TY - GEN
T1 - Tracking the Mobile Jammer in Wireless Sensor Networks Using Extended Kalman Filter
AU - Aldosari, Waleed
AU - Zohdy, Mohamed
AU - Olawoyin, Richard
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/10
Y1 - 2019/10
N2 - Wireless Sensor Networks (WSNs) are susceptible to jamming attacks due to the shared wireless medium. The jammer can disrupt any specific or entire radio frequency based on its function and strategies. Locating the jammer location is very important against the jamming in the wireless network and restore the communication channel. To support the existing anti-jamming techniques, we proposed an algorithm based on the Extended Kalman filter (EKF) and power received to track the jammer. Detecting jammer location is the first step taking to defend such attacks. Besides, estimating jammer location supports a wide range of defense. Range-based jammer localization technique based on the received power is used in this work to detect the external malicious node location by designed the position, velocity, and acceleration approach of Extended Kalman filter. An extensive simulation conducted to evaluate the performance of EKF compares to the Virtual Force Iteration Localization (VFIL), Weighted Centroid Localization (WCL), and Centroid Localization algorithms (CL). The EKF proves to be of high efficiency in comparison to VFIL, WCL, and CL.
AB - Wireless Sensor Networks (WSNs) are susceptible to jamming attacks due to the shared wireless medium. The jammer can disrupt any specific or entire radio frequency based on its function and strategies. Locating the jammer location is very important against the jamming in the wireless network and restore the communication channel. To support the existing anti-jamming techniques, we proposed an algorithm based on the Extended Kalman filter (EKF) and power received to track the jammer. Detecting jammer location is the first step taking to defend such attacks. Besides, estimating jammer location supports a wide range of defense. Range-based jammer localization technique based on the received power is used in this work to detect the external malicious node location by designed the position, velocity, and acceleration approach of Extended Kalman filter. An extensive simulation conducted to evaluate the performance of EKF compares to the Virtual Force Iteration Localization (VFIL), Weighted Centroid Localization (WCL), and Centroid Localization algorithms (CL). The EKF proves to be of high efficiency in comparison to VFIL, WCL, and CL.
KW - Extended Kalman filter
KW - Jammer localization
KW - Jamming attacks
KW - Localization
KW - Tracking
KW - Wireless sensor networks
UR - http://www.scopus.com/inward/record.url?scp=85080131452&partnerID=8YFLogxK
U2 - 10.1109/UEMCON47517.2019.8993050
DO - 10.1109/UEMCON47517.2019.8993050
M3 - Conference contribution
AN - SCOPUS:85080131452
T3 - 2019 IEEE 10th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2019
SP - 207
EP - 212
BT - 2019 IEEE 10th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2019
A2 - Chakrabarti, Satyajit
A2 - Saha, Himadri Nath
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2019
Y2 - 10 October 2019 through 12 October 2019
ER -