Title :
A New Sybil Attack Detection for Wireless Body Sensor Network
Author :
Ruixia Liu ; Yinglong Wang
Author_Institution :
Coll. of Inf. Sci. & Eng., Shandong Univ. of Sci. & Technol., Qingdao, China
Abstract :
The body sensor network (BSN) possess enormous potential for changing people´s daily lives. The data of BSN´s is associated with the physiological health of the user information and privacy, therefore require higher security protection. Sybil attack is particularly easy to perform in BSN where the communication medium is broadcast with multiple node identifiers (ID).In contrast to existing solutions which are based on sharing encryption keys, we propose a new received signal strength indicator (RSSI) based technique to identify Sybil nodes when they are regulating their transmission power. This mechanism not only does not adopt symmetric key encryption technology, but also does not require each node maintains its own identity certificate. Both analysis and simulation results show that our solutions are effective and efficient, providing high detection rate, while incurring limited overhead.
Keywords :
RSSI; body sensor networks; cryptography; telecommunication security; BSN; ID; RSSI; key encryption technology; multiple node identifiers; received signal strength indicator; security protection; sybil attack detection; transmission power; wireless body sensor network; Body area networks; Body sensor networks; Computational intelligence; Peer-to-peer computing; Security; Simulation; BSN; RSSI; atack dection; sybil attackt;
Conference_Titel :
Computational Intelligence and Security (CIS), 2014 Tenth International Conference on
Conference_Location :
Kunming
Print_ISBN :
978-1-4799-7433-7
DOI :
10.1109/CIS.2014.70