scholarly journals Hybrid security protocol for wireless body area networks

2011 ◽  
Vol 11 (2) ◽  
pp. 277-288 ◽  
Author(s):  
Chol Soon Jang ◽  
Deok Gyu Lee ◽  
Jong-wook Han ◽  
Jong Hyuk Park
Keyword(s):  
Body Area Networks ◽  
Wireless Body Area Networks ◽  
Security Protocol ◽  
Body Area

scholarly journals From Wireless Sensor Networks to Wireless Body Area Networks: Formal Modeling and Verification on Security Using PAT

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Tieming Chen ◽  
Zhenbo Yu ◽  
Shijian Li ◽  
Bo Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Model Checking ◽  
Formal Method ◽  
Body Area Networks ◽  
Wireless Body Area Networks ◽  
Security Protocol ◽  
Wireless Sensor ◽  
Formal Modeling ◽  
Body Area

Model checking has successfully been applied on verification of security protocols, but the modeling process is always tedious and proficient knowledge of formal method is also needed although the final verification could be automatic depending on specific tools. At the same time, due to the appearance of novel kind of networks, such as wireless sensor networks (WSN) and wireless body area networks (WBAN), formal modeling and verification for these domain-specific systems are quite challenging. In this paper, a specific and novel formal modeling and verification method is proposed and implemented using an expandable tool called PAT to do WSN-specific security verification. At first, an abstract modeling data structure for CSP#, which is built in PAT, is developed to support the node mobility related specification for modeling location-based node activity. Then, the traditional Dolev-Yao model is redefined to facilitate modeling of location-specific attack behaviors on security mechanism. A throughout formal verification application on a location-based security protocol in WSN is described in detail to show the usability and effectiveness of the proposed methodology. Furthermore, also a novel location-based authentication security protocol in WBAN can be successfully modeled and verified directly using our method, which is, to the best of our knowledge, the first effort on employing model checking for automatic analysis of authentication protocol for WBAN.

scholarly journals Efficient Key Agreement Algorithm for Wireless Body Area Networks Using Reusable ECG-Based Features

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 404
Author(s):  
Yasmeen Al-Saeed ◽  
Eman Eldaydamony ◽  
Ahmed Atwan ◽  
Mohammed Elmogy ◽  
Osama Ouda
Keyword(s):  
Secure Communication ◽  
Key Agreement ◽  
Body Area Networks ◽  
Wireless Body Area Networks ◽  
Sensor Nodes ◽  
Security And Privacy ◽  
Physiological Data ◽  
Computer Assisted ◽  
Body Area ◽  
Key Agreement Protocol

Wireless Body Area Networks (WBANs) are increasingly employed in different medical applications, such as remote health monitoring, early detection of medical conditions, and computer-assisted rehabilitation. A WBAN connects a number of sensor nodes implanted in and/or fixed on the human body for monitoring his/her physiological characteristics. Although medical healthcare systems could significantly benefit from the advancement of WBAN technology, collecting and transmitting private physiological data in such an open environment raises serious security and privacy concerns. In this paper, we propose a novel key-agreement protocol to secure communications among sensor nodes of WBANs. The proposed protocol is based on measuring and verifying common physiological features at both sender and recipient sensors prior to communicating. Unlike existing protocols, the proposed protocol enables communicating sensors to use their previous session pre-knowledge for secure communication within a specific period of time. This will reduce the time required for establishing the shared key as well as avoid retransmitting extracted features in the medium and hence thwarting eavesdropping attacks while maintaining randomness of the key. Experimental results illustrate the superiority of the proposed key agreement protocol in terms of both feature extraction and key agreement phases with an accuracy of 99.50% and an error rate of 0.005%. The efficacy of the proposed protocol with respect to energy and memory utilization is demonstrated compared with existing key agreement protocols.

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