A secure three-party authentication protocol for wireless body area networks

Vishwakarma, Rahul; Mohapatra, Ramesh Kumar

doi:10.1109/ssps.2017.8071573

Cited by 6 publications

(4 citation statements)

References 9 publications

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“…In light of the above challenges, there is need for the development of lightweight and efficient security solutions for these networks to curb the numerous active and passive attacks [1], [3], [24], [25], [26], [27]. One of the most effective mechanisms for boosting security in wireless networks is through strong mutual authentication [28], [29].…”

Section: Figure 1 Wban Communication Architecturementioning

confidence: 99%

Wireless body area networks: A critical review of the state-of-the-art security schemes

Auko¹,

Abeka²

2022

Global J. Eng. Technol. Adv.

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The continued advancement of information communication technologies (ICT) has led to the adoption of internet of things in the healthcare sector. One of such application domain of ICT is the wireless body area network (WBAN), which enables remote monitoring of vital biomedical parameters on the patient or the elderly. Upon collection of these parameters, they are forwarded to the remote hospital servers where analysis and appropriate actions are taken. Obviously, the data exchanged in these networks is sensitive and private and hence can have devastating effects on the patient if leaked to the unintended parties. Consequently, many security solutions have been developed in literature. The goal of this paper is to carry out an extensive review of these security schemes in an effort to pin point their strengths and weaknesses. Based on the findings, it is evident that many of these security solutions try to attain a number of security and privacy protection. However, it is noted that these schemes still lack many of the required security goals such as anonymity, untraeability, forward key secrecy as well as resistance to many of the conventional attacks. Therefore, some recommendations for the attainment of perfect privacy and security are given towards the end of this paper.

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Section: Figure 1 Wban Communication Architecturementioning

confidence: 99%

Wireless body area networks: A critical review of the state-of-the-art security schemes

Auko¹,

Abeka²

2022

Global J. Eng. Technol. Adv.

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“…Such motes emphasize on collecting numerous physical properties, such as Blood Pressure, ECG, etc. The next task is to broadcast the gathered data to the discrete terminals [3,4]. Afterward, these terminals lead to transmit the entire data to the relevant doctor or clinical server.…”

Section: Introduction 11 Wireless Body Area Network (Wban)mentioning

confidence: 99%

“…Additionally, it is presumable that there is a direct line of sight between the network nodes and the base station. The chosen paradigm is regarded as a multipath fading model 𝑑4 (𝑣 𝑖 , 𝑣 𝑗 ) if the transmission distance 𝑑(𝑣 𝑖 , 𝑣 𝑗 ) between 𝑣 𝑖 and 𝑣 𝑗 is greater than the threshold distance d 0. This is true of the suggested protocol.…”

mentioning

confidence: 99%

Cooperative Routing and Improved Energy-Efficient Harvested- Aware Clustering for Wireless Body Area Network

Kaleem

Muthukumaran

2023

Preprint

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WBAN assisted healthcare deployments have the potential to provide important insights for the improvement of health care services to patients as well as for diagnostic and/or clinical monitoring. In a short span of time, WBAN technology has crossed the initial point of entry in the medical restoration and patients’ monitoring. Nevertheless, the fundamental technology is still in the infancy phase of development, and usually depends on highly distinctive wireless communication technologies. The power consumption is the major issue of WBAN. The E-HARP protocol is the existing model which is already proposed to reduce power consumption of WBAN. In the E-HARP protocol, the network is split up into clusters and CH, members are selected dynamically. In this research work, E-HARP protocol is improved in which cache nodes are deployed in the network to forward data to base station. In improved E-HARP protocol single base station is used as in E-HARP protocol two base station are used to receive data. The protocol is implemented in MATLAB is executed to simulate this protocol and diverse metrics: throughput, delay and power consumption are employed to analyze the outcomes.

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“…WBANs are also referred to as body sensor networks (BSNs). Many studies have recently been conducted in WBAN for continuous patient monitoring [ 1 , 2 , 3 , 4 , 5 ]. Unfortunately, the current WBAN does not meet the QoS for a patient [ 6 , 7 ].…”

Section: Introductionmentioning

confidence: 99%

Blockchain Based Delay and Energy Harvest Aware Healthcare Monitoring System in WBAN Environment

Anbarasan

Jaisankar

2022

Sensors

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Wireless body area networks (WBANs) are a research area that supports patients with healthcare monitoring. In WBAN, the Internet of Things (IoT) is connected with WBAN for a smart/remote healthcare monitoring system in which various medical diseases are diagnosed. Quality of service (QoS), security and energy efficiency achievements are the major issues in the WBAN-IoT environment. Existing schemes for these three issues fail to achieve them since nodes are resource constrained and hence delay and the energy consumption is minimized. In this paper, a blockchain-assisted delay and energy aware healthcare monitoring (B-DEAH) system is presented in the WBAN-IoT environment. Both body sensors and environment sensors are deployed with dual sinks for emergency and periodical packet transmission. Various processes are involved in this paper, and each process is described as follows: Key registration for patients using an extended version of the PRESENT algorithm is proposed. Cluster formation and cluster head selection are implemented using spotted hyena optimizer. Then, cluster-based routing is established using the MOORA algorithm. For data transmission, the patient block agent (PBA) is deployed and authenticated using the four Q curve asymmetric algorithm. In PBA, three entities are used: classifier and queue manager, channel selector and security manager. Each entity is run by a special function, as packets are classified using two stream deep reinforcement learning (TS-DRL) into three classes: emergency, non-emergency and faulty data. Individual packets are put into a separate queue, which is called emergency, periodical and faulty. Each queue is handled using Reyni entropy. Periodical packets are forwarded by a separate channel without any interference using a multi objective based channel selection algorithm. Then, all packets are encrypted and forwarded to the sink nodes. Simulation is conducted using the OMNeT++ network simulator, in which diverse parameters are evaluated and compared with several existing works in terms of network throughput for periodic (41.75 Kbps) and emergency packets (42.5 Kbps); end-to-end delay for periodic (0.036 s) and emergency packets (0.028 s); packet loss rate (1.1%); residual energy in terms of simulation rounds based on periodic (0.039 J) and emergency packets (0.044 J) and in terms of simulation time based on periodic (8.35 J) and emergency packets (8.53 J); success rate for periodic (87.83%) and emergency packets (87.5%); authentication time (3.25 s); and reliability (87.83%).

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A secure three-party authentication protocol for wireless body area networks

Cited by 6 publications

References 9 publications

Wireless body area networks: A critical review of the state-of-the-art security schemes

Wireless body area networks: A critical review of the state-of-the-art security schemes

Cooperative Routing and Improved Energy-Efficient Harvested- Aware Clustering for Wireless Body Area Network

Blockchain Based Delay and Energy Harvest Aware Healthcare Monitoring System in WBAN Environment

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