Privacy Preservation Against Traffic Analysis Using Random Network Coding in Multi-Hop Wireless Networks
In multi-hop wireless networks, privacy threat is one of the critical issues, where attacks such as traffic analysis can be easily launched by a malicious adversary due to the open-air transmission. Network coding has the potential to thwart traffic analysis attacks since the coding/mixing operation is encouraged at intermediate nodes. However, the simple deployment of network coding cannot achieve the goal once enough packets are collected by the adversaries. Different from any existing solutions, this paper proposes a novel network coding based privacy-preserving scheme against traffic analysis in multi-hop wireless networks. With homomorphic encryption on Global Encoding Vectors (GEVs). The proposed scheme offers two significant privacy-preserving features, packet flow intractability and message content confidentiality, for efficiently thwarting the traffic analysis attacks.