Pattern recognition for detecting distributed node exhaustion attacks in wireless sensor networks

Malicious attacks when launched by the adversary-class against sensor nodes of a wireless sensor network, can disrupt routine operations of the network. The mission-critical nature of these networks signifies the need to protect sensory resources against all such attacks. Distributed node exhaustion attacks are such attacks that may be launched by the adversarial class from multiple ends of a wireless sensor network against a set of target sensor nodes. The intention of such attacks is the exhaustion of the victim’s limited energy resources. As a result of the attack, the incapacitated data-generating legitimate sensor nodes are replaced with malicious nodes that will involve in further malicious activity against sensory resources. One such activity is the generation of fictitious sensory data to misguide emergency response systems to mobilize unwanted contingency activity. In this paper, a model is proposed for such an attack based on network traffic flow. In addition, a distributed mechanism for detecting such attacks is also defined. Specific network topology-based patterns are defined to model normal network traffic flow, and to facilitate differentiation between legitimate traffic packets and anomalous attack traffic packets. The performance of the proposed attack detection scheme is evaluated through simulation experiments, in terms of the size of the sensor resource set required for participation in the detection process for achieving a desired level of attack detection accuracy. The results signify the need for distributed pattern recognition for detecting distributed node exhaustion attacks in a timely and accurate manner.