Evidence plays a crucial role in judicial systems, and managing it securely and efficiently ensures justice. This paper introduces Decentralized Trust, a framework that combines blockchain technology, Non-Fungible Tokens (NFTs), and fog computing to address common issues like tampering, delays, and reliance on centralized systems. Traditional methods that depend on cloud computing often face high latency and slow processing, especially in remote areas. This research also builds upon the challenges identified in previous studies, such as tampering vulnerabilities, inefficiencies in evidence processing, and accessibility issues in underserved regions, providing a novel and comprehensive solution through Decentralized Trust. Fog computing handles tasks closer to where data is created, reducing delays and improving response times. Blockchain ensures that evidence records cannot be altered, while NFTs make each piece of evidence unique and tamper-proof. The framework is organized into layers: edge nodes at police stations capture evidence, fog nodes process the data and create NFTs, and cloud storage, supported by the Interplanetary File System (IPFS), provides secure long-term storage. Results demonstrate that the framework achieves average transaction delays of 24.5 seconds on low-performance devices (Node A) and 168.9 seconds on high-performance devices (Node B), with margins of error showing efficient scalability even under significant processing loads. The observed transaction delays are due to differences in system architecture and processing priorities. High-performance devices (Node B) have more complex validation processes, increased security checks, or resource contention, contributing to longer transaction times. By combining these technologies, Decentralized Trust offers a reliable, fast, and secure way to manage judicial evidence, building trust in the framework while addressing the needs of remote and underserved areas.

Blockchain networks often face isolation and scalability challenges, particularly when interacting across heterogeneous consensus protocols. This paper introduces Proof of Repute Consensus (PoRC), a decentralized framework designed to facilitate secure and trustless cross-chain interoperability without reliance on third-party bridges. PoRC employs a behavior-driven reputation model, where nodes must maintain a minimum Reputation Score to participate in block proposals. A randomly selected committee of auditors continuously evaluates node behavior using verifiable random selection, enabling accountability without economic collateral. The proposed two-tier architecture decouples intra-chain consensus (Tier-1) from inter-chain collaboration (Tier-2), allowing heterogeneous blockchains to coordinate state updates while preserving their native consensus mechanisms. A comprehensive security framework supported by stochastic modeling is employed to analyze resistance against double-spending, Sybil attacks, and collusion. Experimental evaluation demonstrates that the PoRC interoperability layer sustains an aggregate throughput of up to 8,000 transactions per second across parallel clusters, with an average cross-chain finality of approximately 11 seconds under controlled conditions. These results indicate that PoRC provides a viable architectural foundation for scalable and behavior-driven blockchain interoperability.

Digital Identity Management system is important component of security infrastructure for internet applications. However, existing digital identity management systems encounter various challenges, including difficulties in cross-domain authentication and interoperation, lack of credibility in identity authentication, and vulnerabilities in the security of identity data. Despite the attention blockchain technology has garnered in the field of digital identity management and the development of blockchain-based systems, these systems have not fully resolved the aforementioned problems. To address these issues and establish a secure and trustworthy digital identity management system, this paper proposes an effective model that integrates self-sovereign identity, oracle technology, and blockchain. This model aims to provide solutions and lay the groundwork for overcoming the challenges and ensuring the construction of a secure and reliable digital identity management system.

A vehicle can be tracked through its locatable transmission. The broadcast by a source contains its current identity and also allows estimation of its location by a receiver. This possibility of mapping between the physical entity and the estimated location through the communication broadcast is a threat to privacy. The changes in the location due to motion and the alteration in the temporal identifiers diminish the correlation between location and physical entity. However, such a mapping can still be recognized when an actively communicating node in relative isolation is observed for a sufficient interval of time. This paper addresses the challenges in providing anonymity to a moving vehicle that continually switches identifiers. As a vehicle moves on a road, its neighbors change in accordance to its relative speed with neighboring vehicles. This change in the nature and size of the neighborhood, i.e. the entropy, the degree of the anonymity of a vehicle. It is shown that the effective entropy reduces drastically due to change in the neighbors and transmissions by vehicles. The work studies the possibility that a node may retain its anonymity by switching identities in the vicinity of other vehicles to decorrelate its location and identity relation. A heuristic that allows a vehicle to switch its identity at a time and place where the potential of anonymity preservation can be maximized by increasing the entropy is proposed. The performance of the proposed heuristic is evaluated in a highway environment with vehicle mobility and dynamic vehicle population. Simulation results indicate that updating pseudonyms in accordance to the heuristic maximizes the entropy and through it, the anonymity of a vehicle.