Qubit-efficient quantum intrusion detection using dual-parameter encoding and multi-metric calibration

Modern networks generate high-dimensional traffic that requires numerous features for effective intrusion detection and cybercrime defence, creating a critical challenge for quantum approaches, where qubit availability remains the primary bottleneck for near-term implementation. We present a quantum-enhanced framework that employs Dual-Parameter encoding, using both the polar angle θ and azimuthal phase ϕ of each qubit to encode two normalized features, combined with multi-metric anomaly scoring and calibrated false-positive control. Our detector forms a composite score [Formula: see text] that unifies quantum fidelity (global state similarity), Kullback-Leibler divergence (distributional shift), and von Neumann entropy change (uncertainty shift). The decision threshold is set by quantile calibration on benign validation, and via the Dvoretzky-Kiefer-Wolfowitz inequality, comes with an explicit finite-sample upper bound on the false-positive rate under i.i.d. assumptions. For a selected feature set of size [Formula: see text], our Dual-Parameter encoding reduces the data-qubit requirement from [Formula: see text] to [Formula: see text] at matched-feature count. This qubit reduction preserves the entangling topology but adds one additional single-qubit encoding rotation [Formula: see text] per data qubit and a Hadamard readout layer; when a SWAP-test ancilla is used, the total count becomes [Formula: see text]. We evaluate DP-QIDS on UNSW-NB15 and CIC-IDS2017 and reproduce the baseline's DDoS setting both at a richer selected feature count and under the baseline's standard 87→4 classical compression pipeline applied to both encoders, to ensure direct matched-setting comparisons at the encoder level. Ablations show that fidelity captures correlation-shifting attacks, while KL/entropy detects randomized marginals; their fusion yields consistently reliable operation. We further provide a complexity analysis, deployment architecture, and streaming variants with drift-aware recalibration. Our Dual-Parameter Quantum Intrusion Detection System (DP-QIDS) advances quantum intrusion detection from proof-of-concept toward auditable, resource-aware deployment, connecting simulator studies with practical security operations for resilient infrastructure.