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SIEVE: a distributed, accurate, and robust technique to identify malicious nodes in data dissemination on MANET

Abstract : In this paper we consider the following problem: nodes in a MANET must disseminate data chunks using rateless codes but some nodes are assumed to be malicious, i.e., before transmitting a coded packet they may modify its payload. Nodes receiving corrupted coded packets are prevented from correctly decoding the original chunk. We propose SIEVE, a fully distributed technique to identify malicious nodes. SIEVE is based on special messages called checks that nodes periodically transmit. A check contains the list of nodes identifiers that provided coded packets of a chunk as well as a flag to signal if the chunk has been corrupted. SIEVE operates on top of an otherwise reliable architecture and it is based on the construction of a factor graph obtained from the collected checks on which an incremental belief propagation algorithm is run to compute the probability of a node being malicious. Analysis is carried out by detailed simulations using ns-3. We show that SIEVE is very accurate and discuss how nodes speed impacts on its accuracy. We also show SIEVE robustness under several attack scenarios and deceiving actions.
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https://hal.inria.fr/hal-00911098
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Rossano Gaeta, Marco Grangetto, Riccardo Loti. SIEVE: a distributed, accurate, and robust technique to identify malicious nodes in data dissemination on MANET. 18th IEEE Int. Conference on parallel and distributed systems, Dec 2012, Singapore, Singapore. pp.331-338, ⟨10.1109/ICPADS.2012.53⟩. ⟨hal-00911098⟩

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