NeTS-NOSS: Robust Sensor Network Architecture through Neighborhood Monitoring and Isolation

Purdue University, West Lafayette IN

Investigators

Abstract

Proposal Number: 0626830 PI: Saurabh Bagchi Institution: Purdue University Title: NeTS-NOSS: Robust Sensor Network Architecture Through Neighborhood Monitoring and Isolation Abstract The project provides resilience to wireless networks of mobile ad hoc and sensor (MAHAS) nodes, which are vulnerable to a wide range of security attacks. These attacks could involve eavesdropping, message tampering, or identity spoofing, that have been addressed by customized cryptographic primitives for encryption and authentication. Alternately, the attacks may be targeted to the control or the data traffic in wireless networks. Since the networks are resource constrained (bandwidth, energy, or processing), providing detection and countermeasures to such attacks often turn out to be more challenging than in wired networks. The project is developing protocols for detecting, diagnosing, and mitigating one class of attacks, namely, those that affect the control traffic. Typical examples of control traffic are routing, monitoring the liveness of nodes, and system management. It is critical to guarantee the fidelity of control traffic since disrupting it can hamper the data traffic. For example, if a malicious node manages to interpose itself in an established route between two legitimate nodes, it can disrupt the data traffic by selectively dropping the data packets. Such attacks are often difficult to detect and can be launched without the need for cryptographic keys. The research presents a technique called local monitoring whereby nodes oversee part of the traffic going in and out of its neighbor nodes. The project makes neighbor monitoring feasible in resource constrained environments and mitigates the effect of the malicious node through isolation, either locally or globally using a distributed protocol. The work will enable the deployment of MAHAS networks for critical secure applications. We expect application of the results to two testbeds for environment monitoring (water quality and pharmaceutical manufacturing) that we are currently building.