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Reducing Efficiency of Connectivity-Splitting Attack on Newscast via Limited Gossip

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Applications of Evolutionary Computation (EvoApplications 2016)

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Abstract

Newscast is a Peer-to-Peer, nature-inspired gossip-based data exchange protocol used for information dissemination and membership management in large-scale, agent-based distributed systems. The model follows a probabilistic scheme able to keep a self-organised, small-world equilibrium featuring a complex, spatially structured and dynamically changing environment. Newscast gained popularity since the early 2000 s thanks to its inherent resilience to node volatility as the protocol exhibits strong self-healing properties. However, the original design proved to be surprisingly fragile in a byzantine environment subjected to cheating faults. Indeed, a set of recent studies emphasized the hard-wired vulnerabilities of the protocol, leading to an efficient implementation of a malicious client, where a few naive cheaters are able to break the network connectivity in a very short time. Extending these previous works, we propose in this paper a modification of the seminal protocol with embedded counter-measures, improving the resilience of the scheme against malicious acts without significantly affecting the original Newscast’s properties nor its inherent performance. Concrete experiments were performed to support these claims, using a framework implementing all the solutions discussed in this work.

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Acknowledgments

The experiments presented in this paper were carried out using the HPC facility of the University of Luxembourg.

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Correspondence to Sébastien Varrette .

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Muszyński, J., Varrette, S., Bouvry, P. (2016). Reducing Efficiency of Connectivity-Splitting Attack on Newscast via Limited Gossip. In: Squillero, G., Burelli, P. (eds) Applications of Evolutionary Computation. EvoApplications 2016. Lecture Notes in Computer Science(), vol 9597. Springer, Cham. https://doi.org/10.1007/978-3-319-31204-0_20

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  • DOI: https://doi.org/10.1007/978-3-319-31204-0_20

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