Quick Navigation

Topics

Quantum Compilation Routing Architecture Quantum Cryptography Security Quantum Software Tools Programming Quantum Optimization

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

Crossref
Authors: Department of Computer Science, Tiruppur Kumaran College for Women, Tiruppur, TamilNadu, India, A Arivuselvi, C Kalaiselvi

Year

2025

Paper ID

11608

Status

Peer-reviewed

Abstract Read

~2 min

Abstract Words

277

Citations

0

Abstract

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

Why This Paper Matters

  • This paper contributes to the Quantum Software Tools & Programming research area in the Quantum Articles archive.
  • It adds a 2025 reference point for readers tracking recent quantum research.
  • 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...

Paper Tools

Become a member to use research tools

Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.

Publisher Share Cite This Paper Copy URL Compare Copy DOI Add to Reading List Category Correction Request

References & Citation Signals

Local Citation Graph (Related-Paper Links)

Current Paper #11608 #68466 Uncloneable Encryption from Dec... #68464 Hybrid Classical-Quantum Neural... #68455 Mediative Fuzzy Logic: From Typ...

External citation index: OpenAlex citation signal • updated 2026-06-11 17:06:02

Community Reactions

Quick sentiment from readers on this paper.

Score: 0
Likes: 0 Dislikes: 0

Sign in to react to this paper.

Discussion & Reviews (Moderated)

Average Rating: 0.0 / 5 (0 ratings)

No written reviews yet.