A small-scale anonymous communication model using improved IBE for big data servers

Abstract

The centralized storage and processing of big data increases the risk of communication data leakage, and the security of user communication transmission has become a current research hotspot. Therefore, to improve the efficiency of existing anonymous communication schemes, this study designs an anonymous identity-based encryption algorithm based on the Decisional Bilinear Diffie-Hellman. An anonymous communication model for small-scale users is further proposed. When the data size was 100 MB, the proposed algorithm had an upload time cost of approximately 827.3 ms and a download time cost of 208.4 ms. The proposed method reduced communication time by 37.86%, 30.43%, and 16.88% compared with other methods, respectively. Under 20 multiple server attacks, the average resistance time was as high as 22.78 s, which increased by 30.02%, 25.65%, 52.07%, 488.63%, and 78.67% compared with the other 5 methods, respectively. The anonymous identity-based encryption algorithm can improve the security of information transmission, and the small-scale anonymous communication model strengthens the privacy and security of user communication processes, which is significant for improving the security of big data servers.