Scaling aligned AI from single-agent systems to multi-agent ecosystems introduces collective failures that do not arise in isolation: coalition deviation, governance capture, and rushed rule changes. Prior work in VAST and VAST-Blockchain addresses single-agent compliance and deployment integrity, but not strategic coordination across multiple agents. We introduce COALITION-VAST, a framework for multi-agent alignment with auditable governance under Byzantine validators and Sybil governance attempts. COALITION-VAST models coordination as a coalition game coupled with on-chain rule evolution, keeps agents bound to locked machine-checkable constraints, and adds trust-driven targeted auditing so detection becomes an adaptive outcome rather than a fixed assumption. We derive conditions under which adaptive detection and enforceable penalties make profitable coalition deviation unattractive, and we show that with BFT consensus and supermajority rule updates, Byzantine validators alone cannot finalize unauthorized constraint changes. A prototype simulation across healthcare resource allocation, autonomous swarms, and multi-stakeholder finance shows improved alignment (mean 0.90 vs. 0.69; +30% relative), a 98% reduction in undetected coalition deviation, and modest latency (2.8-3.4 s per coordinated decision). We also present an evolutionary analysis showing that compliance remains stable when expected audit penalty exceeds deviation gain, and we introduce a governance gate for highstakes updates based on evidence commitment, delay, and independent review.
Soraya Partow, Satyaki Nan· 2026 International Conferenc...· 0 citations
Hardware Trojans are malicious circuit modifications that can be covertly inserted during the design or fabrication of integrated circuits, enabling leakage, performance degradation, or mission failure after deployment. Because exhaustive testing against all Trojan classes and activation behaviors are prohibitively expensive, effective defense requires reasoning about the strategic interaction between an IC buyer/tester and a potentially malicious manufacturer. In this paper, we model Hardware Trojan insertion and testing as a two-player zero-sum security game with multi-level attacker and defender intensities. We first derive the Mixed-Strategy Nash Equilibrium (MSNE) under classical expected-utility assumptions and identify parameter regimes in which the game reduces to a smaller equilibrium over the remaining dominant strategies. Recognizing that real decision-makers exhibit bounded rationality, loss aversion, and distorted probability perceptionespecially under low-probability, high-impact threats-we then incorporate Prospect Theory to obtain a ProspectTheoretic MSNE (PT-MSNE) formulation. The resulting equilibrium conditions are nonlinear and are computed numerically under simplex constraints. Extensive simulations quantify how behavioral parameters reshape equilibrium mixing, shift the security-cost tradeoff, and alter defensive investment relative to the rational benchmark, providing actionable insights for designing robust and cost-effective Trojan testing policies under uncertainty and human bias.
Soraya Partow, Satyaki Nan· 2026 International Conferenc...· 0 citations
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