rinaldi; Marco Pasetti; Alan Oliveira de Sá; Raphael C. S. Machado; Luiz F. R. da C. Carmo; António Casimiro<br />
|ResearchLine=Fault and Intrusion Tolerance in Open Distributed Systems (FIT), Timeliness and Adaptation in Dependable Systems (TADS)<br />
|month=jun<br />
|year=2020<br />
|abstract=Industrial control systems (ICS) include networked control systems (NCS), which use Real-Time Ethernet (RTE) protocols since many years, well before the Time Sensitive Networking (TSN) initiative debut. Today, Ethernet based control systems are used all across Industry 4.0, including in critical applications, allowing for straight integration with IT layers. Even if it is known that current RTE protocols do not have strong authentication or ciphering options, it is still very challenging to perform undetected cyber-attacks to these protocols while the NSC is in operation, in particular because such attacks must comply with very strict and small temporal constraints. In this paper, a model based attack is proposed for service degradation of NCS. The attack is carried out in real-time and it can remain undetected for the entire plant life. The attack can be applied to any RTE protocols and, without loss of generality, a detailed analysis of stealth techniques is provided for a specific real use case based on PROFINET. The experimental results demonstrate the feasibility of the proposed attack and its high effectiveness. The paper also points out some possible future investigation directions in order to mitigate the attack.<br />
|journal=IEEE Transactions on Industrial Electronics<br />
|note=DOI: 10.1109/TIE.2020.3001850<br />
|volume=Early Access<br />
|pages=1&ndash;1<br />
|publisher=IEEE<br />
|url=DOI: 10.1109/TIE.2020.3001850<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Publication:Casimiro2020TIEPublication:Casimiro2020TIE2020-07-04T16:27:04Z<p>Casim: </p>
<hr />
<div>{{Publication<br />
|type=article<br />
|title=Model-Based Stealth Attack to Networked Control System Based on Real-Time Ethernet<br />
|author=Paolo Ferrari; Emiliano Sisinni; Paolo Bellagente; Stefano Rinaldi; Marco Pasetti; Alan Oliveira de Sá; Raphael C. S. Machado; Luiz F. R. da C. Carmo; António Casimiro<br />
|ResearchLine=Fault and Intrusion Tolerance in Open Distributed Systems (FIT), Timeliness and Adaptation in Dependable Systems (TADS)<br />
|month=jun<br />
|year=2020<br />
|abstract=Industrial control systems (ICS) include networked control systems (NCS), which use Real-Time Ethernet (RTE) protocols since many years, well before the Time Sensitive Networking (TSN) initiative debut. Today, Ethernet based control systems are used all across Industry 4.0, including in critical applications, allowing for straight integration with IT layers. Even if it is known that current RTE protocols do not have strong authentication or ciphering options, it is still very challenging to perform undetected cyber-attacks to these protocols while the NSC is in operation, in particular because such attacks must comply with very strict and small temporal constraints. In this paper, a model based attack is proposed for service degradation of NCS. The attack is carried out in real-time and it can remain undetected for the entire plant life. The attack can be applied to any RTE protocols and, without loss of generality, a detailed analysis of stealth techniques is provided for a specific real use case based on PROFINET. The experimental results demonstrate the feasibility of the proposed attack and its high effectiveness. The paper also points out some possible future investigation directions in order to mitigate the attack.<br />
|journal=IEEE Transactions on Industrial Electronics<br />
|volume=Early Access<br />
|pages=1&ndash;1<br />
|publisher=IEEE<br />
|url=DOI: 10.1109/TIE.2020.3001850<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Publication:Casimiro2020TIEPublication:Casimiro2020TIE2020-07-04T16:09:24Z<p>Casim: </p>
<hr />
<div>{{Publication<br />
|type=article<br />
|title=Model-Based Stealth Attack to Networked Control System Based on Real-Time Ethernet<br />
|author=Paolo Ferrari,Emiliano Sisinni, Paolo Bellagente, Stefano Rinaldi, Marco Pasetti, Alan Oliveira de Sá, Raphael C. S. Machado, Luiz F. R. da C. Carmo and António Casimiro<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Publication:Casimiro2020TIEPublication:Casimiro2020TIE2020-07-04T16:09:07Z<p>Casim: Created page with "{{Publication |type=article |title=Model-Based Stealth Attack to Networked Control System Based on Real-Time Ethernet |author=Paolo Ferrari, Emiliano Sisinni, Paolo Bellagente, S..."</p>
<hr />
<div>{{Publication<br />
|type=article<br />
|title=Model-Based Stealth Attack to Networked Control System Based on Real-Time Ethernet<br />
|author=Paolo Ferrari, Emiliano Sisinni, Paolo Bellagente, Stefano Rinaldi, Marco Pasetti, Alan Oliveira de Sá, Raphael C. S. Machado, Luiz F. R. da C. Carmo and António Casimiro<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Publication:Sa2020SensorsPublication:Sa2020Sensors2020-02-06T13:36:53Z<p>Casim: </p>
<hr />
<div>{{Publication<br />
|type=article<br />
|document=Document for Publication-Sa2020Sensors.pdf<br />
|title=Identification of Data Injection Attacks in Networked Control Systems Using Noise Impulse Integration<br />
|author=Alan Oliveira de Sá, António Casimiro, Raphael C. S. Machado, and Luiz F. R. da C. Carmo<br />
|ResearchLine=Fault and Intrusion Tolerance in Open Distributed Systems (FIT), Timeliness and Adaptation in Dependable Systems (TADS)<br />
|month=jan<br />
|year=2020<br />
|abstract=The benefits of using Networked Control Systems (NCS) in the growing Industry 4.0 are numerous, including better management and operational capabilities, as well as costs reduction. However, despite these benefits, the use of NCSs can also expose physical plants to new threats originated in the cyber domain—such as data injection attacks in NCS links through which sensors and controllers transmit signals. In this sense, this work proposes a link monitoring strategy to identify linear time-invariant (LTI) functions executed during controlled data injection attacks by a Man-in-the-Middle hosted in an NCS link. The countermeasure is based on a bioinspired metaheuristic, called Backtracking Search Optimization Algorithm (BSA), and uses white Gaussian noise to excite the attack function. To increase the accuracy of this countermeasure, it is proposed the Noise Impulse Integration (NII) technique, which is developed using the radar pulse integration technique as inspiration. The results demonstrate that the proposed countermeasure is able to accurately identify LTI attack functions, here executed to impair measurements transmitted by the plant sensor, without interfering with the NCS behavior when the system is in its normal operation. Moreover, the results indicate that the NII technique can increase the accuracy of the attack identification.<br />
|journal=Sensors<br />
|volume=20<br />
|number=792<br />
|publisher=MDPI<br />
}}<br />
25 pages</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Publication:Sa2020SensorsPublication:Sa2020Sensors2020-02-06T13:34:13Z<p>Casim: Created page with "{{Publication |type=article |document=Document for Publication-Sa2020Sensors.pdf |title=Identification of Data Injection Attacks in Networked Control Systems Using Noise Impulse ..."</p>
<hr />
<div>{{Publication<br />
|type=article<br />
|document=Document for Publication-Sa2020Sensors.pdf<br />
|title=Identification of Data Injection Attacks in Networked Control Systems Using Noise Impulse Integration<br />
|author=Alan Oliveira de Sá, António Casimiro, Raphael C. S. Machado, and Luiz F. R. da C. Carmo<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/File:Document_for_Publication-Sa2020Sensors.pdfFile:Document for Publication-Sa2020Sensors.pdf2020-02-06T13:33:17Z<p>Casim: </p>
<hr />
<div></div>Casimhttps://navigators.di.fc.ul.pt/wiki/Publication:Casimiro2019SRDS-FAPublication:Casimiro2019SRDS-FA2020-01-24T13:50:14Z<p>Casim: </p>
<hr />
<div>{{Publication<br />
|type=inproceedings<br />
|document=Document for Publication-Casimiro2019SRDS-FA.pdf<br />
|title=Self-stabilizing Manoeuvre Negotiation: the Case of Virtual Traffic Lights<br />
|author=António Casimiro, Emelie Ekenstedt, Elad M. Schiller<br />
|ResearchLine=Timeliness and Adaptation in Dependable Systems (TADS)<br />
|month=sep<br />
|year=2019<br />
|abstract=The vision of automated driving promises to have safer and more cost-efficient transport systems. Automated driving systems have to demonstrate high levels of dependability and affordability. Recent advances of new communication technologies, e.g., 5G, allow significant cost reduction of timely shared sensory information. However, the design of fault-tolerant automated driving systems remains an open challenge. This work considers the design of automated driving systems through the lenses of self-stabilization — a very strong notion of fault-tolerance. Our self-stabilizing algorithms guarantee, within a bounded period, recovery from a broad fault model and arbitrary state corruption. After this recovery period, our algorithms provide safe maneuver execution despite the presence of failures, such as unbounded periods of packet loss and timing failures as well as inaccurate sensory information and malicious behavior. We evaluate the proposed algorithms through a rigorous correctness proof and a worst-case analysis as well as a prototype that focuses on an intersection crossing protocol. We validate our prototype via computer simulations and a testbed implementation. Our preliminary results show a reduction in the number of vehicle collisions and dangerous situations.<br />
|address=Lyon, France<br />
|booktitle=38th International Symposium on Reliable Distributed Systems (SRDS 2019), Poster Session<br />
}}<br />
Extended version available on arXiv: https://arxiv.org/abs/1906.04703</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Publication:Jesus2018SafecompPublication:Jesus2018Safecomp2019-11-25T23:52:42Z<p>Casim: </p>
<hr />
<div>{{Publication<br />
|type=incollection<br />
|document=Document for Publication-Jesus2018Safecomp.pdf<br />
|title=Dependable Outlier Detection in Harsh Environments Monitoring Systems<br />
|author=Gonçalo Jesus, António Casimiro, Anabela Oliveira,<br />
|ResearchLine=Timeliness and Adaptation in Dependable Systems (TADS)<br />
|month=sep<br />
|year=2018<br />
|abstract=Environmental monitoring systems are composed by sensor networks deployed in uncertain and harsh conditions, vulnerable to external disturbances, posing challenges to the comprehensive system characterization and modelling. When unexpected sensor measurements are produced, there is a need to detect and identify, in a timely manner, if they stem from a failure behavior or if they indeed represent some environment-related process. Existing solutions for fault detection in environmental sensor networks do not portray the required sensitivity for the differentiation of these processes or they are unable to meet the time constraints of the affected cyber-physical systems.<br />
<br />
We have been developing a framework for dependable detection of failures in harsh environments monitoring systems, aiming to improve the overall sensor data quality. Herein we present the application of an early framework implementation to an aquatic sensor network dataset, using neural networks to model sensors’ behaviors, correlated data between neighbor sensors, and a statistical technique to detect the presence of outliers in the datasets.<br />
|booktitle=Computer Safety, Reliability, and Security. SAFECOMP 2018<br />
|editor=Gallina B., Skavhaug A., Schoitsch E., Bitsch F.<br />
|pages=224-233<br />
|publisher=Springer, Cham<br />
|series=Lecture Notes in Computer Science, vol 11094<br />
|url=https://doi.org/10.1007/978-3-319-99229-7_20<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Publication:Jesus2018SafecompPublication:Jesus2018Safecomp2019-11-25T23:51:57Z<p>Casim: </p>
<hr />
<div>{{Publication<br />
|type=incollection<br />
|document=Document for Publication-Jesus2018Safecomp.pdf<br />
|title=Dependable Outlier Detection in Harsh Environments Monitoring Systems<br />
|author=Gonçalo Jesus, António Casimiro, Anabela Oliveira,<br />
|ResearchLine=Timeliness and Adaptation in Dependable Systems (TADS)<br />
|month=sep<br />
|year=2018<br />
|abstract=Environmental monitoring systems are composed by sensor networks deployed in uncertain and harsh conditions, vulnerable to external disturbances, posing challenges to the comprehensive system characterization and modelling. When unexpected sensor measurements are produced, there is a need to detect and identify, in a timely manner, if they stem from a failure behavior or if they indeed represent some environment-related process. Existing solutions for fault detection in environmental sensor networks do not portray the required sensitivity for the differentiation of these processes or they are unable to meet the time constraints of the affected cyber-physical systems.<br />
<br />
We have been developing a framework for dependable detection of failures in harsh environments monitoring systems, aiming to improve the overall sensor data quality. Herein we present the application of an early framework implementation to an aquatic sensor network dataset, using neural networks to model sensors’ behaviors, correlated data between neighbor sensors, and a statistical technique to detect the presence of outliers in the datasets.<br />
|booktitle=Computer Safety, Reliability, and Security. SAFECOMP 2018<br />
|editor=Gallina B., Skavhaug A., Schoitsch E., Bitsch F.<br />
|publisher=Springer, Cham<br />
|series=Lecture Notes in Computer Science, vol 11094<br />
|url=https://doi.org/10.1007/978-3-319-99229-7_20<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Publication:Jesus2018SafecompPublication:Jesus2018Safecomp2019-11-25T23:51:32Z<p>Casim: </p>
<hr />
<div>{{Publication<br />
|type=incollection<br />
|document=Document for Publication-Jesus2018Safecomp.pdf<br />
|title=Dependable Outlier Detection in Harsh Environments Monitoring Systems<br />
|author=Gonçalo Jesus, António Casimiro, Anabela Oliveira,<br />
|ResearchLine=Timeliness and Adaptation in Dependable Systems (TADS)<br />
|month=sep<br />
|year=2018<br />
|abstract=Environmental monitoring systems are composed by sensor networks deployed in uncertain and harsh conditions, vulnerable to external disturbances, posing challenges to the comprehensive system characterization and modelling. When unexpected sensor measurements are produced, there is a need to detect and identify, in a timely manner, if they stem from a failure behavior or if they indeed represent some environment-related process. Existing solutions for fault detection in environmental sensor networks do not portray the required sensitivity for the differentiation of these processes or they are unable to meet the time constraints of the affected cyber-physical systems.<br />
<br />
We have been developing a framework for dependable detection of failures in harsh environments monitoring systems, aiming to improve the overall sensor data quality. Herein we present the application of an early framework implementation to an aquatic sensor network dataset, using neural networks to model sensors’ behaviors, correlated data between neighbor sensors, and a statistical technique to detect the presence of outliers in the datasets.<br />
|address=Västerås, Sweden<br />
|booktitle=Computer Safety, Reliability, and Security. SAFECOMP 2018<br />
|editor=Gallina B., Skavhaug A., Schoitsch E., Bitsch F.<br />
|publisher=Springer, Cham<br />
|series=Lecture Notes in Computer Science, vol 11094<br />
|url=https://doi.org/10.1007/978-3-319-99229-7_20<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Publication:Jesus2018SafecompPublication:Jesus2018Safecomp2019-11-25T23:50:31Z<p>Casim: Created page with "{{Publication |type=incollection |document=Document for Publication-Jesus2018Safecomp.pdf |title=Dependable Outlier Detection in Harsh Environments Monitoring Systems |author=Gon..."</p>
<hr />
<div>{{Publication<br />
|type=incollection<br />
|document=Document for Publication-Jesus2018Safecomp.pdf<br />
|title=Dependable Outlier Detection in Harsh Environments Monitoring Systems<br />
|author=Gonçalo Jesus, António Casimiro, Anabela Oliveira,<br />
|ResearchLine=Timeliness and Adaptation in Dependable Systems (TADS)<br />
|month=sep<br />
|year=2018<br />
|abstract=Environmental monitoring systems are composed by sensor networks deployed in uncertain and harsh conditions, vulnerable to external disturbances, posing challenges to the comprehensive system characterization and modelling. When unexpected sensor measurements are produced, there is a need to detect and identify, in a timely manner, if they stem from a failure behavior or if they indeed represent some environment-related process. Existing solutions for fault detection in environmental sensor networks do not portray the required sensitivity for the differentiation of these processes or they are unable to meet the time constraints of the affected cyber-physical systems.<br />
<br />
We have been developing a framework for dependable detection of failures in harsh environments monitoring systems, aiming to improve the overall sensor data quality. Herein we present the application of an early framework implementation to an aquatic sensor network dataset, using neural networks to model sensors’ behaviors, correlated data between neighbor sensors, and a statistical technique to detect the presence of outliers in the datasets.<br />
|address=Västerås, Sweden<br />
|booktitle=Computer Safety, Reliability, and Security. SAFECOMP 2018<br />
|editor=Gallina B., Skavhaug A., Schoitsch E., Bitsch F.<br />
|volume=11094<br />
|publisher=Springer, Cham<br />
|series=LNCS<br />
|url=https://doi.org/10.1007/978-3-319-99229-7_20<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/File:Document_for_Publication-Jesus2018Safecomp.pdfFile:Document for Publication-Jesus2018Safecomp.pdf2019-11-25T23:44:22Z<p>Casim: </p>
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<div></div>Casimhttps://navigators.di.fc.ul.pt/wiki/Publication:Sa2019BICTPublication:Sa2019BICT2019-11-25T23:39:01Z<p>Casim: </p>
<hr />
<div>{{Publication<br />
|type=incollection<br />
|document=Document for Publication-Sa2019BICT.pdf<br />
|title=Bio-inspired System Identification Attacks in Noisy Networked Control Systems<br />
|author=Alan Oliveira de Sá, António Casimiro, Raphael Carlos Santos Machado, Luiz Fernando Rust da Costa Carmo<br />
|ResearchLine=Timeliness and Adaptation in Dependable Systems (TADS)<br />
|month=mar<br />
|year=2019<br />
|abstract=The possibility of cyberattacks in Networked Control Systems (NCS), along with the growing use of networked controllers in industry and critical infrastructures, is motivating studies about the cybersecurity of these systems. The literature on cybersecurity of NCSs indicates that accurate and covert model-based attacks require high level of knowledge about the models of the attacked system. In this sense, recent works recognize that Bio-inspired System Identification (BiSI) attacks can be considered an effective tool to provide the attacker with the required system models. However, while BiSI attacks have obtained sufficiently accurate models to support the design of model-based attacks, they have demonstrated loss of accuracy in the presence of noisy signals. In this work, a noise processing technique is proposed to improve the accuracy of BiSI attacks in noisy NCSs. The technique is implemented along with a bio-inspired metaheuristic that was previously used in other BiSI attacks: the Backtracking Search Optimization Algorithm (BSA). The results indicate that, with the proposed approach, the accuracy of the estimated models improves. With the proposed noise processing technique, the attacker is able to obtain the model of an NCS by exploiting the noise as a useful information, instead of having it as a negative factor for the performance of the identification process.<br />
|booktitle=Bio-inspired Information and Communication Technologies. BICT 2019.<br />
|editor=Compagnoni A., Casey W., Cai Y., Mishra B.<br />
|volume=289<br />
|pages=28-38<br />
|publisher=Springer, Cham<br />
|series=Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering<br />
|url=https://doi.org/10.1007/978-3-030-24202-2_3<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Publication:Sa2019BICTPublication:Sa2019BICT2019-11-25T23:38:21Z<p>Casim: Created page with "{{Publication |type=inproceedings |document=Document for Publication-Sa2019BICT.pdf |title=Bio-inspired System Identi�cation Attacks in Noisy Networked Control Systems |author=..."</p>
<hr />
<div>{{Publication<br />
|type=inproceedings<br />
|document=Document for Publication-Sa2019BICT.pdf<br />
|title=Bio-inspired System Identi�cation Attacks in Noisy Networked Control Systems<br />
|author=Alan Oliveira de Sá, António Casimiro, Raphael Carlos Santos Machado, Luiz Fernando Rust da Costa Carmo<br />
|ResearchLine=Timeliness and Adaptation in Dependable Systems (TADS)<br />
|month=mar<br />
|year=2019<br />
|abstract=The possibility of cyberattacks in Networked Control Systems (NCS), along with the growing use of networked controllers in industry and critical infrastructures, is motivating studies about the cybersecurity of these systems. The literature on cybersecurity of NCSs indicates that accurate and covert model-based attacks require high level of knowledge about the models of the attacked system. In this sense, recent works recognize that Bio-inspired System Identification (BiSI) attacks can be considered an effective tool to provide the attacker with the required system models. However, while BiSI attacks have obtained sufficiently accurate models to support the design of model-based attacks, they have demonstrated loss of accuracy in the presence of noisy signals. In this work, a noise processing technique is proposed to improve the accuracy of BiSI attacks in noisy NCSs. The technique is implemented along with a bio-inspired metaheuristic that was previously used in other BiSI attacks: the Backtracking Search Optimization Algorithm (BSA). The results indicate that, with the proposed approach, the accuracy of the estimated models improves. With the proposed noise processing technique, the attacker is able to obtain the model of an NCS by exploiting the noise as a useful information, instead of having it as a negative factor for the performance of the identification process.<br />
|booktitle=Bio-inspired Information and Communication Technologies. BICT 2019. <br />
|editor=Compagnoni A., Casey W., Cai Y., Mishra B.<br />
|volume=289<br />
|pages=28-38<br />
|publisher=Springer, Cham<br />
|series=Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering<br />
|url=https://doi.org/10.1007/978-3-030-24202-2_3<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/File:Document_for_Publication-Sa2019BICT.pdfFile:Document for Publication-Sa2019BICT.pdf2019-11-25T23:28:22Z<p>Casim: </p>
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<div></div>Casimhttps://navigators.di.fc.ul.pt/wiki/Publication:Casimiro2019SAFECOMP-FAPublication:Casimiro2019SAFECOMP-FA2019-11-25T23:23:01Z<p>Casim: </p>
<hr />
<div>{{Publication<br />
|type=inproceedings<br />
|document=Document for Publication-Casimiro2019SAFECOMP-FA.pdf<br />
|title=AQUAMON – A dependable Monitoring Platform based on Wireless Sensor Networks for Water Environments<br />
|author=António Casimiro, José Cecílio, Pedro M. Ferreira, Anabela Oliveira, Paula Freire, Marta Rodrigues, Luís Almeida<br />
|Project=Project:AQUAMON,<br />
|ResearchLine=Timeliness and Adaptation in Dependable Systems (TADS)<br />
|month=sep<br />
|year=2019<br />
|abstract=Continuous monitoring of aquatic environments using water sensors is important for several applications related to aquaculture and/or water resources management, as well as for recreational activities. Since sensors are constantly being subjected to potentially strong currents and debris accumulation, and the communication between sensors may be affected by waves and electromagnetic interference, operating sensors in the water environment presents several challenges to data quality assurance and to dependable monitoring. Thus, it is funda-mental to address these challenges in order to avoid false alarms or ignoring relevant events.<br />
<br />
In this paper we present the AQUAMON project, whose objective is to develop a dependable platform based on WSNs for monitoring in aquatic environments. The project addresses data communication and data quality problems, by per-forming comparative studies of available wireless technologies with respect to aspects with impact on communication quality and deployment cost and proposing new data processing approaches to detect sensor and network failures affecting data quality and to mitigate the effects of these failures.<br />
|address=Turku, Finland<br />
|booktitle=Safecomp 2019 Fast Abstract<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Publication:Casimiro2019SAFECOMP-FAPublication:Casimiro2019SAFECOMP-FA2019-11-25T23:22:40Z<p>Casim: Created page with "{{Publication |type=inproceedings |document=Document for Publication-Casimiro2019SAFECOMP-FA.pdf |title=AQUAMON – A dependable Monitoring Platform based on Wireless Sensor Netw..."</p>
<hr />
<div>{{Publication<br />
|type=inproceedings<br />
|document=Document for Publication-Casimiro2019SAFECOMP-FA.pdf<br />
|title=AQUAMON – A dependable Monitoring Platform based on Wireless Sensor Networks for Water Environments<br />
|author=António Casimiro, José Cecílio, Pedro M. Ferreira, Anabela Oliveira, Paula Freire, Marta Rodrigues, Luís Almeida<br />
|Project=Project:AQUAMON, <br />
|ResearchLine=Timeliness and Adaptation in Dependable Systems (TADS)<br />
|month=sep<br />
|year=2019<br />
|abstract=Continuous monitoring of aquatic environments using water sensors is important for several applications related to aquaculture and/or water resources management, as well as for recreational activities. Since sensors are constantly being subjected to potentially strong currents and debris accumulation, and the communication between sensors may be affected by waves and electromagnetic interference, operating sensors in the water environment presents several challenges to data quality assurance and to dependable monitoring. Thus, it is funda-mental to address these challenges in order to avoid false alarms or ignoring relevant events.<br />
<br />
In this paper we present the AQUAMON project, whose objective is to develop a dependable platform based on WSNs for monitoring in aquatic environments. The project addresses data communication and data quality problems, by per-forming comparative studies of available wireless technologies with respect to aspects with impact on communication quality and deployment cost and proposing new data processing approaches to detect sensor and network failures affecting data quality and to mitigate the effects of these failures.<br />
|booktitle=Safecomp 2019 Fast Abstract<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/File:Document_for_Publication-Casimiro2019SAFECOMP-FA.pdfFile:Document for Publication-Casimiro2019SAFECOMP-FA.pdf2019-11-25T23:19:01Z<p>Casim: </p>
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<div></div>Casimhttps://navigators.di.fc.ul.pt/wiki/Publication:Casimiro2019SRDS-FAPublication:Casimiro2019SRDS-FA2019-11-25T23:16:44Z<p>Casim: </p>
<hr />
<div>{{Publication<br />
|type=inproceedings<br />
|document=Document for Publication-Casimiro2019SRDS-FA.pdf<br />
|title=Self-stabilizing Manoeuvre Negotiation: the Case of Virtual Traffic Lights<br />
|author=António Casimiro, Emelie Ekenstedt, Elad M. Schiller<br />
|ResearchLine=Timeliness and Adaptation in Dependable Systems (TADS)<br />
|month=sep<br />
|year=2019<br />
|abstract=The vision of automated driving promises to have safer and more cost-efficient transport systems. Automated driving systems have to demonstrate high levels of dependability and affordability. Recent advances of new communication technologies, e.g., 5G, allow significant cost reduction of timely shared sensory information. However, the design of fault-tolerant automated driving systems remains an open challenge. This work considers the design of automated driving systems through the lenses of self-stabilization — a very strong notion of fault-tolerance. Our self-stabilizing algorithms guarantee, within a bounded period, recovery from a broad fault model and arbitrary state corruption. After this recovery period, our algorithms provide safe maneuver execution despite the presence of failures, such as unbounded periods of packet loss and timing failures as well as inaccurate sensory information and malicious behavior. We evaluate the proposed algorithms through a rigorous correctness proof and a worst-case analysis as well as a prototype that focuses on an intersection crossing protocol. We validate our prototype via computer simulations and a testbed implementation. Our preliminary results show a reduction in the number of vehicle collisions and dangerous situations.<br />
|address=Lyon, France<br />
|booktitle=38th International Symposium on Reliable Distributed Systems (SRDS 2019), Fast Abstract<br />
}}<br />
Extended version available on arXiv: https://arxiv.org/abs/1906.04703</div>Casimhttps://navigators.di.fc.ul.pt/wiki/Publication:Casimiro2019SRDS-FAPublication:Casimiro2019SRDS-FA2019-11-25T23:14:04Z<p>Casim: Created page with "{{Publication |type=inproceedings |document=Document for Publication-Casimiro2019SRDS-FA.pdf |title=Self-stabilizing Manoeuvre Negotiation: the Case of Virtual Traffic Lights |au..."</p>
<hr />
<div>{{Publication<br />
|type=inproceedings<br />
|document=Document for Publication-Casimiro2019SRDS-FA.pdf<br />
|title=Self-stabilizing Manoeuvre Negotiation: the Case of Virtual Traffic Lights<br />
|author=António Casimiro, Emelie Ekenstedt, Elad M. Schiller<br />
|ResearchLine=Timeliness and Adaptation in Dependable Systems (TADS)<br />
|month=sep<br />
|year=2019<br />
|abstract=The vision of automated driving promises to have safer and more cost-efficient transport systems. Automated driving systems have to demonstrate high levels of dependability and affordability. Recent advances of new communication technologies, e.g., 5G, allow significant cost reduction of timely shared sensory information. However, the design of fault-tolerant automated driving systems remains an open challenge. This work considers the design of automated driving systems through the lenses of self-stabilization — a very strong notion of fault-tolerance. Our self-stabilizing algorithms guarantee, within a bounded period, recovery from a broad fault model and arbitrary state corruption. After this recovery period, our algorithms provide safe maneuver execution despite the presence of failures, such as unbounded periods of packet loss and timing failures as well as inaccurate sensory information and malicious behavior. We evaluate the proposed algorithms through a rigorous correctness proof and a worst-case analysis as well as a prototype that focuses on an intersection crossing protocol. We validate our prototype via computer simulations and a testbed implementation. Our preliminary results show a reduction in the number of vehicle collisions and dangerous situations.<br />
|address=Lyon, France<br />
|booktitle=38th International Symposium on Reliable Distributed Systems (SRDS 2019), Fast Abstract<br />
}}</div>Casimhttps://navigators.di.fc.ul.pt/wiki/File:Document_for_Publication-Casimiro2019SRDS-FA.pdfFile:Document for Publication-Casimiro2019SRDS-FA.pdf2019-11-25T23:08:15Z<p>Casim: </p>
<hr />
<div></div>Casimhttps://navigators.di.fc.ul.pt/wiki/Publication:Nascimento2019MScThesisPublication:Nascimento2019MScThesis2019-11-25T23:05:18Z<p>Casim: Created page with "{{Publication |type=mastersthesis |document=Document for Publication-Nascimento2019MScThesis.pdf |title=Evaluation of WSN Technology for Dependable Monitoring in Water Environmen..."</p>
<hr />
<div>{{Publication<br />
|type=mastersthesis<br />
|document=Document for Publication-Nascimento2019MScThesis.pdf<br />
|title=Evaluation of WSN Technology for Dependable Monitoring in Water Environments<br />
|author=Carlos Nascimento, <br />
|Project=Project:AQUAMON, <br />
|ResearchLine=Timeliness and Adaptation in Dependable Systems (TADS)<br />
|month=nov<br />
|year=2019<br />
|abstract=A few problems arise when trying to reliably monitor a surrounding environment by the use of sensors and a wireless network to disseminate the information gathered. In the context of an aquatic environment, the undulation and the low predictability of the surrounding environment could cause faults in the transmission of data.<br />
<br />
AQUAMON is a project that has as objective the deployment of a dependable Wireless Sensor Network (WSN) for the purposes of water quality monitoring and the study of tidal movements. Therefore, AQUAMON, like any other WSN will have to go through the process of choosing a technology that meets its application requirements as well as the requirements imposed by the deployment environment.<br />
<br />
WSNs can have constraints when it comes to the Quality of Service and availability they can provide. These networks generally have a set of requirements that need to be satisfied. Thus, there needs to be a selection of one (or multiple) wireless technologies that can satisfy said requirements. This selection process is usually done in a ad-hoc way, weighting the advantages and disadvantages of different possible solutions with respect to some requirements, often using empirical knowledge or simply dictated by the designer’s preference for some particular technology. When several functional and non-functional requirements have to be addressed, finding an optimal or close to optimal solution may become a hard problem. <br />
<br />
This thesis proposes a methodology for addressing this optimisation problem in an automated way. It considers various application requirements and<br />
the characteristics of the available technologies (including Sigfox, LoRa, NB-IoT, ZigBee and ZigBee Pro) and delivers the solution that better satisfies the requirements. It illustrates how the methodology is applied to a specific use case of WSN-based environmental monitoring in the Seixal Bay.<br />
|school=Faculdade de Ciências, Universidade de Lisboa<br />
|advisor=António Casimiro, Pedro M. Ferreira, <br />
}}</div>Casim