Pollution Data Detection and Analysis in Random Linear Network Coding
Wei Cui · Jisuanji gongcheng · 2010
Network coding is inherent vulnerable to the data pollution attacks.To address this problem,it discusses two random linear network coding pollution data detection schemes,one is based on homomorphic hash function which deduces the general formation and proves its correctness.The other is linear space signature.It comparatively analyzes their computational cost and payload efficiency under different data block size conditions,and proposes a new combinatory detection scheme for this problem.