QKD Eve Detector: A Research Collection on Eavesdropper Detection in Quantum Key Distribution

This collection presents three interconnected papers on eavesdropper (Eve) detection in Quantum Key Distribution (QKD) channels, following the chronological development of the framework. Part I Eve Detection in QKD via Dual-Layer Sidereal Filtering and Krylov Complexity Analysis (v4): The empirical starting point. Eve is modeled as a Hamiltonian perturbation at the kappa-coupling interface. Krylov-Statistical Mapping establishes a correlation between bₙ deviation and QBER statistical moments (r=0. 948, kurtosis; r=0. 943, |skewness|) across 50 gamma values. Crossover spectral regime (⟨r⟩=0. 366) explicitly documented. Part II: Distinguishing Quantum Scrambling from Eavesdropping via Krylov Temporal Structure and Sidereal Filtering (v2, with Robustness Analysis): The theoretical foundation. A Gaussian autocorrelation template C (t) = exp (−0. 5· (slope·t) ²) is derived from Krylov-Lanczos bₙ coefficients. Under realistic hardware noise (AR (1) + 1/f + afterpulsing + bursts): AUC=0. 9899, separation=12. 13 sigma. Three methodological killer tests included. All results are simulation-based (N=8 crossover regime; not yet validated on real QKD hardware). Part III: QKD Eve Detector: A Unified Framework (Synthesis): The three-layer detector combining all prior work: (1) Dual-Layer Sidereal Filter for environmental noise removal, (2) Krylov Dynamic Detector for template matching, (3) Multi-Vector Attack Classifier distinguishing six attack types. Self-contained implementation provided in the accompanying demo notebook. Accompanying notebooks reproduce all figures and results. Dependencies: NumPy, SciPy, QuTiP. No special hardware required.