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Secure Routing for Mobile Ad hoc Networks

About

The emergence of the Mobile Ad Hoc Networking (MANET) technology advocates self-organized wireless interconnection of communication devices that would either extend or operate in concert with the wired networking infrastructure or, possibly, evolve to autonomous networks. In either case, the proliferation of MANET-based applications depends on a multitude of factors, with trustworthiness being one of the primary challenges to be met. Despite the existence of well-known security mechanisms, additional vulnerabilities and features pertinent to this new networking paradigm might render such traditional solutions inapplicable. In particular, the absence of a central authorization facility in an open and distributed communication environment is a major challenge, especially due to the need for cooperative network operation. In particular, in MANET, any node may compromise the routing protocol functionality by disrupting the route discovery process. In this paper, we present a route discovery protocol that mitigates the detrimental effects of such malicious behavior, as to provide correct connectivity information. Our protocol guarantees that fabricated, compromised, or replayed route replies would either be rejected or never reach back the querying node. Furthermore, the protocol responsiveness is safeguarded under different types of attacks that exploit the routing protocol itself. The sole requirement of the proposed scheme is the existence of a security association between the node initiating the query and the sought destination. Specifically, no assumption is made regarding the intermediate nodes, which may exhibit arbitrary and malicious behavior. The scheme is robust in the presence of a number of non-colluding nodes, and provides accurate routing information in a timely manner.

Panagiotis Papadimitratos, Zygmunt J. Haas• 2024

Related benchmarks

TaskDatasetResultRank
Discriminative PerformanceUltrafeedback 61.1k (test)
Accuracy70.13
30
Generative PerformanceHH Golden 42.5k (test)
Win Rate82.8
30
Discriminative PerformanceHH_Golden 42.5k (test)
Accuracy96.8
30
Generative PerformanceUltrafeedback 61.1k (test)
Win Rate65.6
30
Preference AlignmentUltrafeedback 20% flipping ratio
Accuracy73.96
12
Preference AlignmentUltrafeedback 40% flipping ratio
Accuracy63.99
12
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