Physical resilience to insider attacks in IoT networks: Independent cryptographically secure sequences for DSSS anti-jamming

Abstract

Wireless communication is a key technology for the Internet of Things (IoT). Due to its open nature, the physical layer of wireless systems is a high-priority target for an adversary whose goal is to disrupt the normal behavior of the system. In particular, jamming attacks are one of the most straightforward and effective types of attacks: information flow of the system is stopped or severely disturbed. In this paper, we propose a method to improve the jamming resilience of IoT systems based on Direct-Sequence Spread-Spectrum (DSSS) techniques. Our proposal is inspired by the Moving Target Defense (MTD) paradigm. MTD strategies randomize components of a system, increasing the effort an attacker needs to compromise the system. We use state-of-the-art Cryptographically Secure Pseudo-Random Number Generators outputs as spreading sequences for DSSS. The sequences of the proposed system are generated in an ad-hoc, independent, and distributed way. We show probabilistically that the generated sequences have robust cross-correlation properties. We define a multiuser system model to evaluate the Bit-Error-Rate of our proposal in the presence of two types of jammers: a classical band-limited Gaussian noise jammer, and an insider smart jammer with knowledge of one spreading sequence used in the system. Our proposal proactively mitigates the insider jammer attack. We quantify the insider smart jammer resilience of a system implementing our proposal, as a function of the length of the spreading sequences and the jammer power.

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