Abstract

In recent years, data security becomes a critical issue restricting the wider acceptance of Internet of Things (IoT) devices and Cyber-physical systems since they have limited hardware resources and power supply while high data security protection requires relatively large hardware resources and power supply utilization. This contradiction is particularly prominent in the field of Wireless Body Area Networks (WBANs) which is a segment of the IoT field. WBANs are dedicated to transmit and process biomedical data collected from human beings, any kind of tampering or hacking may cause severe consequences to users. However, the limited computing ability and battery supply of biomedical sensors attached or implanted in the users restrict the security protection strength of the data in WBANs. In this paper, a quantized Logistic mapping-based stream encryption scheme for WBANs is proposed. Meanwhile, Power spectral entropy (PSD) and Peak-to-average Power Ratio (PAPR) analysis of the quantized chaotic sequences have been performed to evaluate the chaotic characteristic among different quantization precision to resolve the ineffectiveness of Lyapunov factor in quantized systems. This encryption scheme utilizes chaotic systems with different quantization precision based on the security requirement of every individual communication, which leads to higher hardware and power efficiency. Finally, the proposed encryption scheme is implemented with VHDL and synthesized using SMIC 60 CMOS technology. The evaluation results illustrate that the proposed encryption scheme has the advantages of high-security performance and high-efficiency hardware resources utilization.

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