Collaborative Adversarial Modeling for Spectrum Aware IoT Communications

• Published in: 2018 International Conference on Computing, Networking and Communications (ICNC) pp. 447 - 451
• Main Authors: Samanta, Priyanka, Kelly, Elizabeth, Bashir, Amina, Debroy, Saptarshi
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.03.2018
• Subjects: Collaboration; collaborative attacks; Computational modeling; Dynamic spectrum access; Games; Hardware; Internet of Things; leader-follower game; Security; selfish adversary; Sensors
• DOI: 10.1109/ICCNC.2018.8390289

In order to cater the growing spectrum demands of large scale future 5G Internet of Things (IoT) applications, Dynamic Spectrum Access (DSA) based networks are being proposed as a high-throughput and cost-effective solution. However the lack of understanding of DSA paradigm's inherent security vulnerabilities on IoT networks might become a roadblock towards realizing such spectrum aware 5G vision. In this paper, we make an attempt to understand how such inherent DSA vulnerabilities in particular Spectrum Sensing Data Falsification (SSDF) attacks can be exploited by collaborative group of selfish adversaries and how that can impact the performance of spectrum aware IoT applications. We design a utility based selfish adversarial model mimicking collaborative SSDF attack in a cooperative spectrum sensing scenario where IoT networks use dedicated environmental sensing capability (ESC) for spectrum availability estimation. We model the interactions between the IoT system and collaborative selfish adversaries using a leaderfollower game and investigate the existence of equilibrium. Using simulation results, we show the nature of adversarial and system utility components against system variables. We also explore Pareto-optimal adversarial strategy design that maximizes the attacker utility for varied system strategy spaces.