Enhancing the LEACH protocol and lightweight chaotic cryptography for secure data transmission in wireless sensor...

Area of Science:

• Computer Science
• Electrical Engineering
• Network Security

Background:

• Wireless sensor networks (WSNs) face critical challenges in energy efficiency, network longevity, and data security due to limited node resources and insecure communication channels.
• Existing WSN protocols often struggle to balance these competing demands, leading to premature network failure and data vulnerabilities.

Purpose of the Study:

• To develop an innovative hybrid framework for WSNs that optimizes cluster head selection and enhances communication security.
• To improve energy efficiency, extend network lifespan, and increase data throughput in resource-constrained WSN environments.

Main Methods:

• Integration of Wild Horse Optimization (WHO) and Giza Pyramids Construction (GPC) meta-heuristic algorithms for dynamic cluster optimization.
• Application of fuzzy logic (Mamdani inference) for intelligent cluster head (CH) selection based on residual energy, node proximity, and base station distance.
• Implementation of a novel chaos-based lightweight cryptography scheme with XOR iteration loops and chaotic shifts for secure data transmission.

Main Results:

• The proposed framework significantly extends network lifespan by 53.75% (vs. LEACH) and 14.73% (vs. GPC).
• Throughput is increased by approximately 2380 packets, an 18% improvement over Firefly Algorithm-based methods.
• Achieves high security with NPCR > 99.5% and entropy near 8 bits, while exhibiting 15% lower energy overhead compared to AES-based methods.

Conclusions:

• The hybrid framework provides a scalable, energy-efficient, and secure solution for WSNs.
• This approach substantially outperforms traditional WSN protocols in key performance metrics.
• The integration of meta-heuristic optimization and chaos-based cryptography offers a promising direction for future WSN research and development.