Titre de la présentation: Towards User-centric Privacy-preserving Techniques for Cloud-assisted IoT Applications
Le mardi 9 juin 2020 à 14h00
Par Webconf sur le lien https://webconf.imt.fr/frontend/mar-7hd-7hk
Biography :
Nesrine Kaaniche is a Lecturer in Cybersecurity at the Department of Computer Science, the University of Sheffield, UK , co-affiliated with the Security of Advanced Systems Research. Group. Dr. Kaaniche is an associate active member of the interdisciplinary chair Values and Policies of Personal Information of Institute Mines Télécom, France. Previously, she was a Post-Doc researcher at Télécom SudParis, Institut Polytechnique de Paris, France and an International Fellow at SRI International, San Francisco, CA, USA. She received a PhD degree with honours on cloud data storage security jointly from Sorbonne University and Télécom SudParis, Institut Mines Télécom, France, in 2014, and got a thesis award from SAMOVAR, France in 2015. Her major research interests include privacy enhancing technologies and applied cryptography for distributed systems and decentralised architectures, i.e., IoT, fog and clouds. Dr. Kaaniche has published several papers in highly ranked journals and conferences in within the cyber security and applied cryptography field. She has also established research collaborations with many industrial partners and international research centers, namely the University of Auckland, NZ, the University of San Francisco, CA, US and IBM Research, US.
Abstract of presentation:
The Information Revolution has helped advance society in unprecedented ways. Vast, easily accessible content has broadened our outlook on the world. Social networks have let us create and foster personal relationships, and advances in artificial intelligence are enabling tremendous progress for many complex tasks.
At the same time, however, these advances have also dramatically increased the amount of collected, stored and processed personal data, in a decentralized fashion and within different contexts, leading to undesirable consequences, from unsolicited advertisement, discrimination and stalking, to surveillance capitalism that has commodified our personal information, and state-level actors that have tapped into electronic systems to interfere in elections and erode their citizens’ online privacy.
This has prompted a variety of challenging research problems around understanding,
modelling, and countering privacy and cyber-security issues online.
In this talk, I will present new advances on user-centric privacy-preserving mechanisms for Cloud-assisted applications, based on the usage of cryptographic primitives.
First, I will introduce a privacy-preserving cooperative computation scheme for personalized applications, empowering end-users to control the disclosed personal data to third parties, while leveraging the trade-off between privacy and utility.
Second, I will detail user-oriented privacy-preserving authenticated access control schemes, ensuring multi-level and selective access to outsourced data in highly dynamic environments, based on attribute-based cryptographic techniques. Then, I will discuss supported extensions, including outsourced-decryption, revocation as well as access policies’ update features; and point out some real-world applications of the proposed schemes, namely for smart homes and opportunistic networks.
By the end, I will highlight some of the inter-disciplinary privacy challenges that may slow down the adoption of privacy-preserving techniques, namely: technical, social, legal and economic concerns; and provide some research directions.