Abstract

We model cryptographic auditing of off-chain data as a Constrained MDP (CMDP) under partial observability : the storage nodes hidden type and corruption state make the problem a POMDP, while a miss-rate ceiling imposes an explicit security constraint. We propose DRQN-CMDP , a Deep Recurrent Q-Network whose GRU layer maintains a belief over the latent node type, paired with Lagrangian dual ascent that adapts the miss-rate penalty automatically. A pairing-free homomorphic-MAC primitive supplies O (1) on-chain verification cost. Across 13 methods—four DQN variants, PPO, A2C, PPO-Lagrangian, a stateful Bayesian heuristic, three fixed-rule baselines, and an oracle-informed heuristic—DRQN-CMDP achieves a favourable balance: 83% lower gas than fixed high-frequency auditing, single-digit miss rate (7.5%), and moderate detection latency—a combination no other method matches across all three objectives simultaneously.