Most existing systems have sufficient data integrity but lack appropriate communication and decision-making methods that allow for timely responses to change. This paper discusses the use of a blockchain-based design as a method for overcoming these limitations by utilizing secure communication protocols and smart evidence management to support electronic evidence. An architecture based on multi-layers is constructed on top of blockchain, cryptographic encoding, hybrid storage (blockchain + IPFS) and a reinforcement learning-based adaptive component. The system is experimentally tested on both simulated and real-world digital evidence sets in different network loads, and attack conditions. The use of metrics like integrity accuracy, communication reliability, latency and scalability is used to measure performance. The proposed framework has high integrity preservation (>99%), enhanced the reliability of communications, and less latency as compared to baseline systems. The hybrid architecture can be used successfully to reduce the storage overheads.
Divyanshu Sinha, Hastimal Jangid, G. Radha Krishna Murthy et al.· Advances in wireless technol...· 0 citations
As the world of smart, connected public safety networks expands in scale and sophistication, it is increasingly susceptible to attacks combining cyber and physical capabilities. The chapter suggests a novel framework for threat detection based on AI, which involves the fusion of multimodal intelligence, graph neural reasoning, transformer-based contextual learning, reinforcement learning for adaptive threat mitigation, and zero-trust behavioral security mechanisms. The envisioned architecture is based on decentralized edge-assisted analytics, which provides real-time threat monitoring in low-latency environments in heterogeneous public safety applications. The large-scale simulated smart city infrastructures with multimodal surveillance, communication and IoT traffic datasets were used in the experimental evaluation under dynamic attack conditions. The framework successfully managed to detect the attacks with 98.74% accuracy while also maintaining low false alarm rates and tolerating adversarial perturbations and high-density network conditions.
Hastimal Jangid, Vandana Pushe, M. Vijayasanthi et al.· Advances in wireless technol...· 0 citations
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