Research on Big Data Encryption Algorithm Based on Data Redundancy Elimination Technology

In the privacy encryption of big data classification, the traditional encryption method based on chaos theory simply regards chaotic sequence as a key without secondary encryption process, which reduces the security of the key and the effectiveness of encryption. This paper discusses the principle of data privacy encryption algorithm in big data environment and the optimization of data privacy encryption algorithm. The message redundancy is dynamically adjusted by using the expected probability of successful transmission of messages to sink and the current opportunity probability of nodes, so that the lower the opportunity probability of forwarding messages, the higher the forwarding redundancy, and the clustering of redundant features of large data sets is realized. Experimental results show that the proposed algorithm has high performance of eliminating redundant data, and the clustering effect of big data under this algorithm is excellent, with high balance.