Optimal Green Hybrid Attacks in Secure IoT

TL;DR

This paper introduces a novel framework for optimizing the energy efficiency of hybrid eavesdropping and jamming attacks in secure IoT, achieving significant improvements over benchmarks.

Contribution

It presents an analytical solution for jointly optimizing attack mode, eavesdropping, and jamming to maximize attacker energy efficiency in IoT security.

Findings

About 45% improvement in average attacker energy efficiency.

Analytical solutions for optimal attack parameters.

Validation through numerical results.

Abstract

In pursuance to understand the behavior of a potential green hybrid attacker in secure internet-of-things (IoT), this letter investigates optimal energy utilization from the attacker's viewpoint. Specifically, we propose a novel framework for optimizing the efficacy of a hybrid attacker, possessing capability to both eavesdrop and jam, while considering the underlying energy consumption. In particular, we maximize the attacker energy efficiency (AEE) in secure IoT by deriving the analytical solutions for jointly global-optimal attacking mode, eavesdropping rate, and jamming power. Numerical results, validating analytical claims, reveal that the proposed green design can offer about 45% improvement in average AEE over the relevant benchmarks.