Blind Watchdog Protocol: Anonymous Mutual Oversight for Autonomous Multi-Agent Systems

The Blind Watchdog Protocol (BWP) constructs a directed oversight graph where each autonomous agent has exactly one hidden watchdog, but no agent knows who watches it. Compliance emerges through a Panopticon equilibrium — the mere possibility of observation makes defection irrational. A closed-form Nash equilibrium theorem (6-step proof, TLC model-checked: 2,071 states, zero violations) establishes that compliance is strictly dominant under configurable parameters. The protocol implements 10 composable plugins (reputation, staking, mixnet, rotation, correlation analysis, adaptive watcher allocation, conviction scoring, knowledge gating, hybrid oversight, and optimistic slashing) and maps 10 biological oversight mechanisms to executable code. Key results: 100% detection rate with 0% false positives across 1,000 deterministic simulation runs (p_d=1.0). Stress-tested with stochastic observation noise, collusion sweeps (10-40%), Dark DAO bribery economics, and latency profiling. Layered defense separates immediate containment (escalation levels 1-3) from delayed adjudication (optimistic slashing with challenge period). Three-tier Sybil resistance via admission staking, DID-based identity, and Proof-of-Personhood interface. Constant-rate dummy traffic for timing-analysis resistance. Standardized evidence protocol for dispute resolution. Dynamic VaR-coupled stakes for high-value environments. Three fundamental open problems are identified: out-of-band cryptographic bribery (Dark DAOs), the recursive final arbitrator problem, and the latency-anonymity-cost trilemma for LLM agents. The reference implementation (422 tests, 5,757+ LOC, Python) is licensed under PolyForm Noncommercial 1.0. This paper is a defensive publication of the protocol design, formal proofs, and empirical results.