We are an information security research group at the Department of Computer Science at Aalto University, Espoo, Finland.
The goal of the Secure Systems research group is to create new technologies and design and analysis methods for the development of secure computing and communication systems. The new technologies should be, at the same time, secure, easy to use, and inexpensive to deploy. As is typical for security research, our results also include the discovery of novel attacks and previously unknown classes of vulnerabilities in existing systems. Security against malicious attacks is a basic requirement for all network-connected services and products, and scientific research can provide both fundamental understanding of the security issues and practical solutions that enable product development.
News
- June 26: Our new blog post gives historical insight into the development of mobile trusted execution environments (TEEs) in Nokia smartphones 15+ years ago.
- June 19: Mika Juuti will present his PRADA: Protecting Against DNN Model Stealing Attacks paper today at the 4th IEEE European Symposium on Security and Privacy, Stockholm, Sweden.
- June 13: In our new blog post we show several ways that pointer authentication can be used to improve security, and prevent attackers from turning programmer errors into remote-code-execution vulnerabilities.
- June 6: Hans Liljestrand presented his PACStack (https://PACStack.github.io) poster and Thomas Nyman his HardScope (https://arxiv.org/abs/1705.10295 ) paper at DAC 2019.
- May 24: Already 100+ registrations from Aalto, University of Helsinki and local infosec companies to our annual Demo Day 2019! Registration is still open, please register if you yet haven’t.
- May 9: AuDI: Towards Autonomous IoT Device-Type Identification using Periodic Communication by Samuel Marchal, Markus Miettinen, Thien Duc Nguyen, Ahmad-Reza Sadeghi and N. Asokan, is published in IEEE JSAC Special Issue on Artificial Intelligence and Machine Learning for Networking and Communications, 2019.
- May 3: DIoT: A Federated Self-learning Anomaly Detection System for IoT by Thien Duc Nguyen, Samuel Marchal, Markus Miettinen, Hossein Fereidooni, N. Asokan, and Ahmad-Reza Sadeghi, has been accepted to appear in the 39th IEEE International Conference on Distributed Computing Systems (ICDCS 2019), 2019. arXiv preprint arXiv:1804.07474
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