TY - GEN
T1 - Intrusion detection in wireless sensor networks for destructive intruders
AU - Yu, Qixiang
AU - Luo, Zhenxing
AU - Min, Paul
N1 - Publisher Copyright:
© 2015 Asia-Pacific Signal and Information Processing Association.
PY - 2016/2/19
Y1 - 2016/2/19
N2 - Intrusion detection in a wireless sensor network (WSN) has drawn intensive attentions recently due to its wide applications. Many issues in intrusion detection, such as sensor deployment, mobility of sensors and data fusion have been investigated extensively. However, the behavior of the intruder has rarely been investigated. In this paper, we introduce a novel situation where the intruder can destroy encountered sensors. This situation is analyzed theoretically and experimentally under our system model. The key point is to discuss the intrusion detection problem differently according to the speed of the intruder. We derive the detection probability, which can be applied to any sensor deployment utilizing the disc model. The detection model we used includes a single-sensing detection model and a multiple-sensing detection model. Some interesting factors in intrusion detection, such as transmission period, sampling period, and the random entrance time of the intruder are also considered. Finally, our Monte-Carlo simulation results validated our analytical results.
AB - Intrusion detection in a wireless sensor network (WSN) has drawn intensive attentions recently due to its wide applications. Many issues in intrusion detection, such as sensor deployment, mobility of sensors and data fusion have been investigated extensively. However, the behavior of the intruder has rarely been investigated. In this paper, we introduce a novel situation where the intruder can destroy encountered sensors. This situation is analyzed theoretically and experimentally under our system model. The key point is to discuss the intrusion detection problem differently according to the speed of the intruder. We derive the detection probability, which can be applied to any sensor deployment utilizing the disc model. The detection model we used includes a single-sensing detection model and a multiple-sensing detection model. Some interesting factors in intrusion detection, such as transmission period, sampling period, and the random entrance time of the intruder are also considered. Finally, our Monte-Carlo simulation results validated our analytical results.
KW - destructive intruder
KW - disc model
KW - intrusion detection
KW - wireless sensor network
UR - https://www.scopus.com/pages/publications/84986192992
U2 - 10.1109/APSIPA.2015.7415410
DO - 10.1109/APSIPA.2015.7415410
M3 - Conference contribution
AN - SCOPUS:84986192992
T3 - 2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2015
SP - 68
EP - 75
BT - 2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2015
Y2 - 16 December 2015 through 19 December 2015
ER -