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 \(\theta\) and azimuthal phase \(\phi\) 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 \(\begin{array}{c}S\left(x\right)={w}_{1}(1-F)+{w}_{2}{{D}\scriptscriptstyle_{{KL}}}+{w}_{3}\varDelta{S}_{v\scriptscriptstyle N}\end{array}\) 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 \({N}_{sel}\) , our Dual-Parameter encoding reduces the data-qubit requirement from \({N}_{sel}\) to \(\left\lceil {N_{{sel}} /2} \right\rceil\) at matched-feature count. This qubit reduction preserves the entangling topology but adds one additional single-qubit encoding rotation \(R_{z}\) per data qubit and a Hadamard readout layer; when a SWAP-test ancilla is used, the total count becomes \(\left\lceil {N_{{sel}} /2} \right\rceil+1\) . 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.
