Journal
IEEE INTERNET OF THINGS JOURNAL
Volume 7, Issue 5, Pages 4061-4071Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2019.2961431
Keywords
Internet of Things; Compression algorithms; Security; Distributed databases; Encoding; Reliability; Error analysis; Attack detection; compression; data provenance; security
Categories
Funding
- National Natural Science Foundation of China [61802180]
- Natural Science Foundation of Jiangsu Province [BK20180421]
- National Cryptography Development Fund [MMJJ20180105]
- Fundamental Research Funds for the Central Universities [NE2018106]
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Data provenance is an effective method to evaluate data reliability and has become a research hotspot in recent years. However, the size of the data provenance will increase rapidly as the number of hops experienced increases, which conflicts with the limitations of energy, storage, and resources of IoT devices. The existing DP provenance compression algorithm has a high error rate when decompressing. To solve this problem, we propose an index-based provenance compression algorithm, which adopts the idea of common substring matching, combined with path identifier and path index to represent the path information in the data provenance, thereby achieving the purpose of reducing the size of data provenance. In addition, we extend the data provenance scheme to attack detection and propose a malicious node identification method based on data provenance. The simulation results show that the proposed scheme has a high compression ratio and higher decoding accuracy and has high accuracy in malicious node identification.
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