Threats, Defences, and Governance in Cyber–Physical Systems Security: A Structured Review of the 2020–2026 Literature
TL;DR
A structured narrative review of 82 sources organised through the CPS Defence-Gap Taxonomy—a framework that classifies 14 attack mechanisms by architectural layer and physical impact, evaluates six defensive technology categories against documented failure modes, and maps five governance dimensions to the institutional conditions required for deployment.
Abstract
When a water treatment plant, power grid, or pipeline is compromised, the consequences extend beyond data loss: a manipulated sensor reading can trigger physical damage, and a disabled safety interlock can endanger lives. Cyber–physical systems (CPSs) sit at this intersection of digital control and physical process, yet existing security reviews treat threats and defences in separate silos, leaving practitioners without a clear picture of which defences fail against which attacks, and why. This paper fills that gap with a structured narrative review of 82 sources (70 from the primary window January 2020 to April 2026, plus 12 foundational pre-2020 works), organised through the CPS Defence-Gap Taxonomy (CPS-DGT)—a framework that classifies 14 attack mechanisms by architectural layer and physical impact, evaluates six defensive technology categories against documented failure modes, and maps five governance dimensions to the institutional conditions required for deployment. Across five intrusion detection system (IDS) studies that differ in dataset, attack selection, training regime and evaluation scope, reported F1 scores lie between 0.796 and 0.969 under each study’s own standard conditions; these values are not a controlled comparison and are reported descriptively. For the one architecture evaluated under adversarial evasion, F1 falls by 37.4 percentage points in absolute terms, a relative reduction of 38.6%. The defence-gap matrix identifies seven entries with insufficient coverage. Five of the 14 attack mechanisms are uncovered: A03, A09, A10, A11 and A14. Two further mechanisms, A01 and A12, have only partial defences. Adversarial evasion of learned detectors is reported separately as a transversal failure mode of one defensive category rather than as an attack mechanism. The uncovered mechanisms cluster at the cyber–physical boundary and in supply-chain channels. We conclude with five concrete research challenges, each with a direct path from the identified gap to a tractable research agenda.