Backup path set selection in ad hoc wireless network using link expiration time
Computers and Electrical Engineering
Detection of Packet Forwarding Misbehavior in Mobile Ad-Hoc Networks
WWIC '07 Proceedings of the 5th international conference on Wired/Wireless Internet Communications
LIDF: Layered intrusion detection framework for ad-hoc networks
Ad Hoc Networks
Optimal monitoring in multi-channel multi-radio wireless mesh networks
Proceedings of the tenth ACM international symposium on Mobile ad hoc networking and computing
Secure communication among cell phones and sensor networks
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Detect DDoS flooding attacks in mobile ad hoc networks
International Journal of Security and Networks
Energy efficient monitoring for intrusion detection in battery-powered wireless mesh networks
ADHOC-NOW'11 Proceedings of the 10th international conference on Ad-hoc, mobile, and wireless networks
Wireless Personal Communications: An International Journal
International Journal of Sensor Networks
IR, DR and BC with wireless mesh networks
Proceedings of the 2012 Information Security Curriculum Development Conference
| Hi-index | 0.07 |
We consider ad hoc networks with multiple, mobile intruders. We investigate the placement of the intrusion detection modules for misuse-based detection strategy. Our goal is to maximize the detection rate subject to limited availability of communication and computational resources. We mathematically formulate this problem, and show that computing the optimal solution is NP-hard. Thereafter, we propose two approximation algorithms that approximate the optimal solution within a constant factor, and prove that they attain the best possible approximation ratios. The approximation algorithms though require recomputation every time the topology changes. Thereafter, we modify these algorithms to adapt seamlessly to topological changes. We obtain analytical expressions to quantify the resource consumption versus detection rate tradeoffs for different algorithms. Using analysis and simulation, we evaluate these algorithms, and identify the appropriate algorithms for different detection rate and resource consumption tradeoffs.