Cryptocurrency KOL communities exhibit a paradoxical trust dynamic: pseudonymous strangers coordinate substantial capital within days, yet the same communities collapse once monetization, dissent suppression, and power concentration escalate. We develop the Crypto Community Trust Dynamics Chain (CCTDC), a six-phase recursive process model theorizing how platform affordances compress tri-dimensional emotional resonance (cognitive, affective, identity) into ephemeral trust, how exploitation unfolds along a five-level gradient, and how fission diverges into resonance maintenance, reform advocacy, or awakened departure. The model distinguishes ephemeral from swift trust, operationalizes identity resonance and narrative capacity, and treats the boundary condition as endogenously coupled.
Blockchain technology is frequently characterized as inherently transparent and tamper-resistant, suggesting strong potential for improving auditability and integrity in cryptocurrency fraud investigations. However, practical forensic outcomes often fall short of these expectations due to regulatory fragmentation, anonymity-enhancing mechanisms, decentralized infrastructures, and limitations in audit and investigative tooling. This study develops a structured conceptual framework to explain the gap between blockchain’s theoretical transparency and real-world forensic accounting capability. Synthesizing 70 relevant studies from an initial pool of 279 published manuscript, the paper organizes cryptocurrency forensic constraints into macro-level barriers and operationalizes them through twenty literature-derived critical factors. We further develop a temporal framework that distinguishes persistent constraints from emergent challenges, demonstrating how investigative bottlenecks evolve as cryptocurrency ecosystems mature. By linking barriers and operational factors to forensic accounting capability and investigative outcomes, the study provides an integrated and time-sensitive foundation for future empirical validation and capability development in decentralized financial environments.
Through this independent concept, the study introduces a fresh new perspective to the world of modern forensic accounting via a theory called “The Decentralized Fraud Matrix” (DFM). This conceptual research was developed specifically as an analytical tool to dissect the modus operandi of financial crimes in the digital-cyber era—including Web3 environments, blockchain architecture, DeFi protocols, and autonomous DAO systems. The focus of the DFM theory completely breaks away from the basic assumptions of the conventional fraud triangle, which has long been overly preoccupied with measuring human emotions. Mechanically, the originality of this theory rests on the testing of three interlocking cyber indicators in the field. These three indicators include the level of opacity in an actor’s digital identity concealment; technological engineering designed to break the audit trail of fund flows; and the exploitation of loopholes in physical national sovereignty boundaries, as well as cyber “jurisdictional evasion” tactics aimed at neutralizing the enforcement power of on-ground regulations, thereby rendering perpetrators immune to formal legal prosecution
Ovaj rad analizira transformativnu ulogu kriptovaluta u infrastrukturi savremenog organizovanog kriminala, argumentujući da blockchain tehnologija nije samo novi alat za stare kriminalne prakse, već da konstituiše kvalitativno novu kriminalnu ekonomsku arhitekturu koja mijenja temeljne odnose između kriminalnih aktera, žrtava i institucija. Kroz sistematsku analizu tehničkih mehanizama od Bitcoin pseudoanonimnosti i privacy coins, do DeFi protokola i cross-chain hopping tehnika, rad mapira evoluciju kriptovalutnog pranja novca od primitivnih jednokratnih transakcija prema sofisticiranim, višeslojnim operacijama koje kombinuju tehnološku sofisticiranost s institucionalnim ranjivostima globalnog regulatornog mozaika. Posebna analitička pažnja posvećena je slučajevima koji demonstriraju konvergenciju kriptokriminala s državnom strategijom, tj. ransomware koji funkcionišu kao paraziti na globalnoj digitalnoj ekonomiji, DeFi eksploatacijama koje u minutama dreniraju stotine miliona dolara, i sjevernokorejskim državno-sponzorisanim hakerskim operacijama koje finansiraju zabranjene oružane programe pod sankcijama. Rad evaluira regulatorne odgovore poput MiCA, FATF Travel Rule i OFAC sankcije, te identifikuje sistemske praznine koje ostavljaju DeFi i peer-to-peer sistem izvan efektivne regulatorne kontrole. Zaključak poziva na fundamentalnu promjenu paradigme regulatornog pristupa, i to od retrospektivne forenzike prema prospektivnoj arhitekturi transparentnosti koja mora biti ugrađena u same protokole.
Abstract - The rise of digital technology has led to an increase in cybercrime. This has made the management of digital forensic evidence more complicated. Traditional evidence management systems utilize manual methods and centralized databases. Methods like these are vulnerable to data tampering, unauthorized access, and human error. These issues threaten the integrity of the evidence and the chain of custody during the investigation process. In this paper, we introduce a system that utilizes blockchain technology, smart contracts, and a decentralized system for the tracking of forensic evidence. Security and transparency will be guaranteed. In our system, evidence records are stored as ERC-721 Non-Fungible Tokens. A private Ethereum blockchain was developed using Ganache and combined with wallet-based authentication and Role-Based Access Control to ensure that only authorized personnel have the ability to view and manage evidence. Smart contracts facilitate the registration, verification, transfer, and auditing of evidence, thus, considerably reducing the manual work and greatly increasing the trustworthiness of the system. We proposed a hybrid system of storage whereby evidence and its forensic files are stored off chain, and the evidence metadata and its forensic files are stored on chain. This paper presents the design and architecture of the system,implementation and evaluation are in progress.Our system will be a trusted, efficient, and effective system of evidence management.
The rapid digitalization of financial services has transformed the global financial ecosystem, enabling faster transactions, enhanced customer experiences, and greater financial inclusion. However, this digital transformation has simultaneously increased the complexity, scale, and sophistication of financial fraud. Traditional rule-based fraud detection systems often struggle to identify evolving fraud patterns, resulting in delayed responses, increased false positives, and substantial financial losses. Artificial Intelligence (AI)-powered real-time fraud monitoring systems have emerged as a transformative solution capable of detecting suspicious activities instantly through advanced data analytics, machine learning, deep learning, natural language processing, and behavioral intelligence. These systems continuously analyze vast volumes of transactional and non-transactional data, enabling financial institutions to identify anomalies, predict fraudulent behavior, and automate risk management processes with unprecedented accuracy and speed. This literature review examines the evolution, applications, technological foundations, benefits, challenges, and future directions of AI-powered real-time fraud monitoring systems in modern financial services. The review highlights how AI enhances fraud detection capabilities across banking, payment systems, insurance, digital wallets, cryptocurrencies, and investment platforms while discussing critical concerns related to privacy, algorithmic bias, explainability, cybersecurity, and regulatory compliance. The findings demonstrate that AI-driven fraud monitoring represents a fundamental component of modern financial security infrastructure and will continue to shape the future of fraud prevention in increasingly digital financial environments.
The widespread problem of cyberbullying in today’s digital environment is made worse by the quick spread of IoT devices and the difficulties in organizing and protecting digital evidence. Traditional forensic methods are often inadequate due to their inability to provide a tamper-proof chain-of-custody and their limited scalability under high data loads. To overcome these constraints, our work makes use of innovative technologies such as a permissioned blockchain (Hyperledger Fabric), powerful encryption methods (AES-256 and RSA), and decentralized off-chain storage (IPFS). We propose an integrated, blockchain-driven forensic evidence collection framework that ensures secure, real-time evidence acquisition from diverse IoT devices, automated validation via smart contracts, and efficient, Role-Based Access Control for evidence retrieval. A hybrid consensus mechanism, combining elements of PBFT and Proof-of-Stake, enhances the system’s security and scalability while reducing processing latency and energy consumption. Experimental results demonstrate that our approach achieves high throughput and low latency, making it a strong and reliable solution for forensic investigations in cyberbullying cases. Within our experimental scope, the framework strengthens the integrity and authenticity of digital evidence and addresses key regulatory considerations, though real-world validation remains future work.