Secure and Energy-Efficient Data Transmission System Based on Chaotic Compressive Sensing in Body-to-Body Networks

计算机科学 加密 密钥空间 压缩传感 数据传输 混乱的 解码方法 传输(电信) 高效能源利用 密码学 人体区域网 实时计算 算法 计算机网络 无线传感器网络 工程类 人工智能 电信 电气工程
作者
Haipeng Peng,Ye Tian,Jürgen Kurths,Lixiang Li,Yixian Yang,Wei-Hua Lin
出处
期刊:IEEE Transactions on Biomedical Circuits and Systems [Institute of Electrical and Electronics Engineers]
卷期号:11 (3): 558-573 被引量:122
标识
DOI:10.1109/tbcas.2017.2665659
摘要

Applications of wireless body area networks (WBANs) are extended from remote health care to military, sports, disaster relief, etc. With the network scale expanding, nodes increasing, and links complicated, a WBAN evolves to a body-to-body network. Along with the development, energy saving and data security problems are highlighted. In this paper, chaotic compressive sensing (CCS) is proposed to solve these two crucial problems, simultaneously. Compared with the traditional compressive sensing, CCS can save vast storage space by only storing the matrix generation parameters. Additionally, the sensitivity of chaos can improve the security of data transmission. Aimed at image transmission, modified CCS is proposed, which uses two encryption mechanisms, confusion and mask, and performs a much better encryption quality. Simulation is conducted to verify the feasibility and effectiveness of the proposed methods. The results show that the energy efficiency and security are strongly improved, while the storage space is saved. And the secret key is extremely sensitive, [Formula: see text] perturbation of the secret key could lead to a total different decoding, the relative error is larger than 100%. Particularly for image encryption, the performance of the modified method is excellent. The adjacent pixel correlation is smaller than 0.04 in different directions including horizontal, vertical, and diagonal; the entropy of the cipher image with a 256-level gray value is larger than 7.98.
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