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<h2><strong>Upcoming  presentations</strong></h2>
<h2><strong>Upcoming  presentations</strong></h2>
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<h3><strong>March 2022</strong></h3>
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<h3><strong>March 2021</strong></h3>
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<table border="0.5" cellspacing="0" style="background:#89B085">
<table border="0.5" cellspacing="0" style="background:#89B085">
<tr>
<tr>
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            <td align="center" style="width:100px">10</td>
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            <td style="width:300px">Miracle Aniakor</td>
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            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="It is prevalent that buildings are one of the fastest growing energy-consuming sectors since they account for one-third of the global final energy consumption. Strategies are needed to ameliorate buildings’ energy efficiency to mitigate the impact of this growing demand. The goal of this ongoing work is to develop a context-aware predictive framework to compose and support the automated building energy self-assessment and optimization services. This presentation overviews the proposed framework and details the initial contributions on extending energy-related ontologies for better describing building subsystems and their energy consumption.">CONTEXT-AWARE PREDICTIVE FRAMEWORK FOR BUILDING ENERGY SELF-ASSESSMENT AND OPTIMIZATION</span></td>
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            <td style="width:30px">&nbsp;</td>
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</tr>
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            <td align="center" style="width:100px">10</td>
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            <td style="width:300px">Diogo Duarte</td>
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            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="">TBD</span></td>
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            <td style="width:30px">&nbsp;</td>
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</tr>
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        <tr>
             <td align="center" style="width:100px">24</td>
             <td align="center" style="width:100px">24</td>
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             <td style="width:300px">Ana Fidalgo</td>  
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             <td style="width:300px">Nuno Dionísio</td>  
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             <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="Machine Learning approaches on vulnerability detection have been gaining popularity due to their capability to predict and/or detect an attack in early stages, without the laborous human effort of other techniques. However, there is not a public dataset for web vulnerabilities based on real web applications, which would help the research community to improve their knowledge and algorithms. This talk aims to present the initial work done on such a dataset, and how it will address the common issues, such as integrating the labelling of opensource tools with the labelling of human experts.">Machine Learning approaches for vulnerability detection</span></td>  
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             <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="">TBD</span></td>  
             <td style="width:30px">&nbsp;</td>
             <td style="width:30px">&nbsp;</td>
</tr>
</tr>
</table>
</table>
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<h3><strong>April 2021</strong></h3>
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<h3><strong>April 2022</strong></h3>
<table border="0.5" cellspacing="0" style="background:#89B085">
<table border="0.5" cellspacing="0" style="background:#89B085">
<tr>
<tr>
             <td align="center" style="width:100px">7</td>
             <td align="center" style="width:100px">7</td>
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             <td style="width:300px">Vasco Leitão</td>  
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             <td style="width:300px">Samaneh Shafee</td>
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            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="">TBD</span></td>
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            <td style="width:30px">&nbsp;</td>
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</tr>
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        <tr>
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            <td align="center" style="width:100px">7</td>
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            <td style="width:300px">Diogo Pires</td>  
             <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="">TBD</span></td>  
             <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="">TBD</span></td>  
             <td style="width:30px">&nbsp;</td>
             <td style="width:30px">&nbsp;</td>
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             <td align="center" style="width:100px">21</td>
             <td align="center" style="width:100px">21</td>
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             <td style="width:300px">João Caseirito</td>  
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             <td style="width:300px">Žygimantas Jasiūnas</td>  
             <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="">TBD</span></td>  
             <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="">TBD</span></td>  
             <td style="width:30px">&nbsp;</td>
             <td style="width:30px">&nbsp;</td>
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</table>
</table>
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<h3><strong>May 2021</strong></h3>
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<h3><strong>May 2022</strong></h3>
<table border="0.5" cellspacing="0" style="background:#89B085">
<table border="0.5" cellspacing="0" style="background:#89B085">
<tr>
<tr>
             <td align="center" style="width:100px">5</td>
             <td align="center" style="width:100px">5</td>
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             <td style="width:300px">Paulo Antunes</td>  
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             <td style="width:300px">Allan Espíndola</td>
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            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="">TBD</span></td>
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            <td style="width:30px">&nbsp;</td>
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</tr>
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        <tr>
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            <td align="center" style="width:100px">5</td>
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            <td style="width:300px">Gabriel Freitas</td>  
             <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="">TBD</span></td>  
             <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="">TBD</span></td>  
             <td style="width:30px">&nbsp;</td>
             <td style="width:30px">&nbsp;</td>
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             <td align="center" style="width:100px">19</td>
             <td align="center" style="width:100px">19</td>
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             <td style="width:300px">Frederico Apolónia</td>  
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             <td style="width:300px">Tiago R. N. Carvalho</td>
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            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="">TBD</span></td>
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            <td style="width:30px">&nbsp;</td>
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</tr>
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        <tr>
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            <td align="center" style="width:100px">19</td>
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            <td style="width:300px">Gonçalo Reis</td>  
             <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="">TBD</span></td>  
             <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="">TBD</span></td>  
             <td style="width:30px">&nbsp;</td>
             <td style="width:30px">&nbsp;</td>
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</table>
</table>
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<h3><strong>June 2021</strong></h3>
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<h3><strong>June 2022</strong></h3>
<table border="0.5" cellspacing="0" style="background:#89B085">
<table border="0.5" cellspacing="0" style="background:#89B085">
<tr>
<tr>
             <td align="center" style="width:100px">2</td>
             <td align="center" style="width:100px">2</td>
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             <td style="width:300px">Žygimantas Jasiūnas</td>  
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             <td style="width:300px">Rafael Ramires</td>  
             <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="">TBD</span></td>  
             <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="">TBD</span></td>  
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            <td style="width:30px">&nbsp;</td>
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</tr>
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        <tr>
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            <td align="center" style="width:100px">2</td>
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            <td style="width:300px">Inês Sousa</td>
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            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="Wireless Sensor Networks used in aquatic environments for continuous monitoring are constantly being affected by physical or environmental factors that create anomalies in collected data by the sensors. This presentation explains the use and reformulation of a previously created framework in the context of the AQUAMON project. The objective of this work is to use this framework in the AQUAMON project to help detect and correct data collected from different sensors and implement a dashboard for a more comprehensive view of real-time data.">Integration of various data sources and implementation of a dashboard for the remotemonitorization system</span></td>
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            <td style="width:30px">&nbsp;</td>
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</tr>
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        <tr>
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            <td align="center" style="width:100px">16</td>
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            <td style="width:300px">Pedro Rosa</td>
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            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="">Lightweight Cryptography for Internet of Things (IoT) Devices</span></td>
             <td style="width:30px">&nbsp;</td>
             <td style="width:30px">&nbsp;</td>
</tr>
</tr>
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             <td align="center" style="width:100px">16</td>
             <td align="center" style="width:100px">16</td>
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             <td style="width:300px">Vasco Ferreira</td>  
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             <td style="width:300px">Jorge Martins</td>  
             <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="">TBD</span></td>  
             <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="">TBD</span></td>  
             <td style="width:30px">&nbsp;</td>
             <td style="width:30px">&nbsp;</td>
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             <td align="center" style="width:100px">30</td>
             <td align="center" style="width:100px">30</td>
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             <td style="width:300px">João Inácio</td>  
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             <td style="width:300px">Pedro Alves</td>
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            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="">TBD</span></td>
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            <td style="width:30px">&nbsp;</td>
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</tr>
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        <tr>
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            <td align="center" style="width:100px">30</td>
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            <td style="width:300px">Lívio Rodrigues</td>  
             <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="">TBD</span></td>  
             <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="">TBD</span></td>  
             <td style="width:30px">&nbsp;</td>
             <td style="width:30px">&nbsp;</td>
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</table>
</table>
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<h3><strong>July 2021</strong></h3>
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<h3><strong>July 2022</strong></h3>
<table border="0.5" cellspacing="0" style="background:#89B085">
<table border="0.5" cellspacing="0" style="background:#89B085">
<tr>
<tr>
             <td align="center" style="width:100px">14</td>
             <td align="center" style="width:100px">14</td>
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             <td style="width:300px">André Gil</td>  
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             <td style="width:300px">Miguel Oliveira</td>  
             <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="">TBD</span></td>  
             <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="">TBD</span></td>  
             <td style="width:30px">&nbsp;</td>
             <td style="width:30px">&nbsp;</td>
</tr>
</tr>
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        <tr>
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</table>
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            <td align="center" style="width:100px">28</td>
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            <td style="width:300px">João Valente</td>
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            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="">TBD</span></td>
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            <td style="width:30px">&nbsp;</td>
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</tr>
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</table>
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</div>
</div>
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</table>
</table>
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<h3><strong>March 2021</strong></h3>
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<table border="0.5" cellspacing="0" style="background:#89B085">
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<tr>
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            <td align="center" style="width:100px">24</td>
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            <td style="width:300px">Ana Fidalgo</td>
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            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="Machine Learning approaches on vulnerability detection have been gaining popularity due to their capability to predict and/or detect an attack in early stages, without the laborous human effort of other techniques. However, there is not a public dataset for web vulnerabilities based on real web applications, which would help the research community to improve their knowledge and algorithms. This talk aims to present the initial work done on such a dataset, and how it will address the common issues, such as integrating the labelling of opensource tools with the labelling of human experts.">Machine Learning approaches for vulnerability detection</span></td>
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            <td style="width:30px">&nbsp;</td>
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</tr>
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</table>
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<h3><strong>April 2021</strong></h3>
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<table border="0.5" cellspacing="0" style="background:#89B085">
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<tr>
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            <td align="center" style="width:100px">7</td>
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            <td style="width:300px">Vasco Leitão</td>
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            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="Industrial products integrate highly configurable safety-critical systems which must be intensively tested before being delivered to customers. This process is highly time-consuming and may require associations between product features and requirements demanded by customers. Machine Learning (ML) has proven to help engineers in this task, through automation of associations between features and requirements, where the latter are prioritized first.
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 +
However, ML application can be more difficult when requirements are written in natural language (NL), and if it does not exist a ground truth dataset with them. This work presents SRXCRM, a Natural Language Processing-based model able to extract and associate components from product design specifications and customer requirements, written in NL, of safety-critical systems. The model has a Weight Association Rule Mining framework that defines associations between components, generating visualizations that can help engineers in prioritization of the most impactful features. Preliminary results of the use of SRXCRM show that it can extract such associations and visualizations.">Discovering Association Rules Between Software System Requirements and Product Specifications</span></td>
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            <td style="width:30px">&nbsp;</td>
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</tr>
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        <tr>
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            <td align="center" style="width:100px">21</td>
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            <td style="width:300px">João Caseirito</td>
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            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="Fuzzing is a software testing technique to find vulnerabilities by providing invalid and unexpected inputs to a target and monitoring exceptions such as crashes, memory leaks or information disclosure.
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This talk aims to present an ensemble fuzzing approach that checks the correctness of web applications by combining multiple web application fuzzers, improving the coverage and precision in detecting the vulnerabilities and performing better than the fuzzers individually.">Improving Web Application Vulnerability Detection Leveraging Ensemble Fuzzing</span></td>
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            <td style="width:30px">&nbsp;</td>
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</tr>
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</table>
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<h3><strong>May 2021</strong></h3>
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<table border="0.5" cellspacing="0" style="background:#89B085">
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<tr>
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            <td align="center" style="width:100px">5</td>
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            <td style="width:300px">Paulo Antunes</td>
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            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="Web applications play a pivotal role in modern society. They have become a prime target for attackers, who exploit a variety of vulnerabilities to access private data and corrupt systems. This work aims to develop novel approaches to detect and remove vulnerabilities in PHP programs. Instead of processing PHP code directly and analyzing the full application at once, we leverage an intermediate language representation of the code and use a guided analysis to find bugs with increased precision. The guided analysis will avoid common approximations of traditional static analysis, resulting in a more accurate emulation of program states.">Web Vulnerability Discovery at an Intermediate Language Level</span></td>
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            <td style="width:30px">&nbsp;</td>
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</tr>
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        <tr>
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            <td align="center" style="width:100px">19</td>
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            <td style="width:300px">Frederico Apolónia</td>
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            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="The levels of energy consumption in the European Union continues to grow above the expected values and buildings are one of the largest consumers, in front of the sectors of industry and transportation. Since buildings can be used for different goals with different requirements, in order to do an appropriate control, it is necessary to design and develop approaches for real-time assessment. In this talk we will present the concept of indoor location using Bluetooth and WiFi scanners to monitor surrounding devices. This information will be used to determine the number of different users inside a building/space, which is later used by control systems in order to improve the efficiency of buildings, keeping certain levels of comfort for the users.">Building Occupancy Assessment</span></td>
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            <td style="width:30px">&nbsp;</td>
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</tr>
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</table>
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<h3><strong>June 2021</strong></h3>
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<table border="0.5" cellspacing="0" style="background:#89B085">
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<tr>
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            <td align="center" style="width:100px">2</td>
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            <td style="width:300px">Bernardo Portela</td>
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            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="Conflict-free Replicated Data Types (CRDTs) are abstract data types that support developers when designing and reasoning about distributed systems with eventual consistency guarantees. In their core they solve the problem of how to deal with concurrent operations, in a way that is transparent for developers. However in the real world, distributed systems also suffer from other relevant problems, including security and privacy issues and especially when participants can be untrusted. In this paper we present the first formal cryptographic treatment of CRDTs, as well as proposals for secure implementations. We start by presenting a security notion that is compatible with standard definitions in cryptography. We then describe new privacy-preserving CRDT protocols that can be used to help secure distributed cloud-backed applications, including NoSQL geo-replicated databases. Our proposals are based on standard CRDTs, such as sets and counters, augmented with cryptographic mechanisms that allow operations to be performed on encrypted data. Our proposals are accompanied with formal security proofs and implement and integrate them in AntidoteDB, a geo-replicated NoSQL database that leverages CRDTs for its operations. Experimental evaluations based on the Danish Shared Medication Record dataset (FMK) exhibit the tradeoffs that our different proposals make and show that they are ready to be used in practical applications.">Secure Conflict-free Replicated Data Types</span></td>
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            <td style="width:30px">&nbsp;</td>
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</tr>
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        <tr>
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            <td align="center" style="width:100px">16</td>
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            <td style="width:300px">Žygimantas Jasiūnas and Vasco Ferreira</td>
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            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="Nowadays there is a focus on energy efficiency and flexible energy where IoT devices can introduce some advantages due to their monitoring and remote control capabilities. There are multiple IoT platforms and systems developed allowing the integration of multiple devices offering monitoring and remote control capabilities and even the usage of triggers, where if something is reached then some action will be performed. However, a simple integration of IoT devices in current solutions is not enough to achieve the levels of desired efficiency, for that, new solutions that integrates legacy appliances with new ones are needed. In order to achieve this goal the SATO (Self Assessment Towards Optimization) platform was designed. The SATO platform aims to integrate existing IoT energy focused platforms (e.g., EDP re:dy and Siemens Navigator) with existing IoT smart systems, such as Google Nest. Supported by Machine Learning algorithms and IoT capabilities, the SATO platform wants to be an autonomous management system for buildings where energy efficiency is a priority. However, the integration of different parts of building management systems is a common issue due to the existence of diverse appliances, devices and technologies that must be integrated. The most common solution to solve this problem is based on middleware solutions, which allows to hide platform specification. In this thesis we will design, implement and test a middleware component that abstracts the specification of different components and exposes generic APIs to deal with a large number of appliances. Supported by the proposed set of API, the services available can easily be used without the complexity of knowing each of the underlying details.">Monitoring and Integration of heterogeneous building IoT platforms and smart systems</span></td>
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            <td style="width:30px">&nbsp;</td>
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</tr>
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        <tr>
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            <td align="center" style="width:100px">30</td>
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            <td style="width:300px">João Inácio</td>
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            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="Currently, embedded systems are present in a myriad of devices, such as IoT, drones, cyberphysical systems. The security these devices can be critical, depending the context they are integrated and the role they play (e.g., water plant, car). C is the main language used to develop the software for these devices and is known for missing the bounds of its data types, which lead to vulnerabilities, like buffer and integer overflows. These flaws when exploited cause severe damage and can put human life in dangerous. Therefore, it is important the software of these devices be secure.
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One of the utmost importance with C programs is how to fix its code automatically, employing the right secure code that can remove the existent vulnerabilities and avoid attacks. However, such task faces some challenges. For example, how to remove vulnerabilities, what is the right secure code needed to remove them, and where to insert this code. Another challenge is how to maintain the correct behavior of the application, after applying the code correction.">Automatic Removal of Flaws in Embedded System Software</span></td>
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            <td style="width:30px">&nbsp;</td>
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</tr>
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</table>
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<h3><strong>July 2021</strong></h3>
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<table border="0.5" cellspacing="0" style="background:#89B085">
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<tr>
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            <td align="center" style="width:100px">14</td>
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            <td style="width:300px">André Gil</td>
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            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="Tools used to assess energy utilization in buildings are inadequate. Real-life energy consumption often exceeds design expectations. The SATO platform aims to reduce this gap by allowing efficient management of buildings energy resources.
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In this talk we will describe our approach in creating an event-driven system in the context of the world of IoT, we will also describe the way to deploy and manage these complex systems, while also going into detail in some of their components.">Platform Architecture and data management for cloud-based buildings energy self-assessment and optimization</span></td>
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            <td style="width:30px">&nbsp;</td>
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</tr>
 +
        <tr>
 +
            <td align="center" style="width:100px">28</td>
 +
            <td style="width:300px">João Valente</td>
 +
            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="In the domain of IoT(Internet of Things), there is a correlation between the efficiency and effectiveness of a platform, and the quality of the data available for processing and decision making. When a scenario of data collection from different types of sensors, integrated into several devices that are distributed alongside the building, is presented. And, considering that data is essential to monitor and control the level of actuation in the building, the process becomes a matter of extreme importance.
 +
Because of it, there is the intention of developing a platform, capable of evaluating data quality that are collected from the devices of the building, and to prevent a situation where, low quality data puts at risk the proper functioning of the component responsible for the monitoring and control, in a way, that suppresses the effects of low quality data and error propagation.
 +
For that to happen, methods and techniques which target themes like data quality, fault detection and fault mitigation, will be presented, developed, evaluated and implemented.">Data quality and dependability of IoT platform for buildings energy assessment</span></td>
 +
            <td style="width:30px">&nbsp;</td>
 +
</tr>
 +
</table>
 +
 +
<h3><strong>November 2021</strong></h3>
 +
<table border="0.5" cellspacing="0" style="background:#89B085">
 +
<tr>
 +
            <td align="center" style="width:100px">26</td>
 +
            <td style="width:300px">Maria Fidalgo</td>
 +
            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="Although the putative advantages of meritocracy have already been refuted by several scientific studies, it is still largely adopted by many individuals and organisations, especially in industrialised countries. In fact, it has been shown that decisions based solely on merit may lead to gender discrimination. In the fourth chapter of her book Invisible Women: Exposing data bias in a world designed for men, Perez reviews the research related to the myth of meritocracy for women at work, with a focus on STEM companies and academia. For this presentation, Maria will present the main findings of the chapter, finishing with some solutions on how to render the workplace less designed only for men.">The Meritocracy Myth: A Gender Perspective</span></td>
 +
            <td style="width:30px">&nbsp;</td>
 +
</tr>
 +
</table>
 +
 +
<h3><strong>December 2021</strong></h3>
 +
<table border="0.5" cellspacing="0" style="background:#89B085">
 +
<tr>
 +
            <td align="center" style="width:100px">16</td>
 +
            <td style="width:300px">Paulo Antunes</td>
 +
            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="Web applications play a pivotal role in modern society. They have become a prime target for attackers, who exploit a variety of vulnerabilities to access private data and corrupt systems. This work aims to develop novel approaches to detect and remove vulnerabilities in PHP programs. Instead of processing PHP code directly and analyzing the full application at once, we leverage an intermediate language representation of the code and use a guided analysis to find bugs with increased precision. The guided analysis will avoid common approximations of traditional static analysis, resulting in a more accurate representation of program states.">Web Vulnerability Discovery at an Intermediate Language Level</span></td>
 +
            <td style="width:30px">&nbsp;</td>
 +
</tr>
 +
</table>
 +
 +
<h3><strong>January 2022</strong></h3>
 +
<table border="0.5" cellspacing="0" style="background:#89B085">
 +
<tr>
 +
            <td align="center" style="width:100px">13</td>
 +
            <td style="width:300px">Rohit Kumar</td>
 +
            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="The complex engineering research field of cyber-physical systems (CPS) is based on integrating computation, communication, and physical processes, providing design, modelling, and analysis techniques as a whole. In this talk, we will present an architectural model of CPS and discuss the requirements and challenges to make CPS safe.">Architectural support and mechanisms for resilient and safe control in Cyber-Physical System</span></td>
 +
            <td style="width:30px">&nbsp;</td>
 +
</tr>
 +
        <tr>
 +
            <td align="center" style="width:100px">13</td>
 +
            <td style="width:300px">Daniel Ângelo</td>
 +
            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="Tor is one of the most popular anonymity networks in the world. Users of this platform range from dissidents to cybercriminals or even ordinary citizens concerned with their privacy. It is based on advanced security mechanisms to provide strong guarantees against traffic correlation attacks that can deanonymize its users and services.
 +
Torpedo is the first known traffic correlation attack on Tor that aims at deanonymizing OS sessions. In a federated way, servers belonging to ISPs around the globe can process deanonymization queries of specific IPs. With the abstraction of an interface, these queries can be submitted by an attacker to deanonymize OSes and clients.
 +
Initial results show that this attack is able to identify the IP addresses of OS sessions with high confidence (no false positives). However, the current version of Torpedo relies on a central authority to manage the system, which requires ISPs to share sensitive network traffic of their
 +
clients with a third party.
 +
Thus, this work seeks to complement the previously developed research with the introduction and study of multi-party computation (MPC) techniques, with the objective of developing and assessing a new attack vector on Tor that can work even if ISPs encrypt their network traffic before correlation. In more detail, we intend to leverage, test and assess some existing general-purpose and machine learning oriented MPC frameworks and build a privacy- preserving solution on top of Torpedo that satisfies its scalability and performance requirements.">Privacy-preserving Deanonymization of Dark Web Tor Onion Services for Criminal Investigations</span></td>
 +
            <td style="width:30px">&nbsp;</td>
 +
</tr>
 +
        <tr>
 +
            <td align="center" style="width:100px">27</td>
 +
            <td style="width:300px">Robin Vassantlal</td>
 +
            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="Byzantine Fault-Tolerant (BFT) State Machine Replication (SMR) is a classical paradigm for implementing trustworthy services that has received renewed interest with the emergence of blockchains and decentralized infrastructures. A fundamental limitation of BFT SMR is that it provides integrity and availability despite a fraction of the replicas being controlled by an active adversary, but does not offer any confidentiality protection. Previous works addressed this issue by integrating secret sharing with the consensus-based framework of BFT SMR, but without providing all features required by practical systems, which include replica recovery, group reconfiguration, and acceptable performance when dealing with a large number of secrets. We present COBRA, a new protocol stack for Dynamic Proactive Secret Sharing that allows implementing confidentiality in practical BFT SMR systems. COBRA exhibits the best asymptotic communication complexity and optimal storage overhead, being able to renew 100k shares in a group of ten replicas 5 times faster than the current state of the art.">COBRA: Dynamic Proactive Secret Sharing for Confidential BFT Services</span></td>
 +
            <td style="width:30px">&nbsp;</td>
 +
</tr>
 +
        <tr>
 +
            <td align="center" style="width:100px">27</td>
 +
            <td style="width:300px">João Loureiro</td>
 +
            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="Connected and autonomous vehicles aim to improve passenger safety and driving quality of experience. However, current self-driving solutions still constitute an entry barrier to many potential users due to their cost and the offloading of the self-driving algorithms to reduce the onboard computing requirements. At the same time, a viable alternative requires a stable connection to the cloud. This work explores deep learning concepts to forecast mobile network KPIs. These models may ultimately be used to adjust the vehicle's operational parameters to improve network signal quality and ensure a reliable connection to the cloud servers.">Deep learning for communication optimization on autonomous vehicles</span></td>
 +
            <td style="width:30px">&nbsp;</td>
 +
</tr>
 +
</table>
 +
 +
<h3><strong>February 2022</strong></h3>
 +
<table border="0.5" cellspacing="0" style="background:#89B085">
 +
<tr>
 +
            <td align="center" style="width:100px">10</td>
 +
            <td style="width:300px">Carlos Mão de Ferro</td>
 +
            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="In this talk, I will present the complete toolchain for programming CPS as proposed in my PhD. In particular, I will discuss how Shelley, our domain-specific model checker, uses a verification algorithm that checks the integration of stateful systems and other safety properties (e.g., absence of deadlocks). This tool is able to verify systems with billions of systems in a few seconds on a personal computer. In an alternative scenario, I will also hint on how it might be possible to adapt an existing programming language (e.g., Python) to verify the same set of properties.">Safe and Modular Integration of Cyber-Physical Systems</span></td>
 +
            <td style="width:30px">&nbsp;</td>
 +
</tr>
 +
        <tr>
 +
            <td align="center" style="width:100px">10</td>
 +
            <td style="width:300px">David Silva</td>
 +
            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="As the Internet of Things is growing considerably, there is a need for high scalability and standardization of the platform on which projects focused on remote controlling, monitoring and actuation of devices will be based.
 +
The application context of IoT projects can vary from each other. However, key factors like scalability, availability, security, reusability and maintainability will always be concerned. This project aims to develop a platform to satisfy all the key factors that are more common in IoT projects by taking advantage of existing solutions like cloud computing services that privilege the aforementioned factors without neglecting other important aspects such as security.
 +
To complement the mentioned platform, a mobile application will be created to control, monitor, and actuate devices connected to a swimming pool, proving the efficiency and quality of the scalable solution by fitting the exact description of a project to which this platform will be suitable.">Developing a scalable IoT solution for remote monitoring and control</span></td>
 +
            <td style="width:30px">&nbsp;</td>
 +
</tr>
 +
        <tr>
 +
            <td align="center" style="width:100px">24</td>
 +
            <td style="width:300px">Adriano Mão de Ferro</td>
 +
            <td style="width:600px"><span style="border-bottom: dashed 1px #000" title="Every day more people live in cities. The quality of life in cities depends heavily on urban planning and the introduction and maintenance of urban green spaces (UGSs). The images of the earth's surface obtained by remote sensing through artificial satellites make it possible to identify the land cover through the electromagnetic spectrum, which represents a complex and time-consuming task due to the diversity of its characteristics (Trees and shrubs and their size, the type of foliage, lakes and respective banks), as well as their temporal variability, depending on the seasons. The use of Machine Learning(ML) algorithms to classify objects through satellite images, such as Support Vector Machine(SVM), Decision Tree(DT), Neural Network (NN), has been widespread in the analysis. of land cover and can therefore be used to classify UGSs.">Machine learning to predict ecological features in satellite Earth observation data</span></td>
 +
            <td style="width:30px">&nbsp;</td>
 +
</tr>
 +
</table>
 +
 +
 +
 +
 +
</div>
</div>
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 +
 +
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Latest revision as of 20:37, 7 March 2022

The NavTalks is a series of informal talks given by Navigators members or some special guests about every two-weeks at Ciências, ULisboa.

Leave mouse over title's presentation to read the abstract.



Contents

Upcoming presentations

March 2022

10 Miracle Aniakor CONTEXT-AWARE PREDICTIVE FRAMEWORK FOR BUILDING ENERGY SELF-ASSESSMENT AND OPTIMIZATION  
10 Diogo Duarte TBD  
24 Nuno Dionísio TBD  

April 2022

7 Samaneh Shafee TBD  
7 Diogo Pires TBD  
21 Žygimantas Jasiūnas TBD  

May 2022

5 Allan Espíndola TBD  
5 Gabriel Freitas TBD  
19 Tiago R. N. Carvalho TBD  
19 Gonçalo Reis TBD  

June 2022

2 Rafael Ramires TBD  
2 Inês Sousa Integration of various data sources and implementation of a dashboard for the remotemonitorization system  
16 Pedro Rosa Lightweight Cryptography for Internet of Things (IoT) Devices  
16 Jorge Martins TBD  
30 Pedro Alves TBD  
30 Lívio Rodrigues TBD  

July 2022

14 Miguel Oliveira TBD  



Past presentations

September 2018

20 Alysson Bessani SMaRtChain: A Principled Design for a New Generation of Blockchains  
20 Rui Miguel Named Data Networking with Programmable Switches  

October 2018

4 Bruno Vavala (Research Scientist in Intel Labs) Private Data Objects  
4 Marcus Völp (Research Scientist, CritiX, SnT, Univ. of Luxembourg) Reflective Consensus  
18 Yair Amir (Professor, Johns Hopkins University) Timely, Reliable, and Cost-Effective Internet Transport Service using Structured Overlay Networks  

November 2018

13 Salvatore Signorello The Past, the Present and some Future of Interest Flooding Attacks in Named-Data Networking  
13 Tiago Oliveira Vawlt - Privacy-Centered Cloud Storage  
27 Nuno Neves Segurança de Software - Como Encontrar uma Agulha num Palheiro?  
27 Ricardo Mendes Vawlt - The Zero-knowledge End-to-end Encryption Protocol  

December 2018

11/12 António Casimiro AQUAMON: Dependable Monitoring with Wireless Sensor Networks in Water Environments  
11/12 Carlos Nascimento Review of wireless technology for AQUAMON: Lora, sigfox, nb-iot  

January 2019

15/01 Fernando Alves A comparison between vulnerability publishing in OSINT and Vulnerability Databases  
15/01 Ibéria Medeiros SEAL: SEcurity progrAmming of web appLications  
29/01 Fernando Ramos Networks that drive themselves…of the cliff  
29/01 Miguel Garcia Some tips before rushing into LaTeX (adapted from: How (and How Not) to Write a Good Systems Paper)  

February 2019

19/02 Ana Fidalgo Conditional Random Fields and Vulnerability Detection in Web Applications  
19/02 João Sousa Towards BFT-SMaRt v2: Blockchains and Flow Control  

March 2019

13/03 Fernando Ramos How to give a great -- OK, at least a good -- research talk  
13/03 Ricardo Morgado Automatically correcting PHP web applications  

March 2019

27/03 Nuno Dionísio Cyberthreat Detection from Twitter using Deep Neural Networks  
27/03 Fernando Ramos My network protocol is better than yours!  

April 2019

10/04 Adriano Serckumecka SIEMs  
10/04 Tulio Ribeiro BFT Consensus & PoW Consensus (blockchain).  

May 2019

08/05 Miguel Garcia Diverse Intrusion-tolerant Systems  
29/05 Pedro Ferreira The concept of the next navigators cybersecurity H2020 project  
29/05 Vinicius Cogo Auditable Register Emulations  

June 2019

05/06 Diogo Gonçalves Network coding switch  
05/06 Francisco Araújo Generating Software Tests To Check For Flaws and Functionalities  
26/06 Joao Pinto Implementation of a Protocol for Safe Cooperation Between Autonomous Vehicles  
26/06 Tiago Correia Design and Implementation of a Cloud-based Membership System for Vehicular Cooperation  
26/06 Robin Vassantlal Confidential BFT State Machine Replication  

March 2021

24 Ana Fidalgo Machine Learning approaches for vulnerability detection  

April 2021

7 Vasco Leitão Discovering Association Rules Between Software System Requirements and Product Specifications  
21 João Caseirito Improving Web Application Vulnerability Detection Leveraging Ensemble Fuzzing  

May 2021

5 Paulo Antunes Web Vulnerability Discovery at an Intermediate Language Level  
19 Frederico Apolónia Building Occupancy Assessment  

June 2021

2 Bernardo Portela Secure Conflict-free Replicated Data Types  
16 Žygimantas Jasiūnas and Vasco Ferreira Monitoring and Integration of heterogeneous building IoT platforms and smart systems  
30 João Inácio Automatic Removal of Flaws in Embedded System Software  

July 2021

14 André Gil Platform Architecture and data management for cloud-based buildings energy self-assessment and optimization  
28 João Valente Data quality and dependability of IoT platform for buildings energy assessment  

November 2021

26 Maria Fidalgo The Meritocracy Myth: A Gender Perspective  

December 2021

16 Paulo Antunes Web Vulnerability Discovery at an Intermediate Language Level  

January 2022

13 Rohit Kumar Architectural support and mechanisms for resilient and safe control in Cyber-Physical System  
13 Daniel Ângelo Privacy-preserving Deanonymization of Dark Web Tor Onion Services for Criminal Investigations  
27 Robin Vassantlal COBRA: Dynamic Proactive Secret Sharing for Confidential BFT Services  
27 João Loureiro Deep learning for communication optimization on autonomous vehicles  

February 2022

10 Carlos Mão de Ferro Safe and Modular Integration of Cyber-Physical Systems  
10 David Silva Developing a scalable IoT solution for remote monitoring and control  
24 Adriano Mão de Ferro Machine learning to predict ecological features in satellite Earth observation data  










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