Provenance Compression Using Packet-Path-Index Differences in Wireless Sensor Networks

In wireless sensor networks (WSNs), provenance is critical for assessing the trustworthiness of data acquired and forwarded by sensor nodes, detecting early signs of attacks, etc. However, the provenance size expands rapidly with increases in the number of packet transmission hops. Among the existing provenance schemes, the dictionary based provenance scheme (DP) achieves the highest provenance compression rate. However, the major drawback of the DP scheme is that it is sensitive to the WSN's topology changes, which cannot be used in the WSNs with rapid topology changes. To overcome such a drawback and achieve a higher compression rate, we propose a path index differences based provenance scheme, in which we first establish backbone paths along the gradient direction, and then we devise a Truncation Hamming Distance (THD) based method to eliminate the backbone paths with high similarity and build the path dictionaries for the selected backbone paths of low similarity. With the support of such dictionaries, a new path is encoded by the index of a similar path in the dictionary together with the differences between them, which makes the size of the provenance stably compressed. Compared to the DP scheme, the simulation and experimental results show that our scheme can achieve a higher provenance compression ratio even if the topology structure of the WSN is not stable.