Bespoke Weighting Schema and Sequence of Transformations for Enhanced Insight into Prospective False Command Injection Attacks

Malicious False Command Injection Attacks (FCIA) can induce power outages, particularly in high automation Smart Grids (SGs). Establishing defensive mitigation bulwarks against FCIA remains a challenging task. Perhaps even more daunting, particularly for those charged with mitigation, is the task of positing likely FCIA Attack Areas of Interest (AAOIs) (FCIA-AAOIopt). This paper introduces a bespoke Adaptive Weighting Schema (AWS) for the derivation of the involved Convex Constrained Optimization Problems (CCOPs), via a Sequence of Transformations (SOT), for better insight into the prospective FCIA-AAOIopt. An Advanced Persistent Threat (APT) Insider Threat Paradigm (ITP) was considered, and an Optimized Contextualization Schema or OCS — comprised of an enhanced Constriction Factor Particle Swarm Optimization-based Robust Convex Relaxation platform — is utilized for the examination. Given the highly significant and impactful arena of SG-related FCIA, the bespoke AWS-SOT-OCS construct should be meaningful, as its posits will have the tightest possible relaxations.