Cognitive Detection at Big-Data Scale: A CNN-LSTM-DQN Framework with Prioritized Experience Replay for Cross-Attack-Family Generalization and Multi-Seed Initialization Sensitivity Analysis
Real-world IoT network security generates traffic at big-data scale with extreme class imbalance, temporal non-stationarity, and continuously evolving attack strategies that overwhelm static supervised classifiers. This paper presents a cognitive computing framework for network intrusion detection: a CNN–LSTM–DQN archi...