Developments in wireless communications and wearable devices have facilitated the emergence of a network of tiny sensors embedded in, on or around human body called Wireless Body Area Network (WBAN). Over the last decade, WBAN has increasingly been playing a vital role in modern medical systems because of its potential to revolutionize healthcare delivery. The data collected by the sensors contain sensitive information and are transmitted via wireless channels. However, the openness of these channels makes WBAN vulnerable to attacks by unauthorized users. Therefore, secure authentication and data encryption schemes in WBAN are essential. The resource constraint nature of the sensors makes traditional cryptographic schemes unsuitable. Consequently, authentication schemes based on channel characteristics are proposed, which are more suitable with fewer requirements. However, existing approaches do not consider mutual authentication as well as passive/active attacks. Motivated by these limitations, we propose in this paper, a mutual authentication and data encryption scheme based on signal propagation characteristics and enhanced butterfly algorithm. To validate the effectiveness of our scheme, we conducted an extensive real-world experiment involving 5 volunteers in indoor and outdoor areas, under distinct scenarios. We further conducted security and performance analyses to validate the effectiveness of our scheme in terms of resources and its resilience to various attacks. The results of the experiments and the analyses show that our scheme could mutually identify legitimate users and protect user data against active/passive eavesdropping attacks with minimal overhead.INDEX TERMS Authentication, active attack, passive attack, signal propagation characteristic, wireless body area network (WBAN).
This paper presents an automated non-intrusive control system for monitoring the water level of domestic overhead and underground reservoir tank base on the property of wave reflection. The system consists of two HC-SR04 Ultrasonic transceivers that generate ultrasonic pulses and determines the depth of the water surface based on the total Time of Flight (TOF) of the reflected wave. An ATMEGA328 microcontroller was programmed to read the sensors, control the water level and display the corresponding volume of the water on a Liquid Crystal Display (LCD). The experimental result proves the system stability both at turbulence and laminar flows. The proposed approach can be extended to monitor and control the volume and level of other valuable fluids such as diesel, kerosene etc.; as well as hazardous chemical where human interventions may be treacherous.
Owing to its capability to measure the sensitive biological data of patients through embedded sensors and transmit them via open wireless channels to remote medical experts, wireless body area network (WBAN) has been playing an important role in pervasive healthcare systems. However, the open nature of the wireless channels renders the data susceptible to being eavesdropped by an adversary and linked to the identities of the transmitting devices, which can enable the adversary to gain sensitive information and launch targeted physical attacks. Therefore, anonymous authentication and confidentiality of the data in WBAN are vital. In the last few years, numerous anonymous authentication schemes based on cryptographic primitives and physiological features were designed to enhance security in WBAN. However, most of the existing schemes are not computationally efficient or require additional sensing hardware. To address these limitations, we propose an efficient anonymous authentication scheme for WBAN based on signal propagation characteristics. The key idea in the proposed scheme is to utilize the distinct received signal strength (RSS) variation profiles between on-body and off-body communication channels to conceal the identities of communicating devices, thereby ensuring their anonymity during authentication. We perform security and performance analyses of the proposed approach to prove its security strength and computational efficiency, respectively. Moreover, extensive experiments are conducted on human volunteers in indoor and outdoor environments to show the robustness of our approach. The results of the analyses and the experiments show that our scheme can successfully mitigate 88.8% of active attack attempts with less computation overhead.
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