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Inference-Based Adaptation Techniques for Next Generation Jamming and Anti-Jamming Capabilities

Researcher: Patrick Tague

Research Area: Next Generation Secure and Available Networks

Cross Cutting Thrusts: Next Generation Threat Prediction and Response | Threat Analysis and Modeling


Continual advances in wireless communication technology offer additional protections against interference and jamming, but these same advances unfortunately also enable stronger attacks, especially given the low cost of modern software-defined radios. Observant attackers can achieve significant gains by incorporating knowledge of the network under attack, and jammers can consider various metrics, including attack impact, energy efficiency, and stealth. Moreover, attackers can continually adapt parameters and behaviors to compensate for system dynamics, thwart detection, and save valuable resources. Robust wireless communication protocols that can survive such adaptive attacks require new techniques for near-real-time defensive adaptation, allowing the defenders to similarly modify their parameters in response to perceived attack impacts. This project will involve the three primary tasks of identifying and modeling advanced inference-based jamming attacks, developing novel cross-layer network defenses to mitigate jamming attacks using similar adaptation techniques, and characterizing system-level behaviors that emerge from the interactions between multiple adapting parties. Contributions of the project will expand the existing body of knowledge in wireless network security by developing novel probabilistic, game theoretic, and control system theoretic models to better understand efficient and stealthy jamming attacks and provide a basis for future robust protocol design.

Outcomes: With past funding from CyLab and Northrop Grumman and continued funding from NSF, we have developed new attack and defense techniques as well as a software-defined radio testbed with front-end testing software to evaluate the interactions between selected attacks and defenses.