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Continual advances in wireless communication technology offer additional protections against interference and jamming, but these same advances unfortunately also enable stronger attacks. 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 adapatation 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. Application areas in which the project work will be included are mobile commerce using NFC, home networking, medical information management, smart grid communication, and disaster response.
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CAREER: Inference-Based Adaptation Techniques for Next Generation Jamming and Anti-Jamming Capabilities