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Quantification Model and Systems for Assessing and Developing Resilient Wireless Communication Operation


TECHNOLOGY AREA(S): Information Systems

OBJECTIVE: The objective is to create a highly effective and accurate system that can identify stealthy wireless attacks. This topic will enhance the resiliency of Army and DoD cyber operations through better response to intrusions and more effective mitigation of attack impacts

DESCRIPTION: Wireless systems are important part of DoD operations, for both tactical and strategic applications. New capabilities such as unmanned vehicles or unmanned weapon systems are critically dependent on highly trusted and reliable wireless communications. However, due to the open communication of wireless communication, the system is subject to a wide range of external effects, ranging from environmental impact to malicious human attacks, especially silent attacks, such as carrier-sensing attacks, signal emulation, and radio interference are posing more challenges. With a much smaller footprint, many smart attacks can be easily blended in without being detected. The net consequence is that our wireless systems are seemingly working fine from network setup and operation perspective, but users/systems experience delays and information loss, leading to degraded mission execution capability.

It is critical that we establish a formal quantitative analysis models that can be used to predict, assess and analyze impact assessment of wireless systems. Such quantitative model and its associated benchmark will guide us to create effective detection systems, and design attack resilient wireless systems that can sustain critical missions. This topic seeks the development of advanced wireless quantification techniques as well as novel attack detection and defense frameworks that account for a broad scope of the attack space in a tactical network environment. The development should consist of both theoretical modeling and realistic hardware-in-the-loop experimentations with unique test and evaluation capabilities that can be provided by high fidelity radio frequency network channel emulators. The effectiveness of defense techniques should be thoroughly validated in hardware based experiments under realistic dynamic tactical scenarios.

PHASE I: Establish performance and resiliency models and quantification metrics for wireless system that are subject to stealthy attacks. Create proactive defense mechanism which include attack detection and dynamic maneuvering to identify potential threats and to mitigate their impact.

PHASE II: Develop an attack quantification and defense prototype system that can demonstrate the capability of attack detection, measurement, quantification, and proactive defense. Detection system efficiency and accuracy need to be verified not only in NS-2 type of software based simulation, but also through wireless network emulator that contains physical layer setup including true over the air RF waveforms, and that can replicate relevant and complex networking environment, such as multi-hop communication, multiple spectrum channels, radio interference, mobility, multi-path, and Doppler effects.

PHASE III DUAL USE APPLICATIONS: Further develop and mature the prototype system and reach TRL-6. Demonstrate the working prototype in an operationally relevant environment. Define, finalize, and execute the transition and commercialization plans such that the detection systems can be field tested.

DUAL-USE APPLICATIONS: Wireless defense technology has direct application in commercial communications, such as cellular communications, Wi-Fi and mobile cloud systems, sensor and vehicular networks, and satellite communications. In addition, related cyber defense capabilities could greatly enhance performance and resilience of public safety and emergency communications systems and support interoperability of other emerging wireless systems over unlicensed spectrum.


    • A. Hamieh, J. Ben-Othman, L. Mokdad, “Detection of Radio Interference Attacks in VANET”, Global Telecommunications Conference, 2009.


    • J. Tang, Y. Cheng, W. Zhuang, “Real-Time Misbehavior Detection in IEEE 802.11-Based Wireless Networks: An Analytical Approach”, IEEE Transactions on Mobile Computing, vol. 13, pp. 146-158, 2014.


    • J. Soto, S. Queiroz, M. Nogueira, “Managing sensing and cooperation to analyze PUE attacks in cognitive radio ad hoc networks”, the International Conference on Network and Service Management, 2012.


  • M. Spuhler, D. Giustiniano, V. Lenders, M. Wilhelm, J. B. Schmitt, “Detection of Reactive Jamming in DSSS-based Wireless Communications”, IEEE Transactions on Wireless Communications, vol. 13, pp. 1593 – 1603, 2014.

KEYWORDS: wireless attacks, quantification, measurement, emulation, defense, wireless networking

  • TPOC-1: Dr. Cliff Wang
  • Phone: 919-549-4207
  • Email:
  • TPOC-2: Dr. Hasan Cam
  • Phone: 301-394-2871
  • Email:
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