Abstract:

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.

Key words: network coding, data pollution, detection

摘要：

网络编码对注入网络的污染数据攻击具有固有的脆弱性，针对该问题，讨论2种分别基于同态哈希函数和线性空间签名来检测随机线性网络编码中污染数据的方案，推导同态哈希函数的一般形式并证明方案的正确性。对比分析2种方案在不同数据分块大小情况下的计算开销和荷载效率，并给出一种新的组合检测方案。

关键词: 网络编码, 数据污染, 检测

CLC Number: 

• N945