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Cyber Security Webinar by Roland Kromes MSc - Modeling a low-power IoT architecture for Blockchain and Smart Contract applications

Cyber Security Webinar by Roland Kromes MSc - Modeling a low-power IoT architecture for Blockchain and Smart Contract applications 23 November 2021 12:00 till 12:45 - Location: Zoom meeting Join Zoom Meeting https://tudelft.zoom.us/j/93459336716?pwd=VFk4N3dCQTF2TUlHYnBLejk0dFVPUT09 Meeting ID: 934 5933 6716 Passcode: 389654 Abstract Nowadays, most IoT applications are based on a centralized system in which all of the system participants have to rely on a central entity. In such a system, data immutability, data traceability, and transparency cannot be provided. Blockchain technology is an entirely decentralized system in which the third trusted party (central entity) is removed. Contrarily to centralized systems, blockchain technology provides data immutability, traceability, and transparency. Most modern blockchains also allow the deployment of smart contracts, which are digital programs that can be read by all participants and executed automatically according to an event on the blockchain. These advantageous features of blockchain technology show a clear interest in the integration of IoT with blockchain technology. The contribution's main objectives are the study of the integration possibilities of IoT with blockchain technology and the development of a model of dedicated low-power-consumption IoT hardware architecture that enables communication with multiple types of blockchain. The proposed blockchain APIs (Ethereum, Hyperledger Sawtooth) are written in C++. These APIs can create valid transactions. The IoT architecture model's CPU is emulated with QEMU and the dedicated cryptographic hardware accelerators are modeled in SystemC-TLM high-level hardware description language. As QEMU and SystemC-TLM work on different time environments, they must be synchronized by a co-simulation platform. The CPU of the proposed IoT architecture executes a Linux Operating System, which runs blockchain APIs. These APIs cannot have direct access to the hardware accelerators. In order to handle access to the hardware accelerators and the orchestration of dedicated power management, Linux Kernel device drivers were developed. The results represent that a significant reduction of the overall energy consumption can be achieved when the elliptic curve point multiplication and hash operations are hardware accelerated. Bio I am Roland Kromes, a PhD candidate at the Université Côte d'Azur in the Electronics, Antennas and Telecommunications Laboratory (LEAT-CNRS). In January, I will join the Cybersecurity group at Delft University of Technology as a postdoctoral researcher. I obtained my diploma in Electronics, Systems and Telecommunications with the specialty of embedded systems at the Université Côte d'Azur. My thesis focuses on the possibilities of IoT integration with Blockchain technology and the modeling of a specific low power IoT architecture for Blockchain and Smart Contract applications. This thesis is part of the Smart IoT for Mobility multidisciplinary project (ANR-National Agency for Research) in which I could also work on acceptability issues of Blockchain technology with fellow management researchers. My research interests: Blockchain, IoT, applied cryptography, secure data sharing.

Cyber Security Webinar by Dr. Yunpeng Li - Uncertainty quantification and propagation in high-dimensional spaces

Cyber Security Webinar by Dr. Yunpeng Li - Uncertainty quantification and propagation in high-dimensional spaces 28 September 2021 12:00 till 12:45 - Location: Zoom meeting Join Zoom Meeting https://tudelft.zoom.us/j/99314357068 Meeting ID: 993 1435 7068 Passcode: 678062 Abstract: Deep learning models, which are cornerstones in the success of modern machine learning applications, often lack representation of uncertainty or produce overconfident predictions that can lead to costly consequences. The optimal transport theory has found it application in quantifying uncertainty in large-scale machine learning problems by measuring the Wasserstein distance between data distributions. Separately, for real-world sequential inference applications, differentiable filters provided a mathematically principled framework to propagate model uncertainty. This talk will hence be divided into two parts. In the first part, I will discuss a new family of slice-based Wasserstein distance metrics, called augmented sliced Wasserstein distances (ASWDs), with a novel incorporation of injective neural networks. ASWDs learns nonlinear projections that can capture the complex structure of the data distributions which improve their projection efficiency. In the second part, I will discuss our recent efforts in constructing more expressive dynamic model and proposal distributions in the differentiable particle filtering framework through normalizing flow. In addition, I will introduce an end-to-end learning objective based upon the maximisation of a pseudo-likelihood function which can improve the estimation of states when large portion of groundtruth information are unknown. Bio: Dr Yunpeng Li is Senior Lecturer in Artificial Intelligence in the Department of Computer Science at the University of Surrey in the UK. Before joining Surrey as a Lecturer in AI in 2018, he was a postdoctoral researcher in the Machine Learning Research Group in the Department of Engineering Science at the University of Oxford and was a Junior Research Fellow at Wolfson College at Oxford. He received a PhD in Electrical Engineering at the McGill University in Canada in 2017. His research interests are in the areas of statistical machine learning and signal processing, particularly Bayesian inference techniques and the optimal transport theory. He has broad interests in applications of machine learning, e.g. breast cancer detection, dental disease detection, and environment acoustic sensing. His work has won the best paper award in the NeurlPS Workshop on Machine Learning for Developing World in 2018 and 2019.

Cyber Security Webinar by Martin Fejrskov MSc - Using NetFlow to measure the impact of deploying DNS-based blacklists

Cyber Security Webinar by Martin Fejrskov MSc - Using NetFlow to measure the impact of deploying DNS-based blacklists 12 October 2021 12:00 till 12:45 - Location: Zoom meeting Join Zoom Meeting https://tudelft.zoom.us/j/95465881342 Meeting ID: 954 6588 1342 Passcode: 808322 Abstract To prevent user exposure to a wide range of cyber security threats, organizations and companies often resort to deploying blacklists in DNS resolvers or DNS firewalls. The impact of such a deployment is often measured by comparing the coverage of individual blacklists, by counting the number of blocked DNS requests, or by counting the number of flows redirected to a benign web page that contains a warning to the user. This paper suggests an alternative to this by using NetFlow data to measure the effect of a DNS-based blacklist deployment. Our findings suggest that only 38-40\% of blacklisted flows are web traffic. Furthermore, the paper analyzes the flows blacklisted by IP address, and it is shown that the majority of these are potentially benign, such as flows towards a web server hosting both benign and malicious sites. Finally, the flows blacklisted by domain name are categorized as either spam or malware, and it is shown that less than 6\% are considered malicious. Short bio: Martin Fejrskov is an Industrial Ph.D. student at Telenor Denmark and Aalborg University focusing on detecting cybersecurity threats with data from Internet Service Providers. Prior to the Ph.D. studies, he was a Solution Architect at Telenor Denmark, focusing on security services and the national backbone network. Before that he was a Product Manager at the Danish company formerly known as ETI A/S, heading the development and architecture of one of the core products. He received his Master of Science from Aalborg University in 2005 with excellent grades, studying primarily within the fields of network protocols, traffic analysis and security.

Cyber Security Webinar by Dr. Shihui Fu of the University of Waterloo - Transparent Succinct Zero-Knowledge Arguments for R1CS with Efficient Verifier

Cyber Security Webinar by Dr. Shihui Fu of the University of Waterloo - Transparent Succinct Zero-Knowledge Arguments for R1CS with Efficient Verifier 09 November 2021 12:00 till 12:45 - Location: Zoom meeting Join Zoom Meeting https://tudelft.zoom.us/j/95108026354?pwd=RVhXS3EwQjIyZnVzNk1ScWNzQmtTdz09 Meeting ID: 951 0802 6354 Passcode: 378365 Abstract We propose Polaris, a zkSNARK with quasi-linear prover time and both polylogarithmic proof size and verification time in the size of the arithmetic circuit representing the statement. By instantiating with different commitment schemes, we obtain several zkSNARKs where the verifier's costs and the proof size range from $O(\log^2{N})$ to $O(\sqrt{N})$ depending on the underlying polynomial commitment schemes. All these schemes do not require a trusted setup. It is plausibly post-quantum secure when instantiated with a secure collision-resistant hash function. Our experimental evaluation demonstrates that Polaris offers a much lower verification time than Ligero and Aurora for instances with large sizes as we reduce the complexity from linear to polylogarithmic. Short bio Shihui Fu received his Ph.D. degree in Mathematics from Academy of Mathematics and Systems Science, CAS in 2018. Currently, he is a post-doc in University of Waterloo. His main research interests include cryptographic protocols and zero-knowledge proof.

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How system safety can make Machine Learning systems safer in the public sector

Machine Learning (ML), a form of AI where patterns are discovered in large amounts of data, can be very useful. It is increasingly used, for example, in chatbot Chat GPT, facial recognition, or speech software. However, there are also concerns about the use of ML systems in the public sector. How do you prevent the system from, for example, discriminating or making large-scale mistakes with negative effects on citizens? Scientists at TU Delft, including Jeroen Delfos, investigated how lessons from system safety can contribute to making ML systems safer in the public sector. “Policymakers are busy devising measures to counter the negative effects of ML. Our research shows that they can rely much more on existing concepts and theories that have already proven their value in other sectors,” says Jeroen Delfos. Jeroen Delfos Learning from other sectors In their research, the scientists used concepts from system safety and systems theory to describe the challenges of using ML systems in the public sector. Delfos: “Concepts and tools from the system safety literature are already widely used to support safety in sectors such as aviation, for example by analysing accidents with system safety methods. However, this is not yet common practice in the field of AI and ML. By applying a system-theoretical perspective, we view safety not only as a result of how the technology works, but as the result of a complex set of technical, social, and organisational factors.” The researchers interviewed professionals from the public sector to see which factors are recognized and which are still underexposed. Bias There is room for improvement to make ML systems in the public sector safer. For example, bias in data is still often seen as a technical problem, while the origin of that bias may lie far outside the technical system. Delfos: “Consider, for instance, the registration of crime. In neighbourhoods where the police patrol more frequently, logically, more crime is recorded, which leads to these areas being overrepresented in crime statistics. An ML system trained to discover patterns in these statistics will replicate or even reinforce this bias. However, the problem lies in the method of recording, not in the ML system itself.” Reducing risks According to the researchers, policymakers and civil servants involved in the development of ML systems would do well to incorporate system safety concepts. For example, it is advisable to identify in advance what kinds of accidents one wants to prevent when designing an ML system. Another lesson from system safety, for instance in aviation, is that systems tend to become more risky over time in practice, because safety becomes subordinate to efficiency as long as no accidents occur. “It is therefore important that safety remains a recurring topic in evaluations and that safety requirements are enforced,” says Delfos. Read the research paper .

Three Students Nominated for the ECHO award

Three TU Delft students have been nominated for the ECHO Award 2024. The ECHO award is awarded to students with a non-western background who are actively engaged in society. Sibel, TJ and Pravesha talk about their background their nomination. The finalists will be selected on September 27th. Sibel Gökbekir How has your background influenced your academic journey? As a woman with Turkish roots, my academic journey has been about more than just pursuing degrees in engineering and law; it’s been about consistently advocating for the diverse needs of women and multicultural groups, ensuring their voices are heard in important decisions. This is why I actively contributed to different board positions at TU Delft, working to promote inclusivity and equality. My background inspired me to explore how engineering, law, and social justice intersect, particularly in empowering marginalised communities. I chose to study energy transitions and human rights to contribute to a fairer, more inclusive World. How have you turned this into contributions to society? I’ve dedicated my academic and personal life to promoting diversity and inclusion. As a youth ambassador for Stop Street Harassment, I aimed to create safer spaces for women and minorities because I believe everyone has the right to feel free and safe in society. Through the Turkish Golden Tulip Foundation, I advocated for vulnerable communities in earthquake relief. Additionally, I founded an initiative for migrant students in Rotterdam-South and I have been committed to improving educational opportunities for secondary school students with a migration background. Next, I gave guest lectures across the Netherlands to educate the younger generation about climate change and equitable energy transitions, emphasising the importance of a fair transition for all communities. What does it mean for you to nominated to the ECHO award? I feel very honoured to have been nominated on behalf of TU Delft. My commitment to community engagement is part of who I am, and therefore the ECHO Award is more than just a recognition; It offers me an opportunity to further expand my contributions to a more inclusive society. As an ECHO Ambassador, I plan to expand my efforts in promoting equality and sustainability, while inspiring others to take action for a more equitable World. TJ Rivera How has your background influenced your academic journey? My background as a Filipino in a Dutch-speaking bachelor’s programme made my academic journey both challenging and enriching. Being gay in a male-dominated field like Architecture, where most role models were heteronormative men, added another layer of difficulty. It was intimidating to not see people like me represented. However, this experience fuelled my belief that systems can and should be challenged, changed, and updated. I aimed to bring a fresh perspective, advocating for greater diversity and inclusivity in the field. How have you turned this into contributions to society? I translated my personal challenges into tangible contributions by advocating for inclusivity within architecture. Together with like-minded individuals, I began exploring the intersection of identity, sexuality, and architecture, and collaborated with my faculty’s diversity team to raise awareness. As I became known for my work with the queer community, I saw an opportunity to create lasting change. I co-revived ARGUS, the once-inactive study association for the Master of Architecture, which now serves as a platform to discuss and address issues of diversity within the field. This initiative continues to foster a more inclusive academic environment. What does it mean for you to be nominated to the Echo award? Being nominated for the ECHO Award is a significant milestone in my journey to expand my mission beyond the confines of my faculty. This national platform provides the opportunity to raise awareness and advocate for social justice on a larger scale. I believe students are key to driving change, and my focus is on amplifying the voices of the queer community, which is often overlooked. The ECHO Award will enable me to form partnerships with organizations and universities, further promoting diversity, inclusivity, and equality. It’s a chance to create broader, tangible change, addressing the needs of those who often go unheard. Pravesha Ramsundersingh How has your background influenced your academic journey? As a woman in STEM (Science, Technology, Engineering, and Mathematics), my background has been a powerful motivator to challenge gender disparities within Computer Science. Experiencing firsthand the underrepresentation of women in this field, I have been driven to not only excel academically but also become an advocate for diversity. Through leadership roles in the Faculty and Central Student Councils, I’ve focused on creating an inclusive environment that supports women and minority students, ensuring that everyone has the opportunity to succeed. How have you turned this into contributions to society? I’ve translated my experiences into actionable contributions by actively advocating for DEI at TU Delft. I ensured sexual education and consent training for 3,000 freshmen students, and I led initiatives like the Social Safety Initiatives Conference alongside the Dutch National Coordinator against Racism and Discrimination. In my student governance roles, I pushed for policies that address gender discrimination and social safety concerns, creating a more supportive environment for students of all backgrounds to thrive in both academic and social spaces. What does it mean for you to nominated to the ECHO award? Being nominated for the ECHO Award is an incredible honour that highlights the importance of the work I have done to promote DEI. It inspires me to continue advocating for systemic change in the tech industry and academia. This nomination reaffirms my commitment to driving equity in STEM, ensuring that future generations have more inclusive opportunities. It also motivates me to keep pushing boundaries and empower others to take action for a more just and equal society. The ECHO Award Every year ECHO, Center for Diversity Policy, invites colleges and universities to nominate socially active students who make a difference in the field of Diversity & Inclusion for the ECHO Award 2024. The ECHO Award calls attention to the specific experiences that students with a non-Western background* carry with them and the way they manage to turn these experiences into a constructive contribution to society. Winners are selected by an independent jury and may attend a full-service Summercourse at UCLA in the United States in 2025. Read more: ECHO Award - ECHO (echo-net.nl)