Visible to the public EAGER: Malicious Behavior Detection in Hybrid Dynamic Spectrum AccessConflict Detection Enabled

Project Details

Lead PI

Performance Period

Sep 01, 2017 - Aug 31, 2019

Institution(s)

SUNY at Binghamton

Award Number


To tackle the ever-increasing spectrum scarcity issue, dynamic spectrum access is envisioned as a set of promising new spectrum management paradigms. Although it has enabled the opportunistic access of underutilized licensed bands, various practical factors, such as environmental dynamics, intentional interference, and unauthorized transmission, hinder it from wide deployment. The recently released FCC rules suggest participatory real-time spectrum sensing can greatly improve the spectrum utilization efficiency for database-driven spectrum sharing, which forms a new paradigm, hybrid dynamic spectrum sharing. However, the frequent information exchanged between secondary users and spectrum database can be easily intercepted and manipulated by malicious users, which not only downgrades the spectrum efficiency but also incurs severe security breaches to the hybrid dynamic spectrum access system. This project will explore new paradigms of safeguarding the future cognitive radio system with focus on non-compliance behavior detection. The success of this project will serve as a key enabler to provide reliable wireless communication in the near future.

This project will investigate several fundamental security challenges in the newly defined hybrid dynamic spectrum access. This first research task will identify new attack models that compromise the spectrum efficiency and then provide countermeasures adapted to future wireless systems. Due to the inherent nature of database-driven spectrum access, primary user emulation (PUE) attackers can retrieve the spectrum availability information to either perform as the incumbent user (IU) when it is not present, or try to increase secondary users' transmission power to interfere with present IUs. Featuring the sensing results stored in the database, novel detection schemes will be designed to mitigate the influence brought by the attack. The second research task leverages physical-layer approaches to detect unauthorized access under different channel models. To address this issue, channel availability information will be used to detect malicious secondary users. Meanwhile, the detection mechanisms will be developed with joint consideration on practicality and efficiency. Additionally, the project includes strong validation component that combines simulation study, prototyping, and experimentation. It will thus provide an effective training ground for interdisciplinary subjects including wireless networks, wireless communication, and cybersecurity, all of which are critical to diversified professionals for future national work force.