Hybrid Secure Routing Mechanisms Combining Graph Learning and Lightweight Encryption for Mobile Networks

Abstract

Mobile networks and Mobile Ad Hoc Networks (MANETs) have become essential communication infrastructures for intelligent transportation systems, military operations, healthcare monitoring, disaster recovery, Internet of Things (IoT) environments, and next-generation wireless communication systems due to their decentralized, dynamic, and infrastructure-less communication capability. However, the open wireless communication medium, node mobility, routing instability, limited computational resources, and absence of centralized administration expose mobile networks to severe security threats such as black hole attacks, packet interception, routing manipulation, spoofing, and malicious node infiltration. Traditional routing protocols and conventional cryptographic security mechanisms often suffer from high computational overhead, excessive communication latency, energy inefficiency, and limited adaptability to dynamic attack patterns within highly mobile wireless environments. To address these challenges, this research proposes Hybrid Secure Routing Mechanisms Combining Graph Learning and Lightweight Encryption for Mobile Networks that integrate graph-based communication intelligence, lightweight cryptographic protection, adaptive trust-aware routing, anomaly detection, and intelligent route optimization into a unified secure communication framework.