Section: New Results

Security, Safety and Verification

Participants : Nathalie Mitton, Allan Blanchard, Simon Duquennoy.

Current practices of fault-tolerant network design ignore the fact that most network infrastructure faults are localized or spatially correlated (i.e., confined to geo-graphic regions). Network operators require new tools to mitigate the impact of such region-based faults on their infrastructures. Utilizing the support from the U.S. Department of Defense, and by consolidating a wide range of theories and solutions developed in the last few years, [12] designs RAPTOR, an advanced Network Planning and Management Tool that facilitates the design and provisioning of robust and resilient networks.The tool provides multi-faceted network design, evaluation, and simulation capabilities for network planners. Future extensions of the tool currently being worked upon not only expand the tool’s capabilities, but also extend these capabilities to heterogeneous interdependent networks such as communication, power, water, and satellite networks.

IoT applications often utilize the cloud to store and provide ubiquitous access to collected data. This naturally facilitates data sharing with third-party services and other users, but bears privacy risks, due to data breaches or unauthorized trades with user data. To address these concerns, we present Pilatus, a data protection platform where the cloud stores only encrypted data, yet is still able to process certain queries (e.g., range, sum). More importantly, Pilatus features a novel encrypted data sharing scheme based on re-encryption, with revocation capabilities and in situ key-update. The solution proposed in [37], [56] includes a suite of novel techniques that enable efficient partially homomorphic encryption, decryption, and sharing. We present performance optimizations that render these cryptographic tools practical for mobile platforms. We implement a prototype of Pilatus and evaluate it thoroughly. Our optimizations achieve a performance gain within one order of magnitude compared to state-of-the-art realizations; mobile devices can decrypt hundreds of data points in a few hundred milliseconds. Moreover, we discuss practical considerations through two example mobile applications (Fitbit and Ava) that run Pilatus on real-world data.