Secure Systems Demo Day 2020 will be held virtually on October 29!
Every year we organize a Demo Day to showcase our current research in information security and to seek valuable inputs from external visitors. The event is intended to bring local academia and industry together and give them an overview of information security research going on in Finland’s capital area.
Demo Day presentations will end with a HAIC talk given by Elissa Redmiles.
14:00-15:00 Virtual company booths for students to search for open job opportunities in local infosec companies
15:00-16:30 Demo day talks
- Opening talk by HAIC director Janne Lindqvist
- Short overview talks about on-going research by group leaders
- Lachlan Gunn, Aalto University: Platform security
- Samuel Marchal, Aalto University/F-Secure: Machine learning and security
- Tuomas Aura, Aalto University: Network security and protocols
- Valtteri Niemi, University of Helsinki: 5G security and applied cryptography
- Stephan Sigg, Aalto University: Usable security @Ambient Intelligence group
- Chris Brzuska, Aalto University: Cryptography [video]
16:30-17:15 Thematic sessions for technical presentations + Q&A sessions
- Lachlan Gunn, Aalto University:
- Hans Liljestrand, University of Waterloo: Towards Deterministic Memory Safety with ARMv8.5-MTE
- Antti Rusanen, Huawei: Color Coating Rust – Protecting the Exposed Parts
Machine learning and security
- Buse Atli, Aalto University:
- Buse Atli, Aalto University and Shelly Wang, University of Waterloo:
- Tommi Gröndahl, Aalto University:
- Sebastian Szyller, Aalto University and Vasisht Duddu, University of Waterloo:
- Sebastian Szyller, Aalto University:
Network security and protocols
- Amel Bourdoucen, Aalto University & Tolgahan Akgun, Huawei: Simple and Secure Control of Consumer IoT Device with a Smartphone
- Aleksi Peltonen, Aalto University: A Comprehensive Formal Analysis of 5G Handover
5G security and applied cryptography
- Gizem Akman, University of Helsinki: Privacy for Users of Multi-Access Edge Computing (MEC) Applications
- Milad Bahadori, University of Helsinki: Acceleration of Functional Encryption for Privacy-Preserving Machine Learning
- Tommi Meskanen, University of Helsinki:Peer discovery for HELIOS platform Demoday_Meskanen
- Sara Ramezanian, University of Helsinki: AI-based Cyberbullying Prevention in 5G Networks
- Nils Beck, Aalto University: Exploiting randomness in heart-rate variability for security applications
- Stephan Sigg, Aalto University: Camouflage learning: distributed machine learning with obscured model and private data
- Si Zuo: CardioID: ECG-BCG agnostic usably secure device pairing
- Chris Brzuska, Aalto University: Q&A after Chris’s overview talk in the main session
17:30-18:30 HAIC Talk: Learning from the People: From Normative to Descriptive Solutions to Problems in Security, Privacy & Machine Learning – with Elissa Redmiles
18:30-20:00 Demo Day Lounge – Virtual Get-together
Description: A variety of experts — computer scientists, policy makers, judges — constantly make decisions about best practices for computational systems. They decide which features are fair to use in a machine learning classifier predicting whether someone will commit a crime, and which security behaviors to recommend and require from end-users. Yet, the best decision is not always clear. Studies have shown that experts often disagree with each other, and, perhaps more importantly, with the people for whom they are making these decisions: the users.
This raises a question: Is it possible to learn best-practices directly from the users? The field of moral philosophy suggests yes, through the process of descriptive decision-making, in which we observe people’s preferences from which to infer best practice rather than using experts’ normative (prescriptive) determinations of best practice. In this talk, I will explore the benefits and challenges of applying such a descriptive approach to making computationally-relevant decisions regarding: (i) optimizing security prompts for an online system; (ii) determining which features are fair to include in a classifier and which decision makers should evaluate fairness; (iii) defining standards for ethical virtual reality content.
About the speaker: Elissa M. Redmiles is a Faculty Member and Research Group Leader of the Digital Harm group at the Max Planck Institute for Software Systems. She additionally serves as a consultant and researcher at multiple institutions, including Microsoft Research and Facebook. Dr. Redmiles uses computational, economic, and social science methods to understand users’ security, privacy, and online safety-related decision-making processes. Much of her work focuses specifically on investigating inequalities that arise in these decision-making processes and mitigating those inequalities through the design of systems that facilitate safety equitably across users. Dr. Redmiles’ work has been featured in popular press publications such as Scientific American, Wired, Business Insider, Newsweek, Schneier on Security, and CNET and has been recognized with multiple Distinguished Paper Awards at USENIX Security as well as the John Karat Usable Privacy and Security Research Award. Dr. Redmiles received her B.S. (Cum Laude), M.S., and Ph.D. in Computer Science from the University of Maryland. As a graduate student, she was supported by a NSF Graduate Research Fellowship, a National Defense Science and Engineering Graduate Fellowship, and a Facebook Fellowship.
The Secure Systems Demo Day is part of Helsinki-Aalto Institute for Cybersecurity (HAIC) public outreach program and jointly organized by the Secure Systems Group at Aalto University and the University of Helsinki.