This time around, not one but two different papers from the WIDE team have been accepted at the IEEE/IFIP International Conference on Dependable Systems and Networks (DSN 2018). The first one is a wide collaboration between EPFL, various Inria Centers, ENS Rennes, and Mediego, while the second one is a pure product from WIDE.
- Collaborative Filtering Under a Sybil Attack: Similarity Metrics do Matter!
A. Boutet, F. De Moor, D. Frey, R. Guerraoui, A. Kermarrec, A. Rault Abstract: Recommendation systems help users identify content that may be of interest to them. However besides filtering information, they also open new privacy threats. In this paper, we deeply analyze the effect of a Sybil attack that tries to infer information on users from a user-based collaborative-filtering recommendation systems. We discuss the impact of different similarity metrics used to identity users with similar tastes in the trade-off between recommendation quality and privacy. Finally, we propose and evaluate a novel similarity metric that combines the best of both worlds: a high recommendation quality with a low prediction accuracy for the attacker. Our results, on a state-of-the-art recommendation framework and on real datasets show that existing similarity metrics exhibit a wide range of behaviors in the presence of Sybil attacks, while our new similarity metric consistently achieves the best trade-off while outperforming state-of-the-art solutions.
- Pleiades: Distributed Structural Invariants at Scale
Simon Bouget, Yérom David Bromberg, Adrien Luxey, Francois Taiani Abstract: In order to meet rising expectations in terms of scalability, robustness, and flexibility, large scale distributed systems increasingly espouse sophisticated distributed architectures that require enforcing complex distributed structural invariants. Unfortunately, maintaining these structural invariants at scale is particularly time consuming and error prone, as developers must take into account asynchronous failures, loosely coordinated sub-systems and network delays. To address this problem, we propose PLEIADES, a new plat- form to construct and enforce large-scale distributed structural invariants under aggressive conditions. PLEIADES combines the resilience of self-organizing overlays, with the expressiveness of an assembly-based design strategy. The result is a highly survivable framework that is able to dynamically maintain arbitrary complex distributed structures under aggressive crash failures. Our evaluation shows in particular that PLEIADES is able to restore the overall structure of a 25,600 node system in 11 asynchronous rounds after half of the nodes have crashed.
A round of applause for our numerous authors.
