TripleLP: Privacy-Preserving Log Parsing Based on Blockchain
Teng Li, Shengkai Zhang, Zexu Dang, Yongcai Xiao, Zhuo Ma · 2023
The amount of computer log data in today’s world is exploding, and the huge amount of data is affecting data management, storage, and analysis. However, large-scale log analysis is a time-consuming and inefficient process, and the large amount of data makes data privacy protection extremely difficult. The TripleLP proposed in this article is an automated log parsing tool based on blockchain, which stores and manages logs in a structured and unified format within the blockchain. It provides a well-organized database for comprehensive log auditing of computing systems, which can efficiently parse large-scale log data while protecting data privacy. In this article, we validate TripleLP on a large-scale public log dataset (i.e. log hub). Experimental data shows that TripleLP can efficiently parse logs while protecting data privacy.