Encrypted data stream identification using randomness sparse representation and fuzzy Gaussian mixture model
Hong Zhang, Rui Hou, Lei Yi, Juan Meng, Zhisong Pan, Yuhuan Zhou · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2016
The accurate identification of encrypted data stream helps to regulate illegal data, detect network attacks and protect users' information. In this paper, a novel encrypted data stream identification algorithm is introduced. The proposed method is based on randomness characteristics of encrypted data stream. We use a l1-norm regularized logistic regression to improve sparse representation of randomness features and Fuzzy Gaussian Mixture Model (FGMM) to improve identification accuracy. Experimental results demonstrate that the method can be adopted as an effective technique for encrypted data stream identification.