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

职业：下一代干扰和抗干扰能力的基于推理的适应技术

• 批准号: 1149582
• 负责人: Patrick Tague
• 金额: $ 51.24万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1149582&HistoricalAwards=false
• 关键词: CAREER; Inference; Based; Adaptation; Techniques

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.

无线通信技术的不断进步提供了针对干扰和干扰的额外保护，但不幸的是，这些同样的进步也使更强大的攻击成为可能。 观察力强的攻击者可以通过整合受攻击网络的知识来获得显着收益，干扰者可以考虑各种指标，包括攻击影响，能源效率和隐身。 此外，攻击者可以不断调整参数和行为，以补偿系统动态，阻挠检测，并节省宝贵的资源。要想在这种自适应攻击中幸存下来，健壮的无线通信协议需要新的近实时防御自适应技术，使防御者能够根据感知到的攻击影响类似地修改其参数。该项目将涉及三个主要任务：识别和建模基于推理的高级干扰攻击，开发新的跨层网络防御以使用类似的自适应技术减轻干扰攻击，以及表征从多个适应方之间的交互中出现的系统级行为。该项目的贡献将通过开发新的概率，博弈论和控制系统理论模型来扩展无线网络安全的现有知识体系，以更好地理解高效和隐身的干扰攻击，并为未来的鲁棒协议设计提供基础。该项目工作将包括的应用领域包括使用NFC的移动的商务、家庭网络、医疗信息管理、智能电网通信和灾难响应。