Bio-Inspired Multi-Layer Quantum Swarm Immunization (QSI-Fusion) for Secure and Trust-Aware Routing in Wireless Sensor Networks

Objectives: To propose a novel bio-inspired self-healing Quantum Swarm Immunization (QSI) and intelligent optimization protocol for holistic security and trust-aware routing in multi-layered WSNs. The model also intends to improve energy efficiency, defense against malicious node behavior, minimizes packet loss and transmission delay. The proposed QSI-Fusion model integrates quantum superposition and Immune-Inspired Methods: Adaptive Selection (IISS) with swarm intelligence to achieve optimal and trust-aware routing. QSI-Fusion works with a three-layer hybrid architecture: i) Quantum Behavioral Layer (QBL) for anomaly detection, ii) Immunized Trust Layer (ITL) for adaptive selection, and iii) Secure Swarm Routing Layer (SSRL), which enables energy-efficient and attack-resilient connections between source and destination. This multi-layer quantum swarm optimization process dynamically adjusts the learning parameters, including a) trust threshold, b) node selection, and c) energy-aware transmission weights, to enhance performance. NS-3 is used to evaluate the performance under variable node densities and attack scenarios. The results are compared with existing energy-efficient and trust-aware bio-inspired models such as MC-CRITIC, Bio-Inspired Models (PSO, ACO, BO, WO, FCM, AC), WQALO, and QEBSO. NSL-KDD & DS2OS IoT datasets are used for validation to ensure generalization under heterogeneous WSN-IoT environments. Findings: The proposed QSI-Fusion achieves promising results compared to existing models, attaining a 98.4% Fault Detection Rate (FDR), 98.6% Accuracy (AC), 97.9% Energy Efficiency (EE), a reduced delay of 0.021 s, and 96.5% Intrusion Resistance (IR). The execution time is reduced to 27%. Novelty: A unified integration of quantum intelligence, immunological learning, and bio-inspired swarm forms a multi-layer security ecosystem that helps to secure data in complex WSN environments. The proposed model establishes an energy-efficient, trust-aware, and self-adaptive WSN system suitable for next-generation applications. Keywords: Wireless Sensor Networks, Quantum Swarm Search, QSI-Fusion, Trust Aware Routing, Swarm Intelligence