The Police Complaint Management System (PCMS) is a decentralized application template designed to modernize the processes of lodging, tracking, and resolving complaints within law enforcement systems. Leveraging the Next.js framework, Web3 technologies, and blockchain integration, the system ensures tamper-proof complaint records, real-time updates, and enhanced transparency for citizens and authorities. By utilizing Wagmi and Ethers.js for seamless wallet connections, IPFS for decentralized evidence storage, and a user-friendly interface styled with Tailwind CSS, the PCMS provides a scalable, efficient, and accessible platform. With automated processes for complaint categorization and routing, as well as immutable blockchain records, the system fosters greater accountability and trust in public services. Built with TypeScript for reliability and enhanced with modular tools for rapid deployment, the PCMS exemplifies a modern, citizen-centric approach to grievance management, ensuring data security and operational efficiency in law enforcement agencies
Flash loan attacks threaten decentralized finance (DeFi) protocols, which constitute a Total Value Locked (TVL) of more than 106 billion. These attacks exploit the atomicity property in blockchains to drain funds within a single block. Existing research overlooks the mitigation of non-price flash loan attacks, which mostly exploit zero-day vulnerabilities. These attacks are challenging to detect as they are highly time-sensitive and each instance of the attack is complex and has a unique pattern. To address this challenge, we present FlashGuard, a runtime detection and mitigation framework for non-price flash loan attacks. FlashGuard communicates directly with the miners and bypasses the public mempool, where attack transactions usually reside. We utilize the temporary time window where transactions are visible in the mempool but not yet confirmed. Once the attack is detected, FlashGuard dispatches a dusting counter-transaction for the victim contract to the miners directly within the same block to disrupt the attack's atomicity and change the smart contract state. This forces the malicious transaction to revert. FlashGuard ensures that the series of operations that are required for a non-price flash loan attack cannot be completed atomically, leading to a failure of the attack. Our evaluation using 20 historical attacks that exploited protocol vulnerabilities shows an outstanding detection rate for FlashGuard with minimal false positives, and effective attack disruption and indicates that FlashGuard could have rescued about $405.71 million in losses.
Cong Wu, Jing Chen, Ziming Zhao, Kun He · 10 authors
Decentralized finance has experienced phenomenal growth, revolutionizing the landscape of financial transactions and asset management via blockchain. Yet, this swift growth brings with it substantial challenges, notably the surge in scam tokens, imposing significant security threats on cryptocurrency investments and trading. Existing detection methods of scam token, primarily relying on analyzing contract codes or transaction patterns, struggle to catch increasingly sophisticated tactics employed by scammers. For example, contract-based analysis are unable to identify scams lacking overt malicious code, e.g., most rugpulls, while transaction-based methods generally lack the foresight to early-detect potential risks.
Abstract The proliferation of cryptocurrencies has brought significant changes in the global economic market while introducing new risks to national security. This paper explores the economic transformations driven by the rise of digital currencies, analyzing their impact on traditional financial systems, monetary policy, and international trade. While cryptocurrencies offer opportunities for innovation and economic growth, they also pose substantial challenges for regulators, particularly in addressing illicit activities such as money laundering, terrorism financing, and tax evasion. Furthermore, the decentralized nature of these digital assets presents unique vulnerabilities for national security, as they can be used to avoid financial controls and sanctions. This paper aims to provide a comprehensive analysis of the economic benefits and security risks associated with cryptocurrencies, emphasizing the need for coordinated regulatory frameworks. By examining the intersection of technological innovation, economic impact, and security concerns, this research contributes to the ongoing debate on how to handle the main challenges brought by the growth of cryptocurrencies in a globalized, digital economy.
Maria JellâOjobor, Roland Russwurm, Josef Windsperger
ABSTRACT This study explores the implications of the introduction of blockchain technology for the governance of franchise networks. In light of the limited prior research on this topic, the study employs a twofold approach. It begins by identifying the central themes present in current research at the intersection of franchising and blockchain technology. Next, it examines existing instances of implementations of blockchain technology and connects them to corresponding value chain operations in the franchising context. The study takes a comprehensive approach, combining bibliometric analysis with a semisystematic literature review, to offer insights into blockchain technology's potential future impact on the franchise industry. Specifically, it shows that franchise network governance can benefit significantly from attributes of blockchain such as transparency, efficiency, and trust as well as from its various applications such as smart contracts and decentralized autonomous organizations.
Abstract Cryptocurrency remittances overcome many regulatory and practical barriers, but there is little empirical research into this increasingly popular remittance medium. In response, this article explores cryptocurrency remittances from Latin America and the Caribbean into Venezuela. Cryptocurrencies as a remittance medium conveys important messages for advocates and critics. To appropriately critique cryptocurrencies, it is important to understand how they are used in the âevery dayâ rather than how their use may be characterised by ideologues. Rather than directly relying on âtrustlessâ and decentralised blockchain technology, âreally existingâ cryptocurrency remittances are highly intermediated. Access to this medium is often hierarchical, stemming from knowledge barriers but also legal status (and by extension, economic status). The âneedâ for trusted intermediaries prompts discussions around the relationship between âtrustlessâ blockchain technology and cryptocurrency remittances. This article shows that stablecoins (cryptocurrencies pegged to fiat currenciesâusually the US dollar) are the most popular cryptocurrency remittance medium. Stablecoins challenge institutional attempts to geographically restrict currencies, yet also contribute to global processes of dollarisation. This is important to understanding how stablecoins simultaneously undermine spatial barriers to financial access yet may create new ones in the process.
In this paper, we analyze the global controversy surrounding the innovation of cryptocurrencies, developing an analytical framework to assess the empirical structure of arguments. By unpacking an argumentation analysis of a comprehensive set of scholarly, media, and industry publications, we identify six key dimensions of disagreement, comprising 42 distinct arguments. These dimensions include the raison dâĂȘtre, environmental impact, social inclusion, susceptibility to illegal activities, economic impact, and potential for decentralization and democratization. Our findings reveal entrenched positions supported by robust scholarly research and empirical evidence. Cryptocurrencies represent a controversial innovation, for which global resolution remains elusive. While the controversy may appear unbounded, we plead for a geographical approach, emphasizing that localized institutional contexts are crucial for exploring potential trajectories of the controversy. Finally, our analysis illustrates the potential of argumentation analysis to properly disentangle complex societal disagreements, and it therefore promises to enrich the methodological pluralism in economic geography.
In order to maintain the value of the national currency and control foreign debt, central banks are vital to the management of a nationâs foreign exchange reserves. These reserves, however, are vulnerable to a variety of hazards, including as money laundering, fraud, theft, and cyberattacks. These are issues that traditional financial systems frequently face because of their vulnerabilities and inefficiency. Using modern innovations in a blockchain-based solution can help tackle these serious issues. To protect data privacy, the Microsoft SEAL library is utilized for homomorphic encryption (FHE). For the development of smart contracts, Solidity is employed within the Ethereum blockchain ecosystem. Additionally, Amazon Web Services (AWS) is leveraged to provide a scalable and powerful infrastructure to support our solution. To guarantee safe and effective transaction validation, our method incorporates a hybrid consensus process that combines Proof of Authority (PoA) with Byzantine Fault Tolerance (BFT). The administration of foreign exchange reserves by central banks is made more secure, transparent, and operationally efficient by this all-inclusive approach.
Abstract This study examines the spillover of Bitcoin's jumps and diffusive variations to traditional assets using highâfrequency data. For our crossâasset analysis, we detect positive spillovers from Bitcoin to risk assets and negative spillovers to defensive assets. We also find evidence of positive jump and diffusion spillovers from Bitcoin to U.S. equity sectors, particularly the financials, technology, consumer discretionary, and communication services sectors. By examining the source of these risk transmissions, we show that these spillovers are exacerbated by increased economic exposures to blockchain and cryptocurrency technologies by U.S. companies. The empirical findings reveal that the price fluctuations of an unregulated asset such as Bitcoin can materially affect the price dynamics of regulated assets.
In this study, the author focuses on how cryptocurrency and blockchain technology can be used to improve delivery of international aid since traditional methods include problems such as corruption, inefficiency and lack of transparency. The main research question addresses the question of how cryptocurrency could enhance efficiency, enhance transparency, accountability, and fight corruption in the dispensation of aid. The authors performed a qualitative content analysis of data collected from multiple articles, reports, and case studies including World Food Programme and United Nations Children's Fund(UNICEF).The study shows that blockchainâs distributed digital ledger minimizes misappropriation of funds risk, maintains real-time tracking; cryptocurrencies, specifically stablecoins, are more effective in real and low-cost transactions. Nevertheless, the work also points to the threats evident in legal and regulatory frameworks, low levels of digital literacy, and technological constraints. In conclusion, if all the challenges are solved, the cryptocurrency will enable the complete redesign of the distribution of the funds for aid.
Purpose: This research explores how advanced digital strategies can be harnessed to combat cryptocurrency-enabled crimes, focusing on the use of blockchain analysis, artificial intelligence (AI), machine learning, and enhanced regulatory frameworks to detect, trace, and prevent illegal transactions on cryptocurrency platforms. Materials and Method: The study examines the challenges law enforcement and regulatory bodies face due to the pseudonymous nature of cryptocurrencies and their cross-border complexities. It analyses emerging digital tools that facilitate the de-anonymization of transactions and enable real-time monitoring of suspicious activities. Case studies from recent high-profile cryptocurrency crimes, such as the Silk Road shutdown and recent ransomware attacks, are utilized to highlight the effectiveness of these digital strategies. Findings: The findings indicate that a multi-layered approach, which combines technological innovations with global regulatory efforts, is essential for mitigating risks associated with cryptocurrency as a facilitator of cybercrime. Advanced analytics and regulatory techniques are identified as key resources for detecting and preventing illicit activities. Implications to Theory, Practice and Policy: The research demonstrates practical implications for law enforcement agencies in developing strategies that integrate advanced digital tools to improve their capabilities to manage and investigate cryptocurrency-related crimes. From a policy perspective, the study highlights the importance of creating adaptive regulatory frameworks that can evolve alongside cryptocurrency technology to effectively address the unique challenges it presents in combating cybercrime.
Cryptocurrency, a form of virtual currency, is increasingly pervasive in the modern society. People can use Bitcoin, Ether or Dogecoin to buy a range of products and services with ease and convenience. Yet, beneath the popularity of cryptocurrency is an emerging socio-legal concern: money laundering. Using the information collected from web sources, this brief paper taps into how cryptocurrency money laundering works and what measures can be undertaken to curtail digital crime. In view of the extant information, the paper found that a mixer is required as a âmiddle manâ to convert identifiable crypto-tokens into unidentifiable clean ones thereby delivering them to new wallet(s). In this manner, the origins of these tokens can be obscured, and the new tokens can be accessed and used legally. Many platforms and channels can serve as the mixer to proceed with illegal activities, including casinos, dark web marketplaces, and p2p networks. In considering the ways to tackle such digital crime in jurisdictions with limited oversight, the paper proposes to adopt measures in the Anti-Money Laundering initiatives already implemented in Hong Kong, the United States, and Singapore â especially, the need to strengthen recordkeeping to enhance the traceability and trackability of cryptocurrencies. Meanwhile, laws and rules associated with digital crime shall also be reshaped for risk mitigation.
Elections and voting play a crucial role in the development of a democratic society, enabling the public to express their views and participate in the decision-making process. Voting methods have evolved from paper ballot systems to e-voting systems to preserve the integrity of votes, ensuring a secure, transparent, and verifiable process. Continuous efforts have been made to develop a secure e-voting system that eliminates fraud attempts and provides accurate voting results. In this paper, we propose the architecture of a blockchain-based e-voting system called VoteChain. Developed to support the existing voting system in the state of Palestine, VoteChain aims to provide secure e-voting with features such as auditability, verifiability, accuracy, privacy, flexibility, transparency, mobility, availability, convenience, data integrity, and distribution of authority. The work introduces a smart contract designed to meet the demands of e-voting, governing transactions, monitoring computations, enforcing acceptable usage policies, and managing data usage after transmission. The proposed system also adopts advanced cryptographic techniques to enhance security. VoteChain features a web-based interface to facilitate user interaction, providing protection against multiple or double voting to ensure the integrity of the election. Furthermore, VoteChain is designed with a user-friendly and easily accessible administrator interface for managing voters, constituencies, and candidates. It ensures equal participation rights for all voters, fostering fair and healthy competition among candidates while preserving voter anonymity. A comparative analysis demonstrates VoteChainâs advancements in privacy, security, and scalability over both traditional and blockchain-based e-voting systems.
Smart contracts, self-executing agreements directly encoded in code, are fundamental to blockchain technology, especially in decentralized finance (DeFi) and Web3. However, the rise of Ponzi schemes in smart contracts poses significant risks, leading to substantial financial losses and eroding trust in blockchain systems. Existing detection methods, such as PonziGuard, depend on large amounts of labeled data and struggle to identify unseen Ponzi schemes, limiting their reliability and generalizability. In contrast, we introduce PonziSleuth, the first LLM-driven approach for detecting Ponzi smart contracts, which requires no labeled training data. PonziSleuth utilizes advanced language understanding capabilities of LLMs to analyze smart contract source code through a novel two-step zero-shot chain-of-thought prompting technique. Our extensive evaluation on benchmark datasets and real-world contracts demonstrates that PonziSleuth delivers comparable, and often superior, performance without the extensive data requirements, achieving a balanced detection accuracy of 96.06% with GPT-3.5-turbo, 93.91% with LLAMA3, and 94.27% with Mistral. In real-world detection, PonziSleuth successfully identified 15 new Ponzi schemes from 4,597 contracts verified by Etherscan in March 2024, with a false negative rate of 0% and a false positive rate of 0.29%. These results highlight PonziSleuth's capability to detect diverse and novel Ponzi schemes, marking a significant advancement in leveraging LLMs for enhancing blockchain security and mitigating financial scams.
Ensuring the absence of vulnerabilities or flaws in smart contracts before their deployment is crucial for the smooth progress of subsequent work. Existing detection methods heavily rely on expert rules, resulting in low robustness and accuracy. Therefore, we propose EDSCVD, an enhanced deep learning vulnerability detection model based on dual-channel networks. Firstly, the contract fragments are preprocessed by BERT into the required word embeddings. Next, we utilized adversarial training FGM to the word embeddings to generate perturbations, thereby producing symmetric adversarial samples and enhancing the robustness of the model. Then, the dual-channel model combining BiLSTM and CNN is utilized for feature training to obtain more comprehensive and symmetric information on temporal and local contract features.Finally, the combined output features are passed through a classifier to classify and detect contract vulnerabilities. Experimental results show that our EDSCVD exhibits excellent detection performance in the detection of classical reentrancy vulnerabilities, timestamp dependencies, and integer overflow vulnerabilities.
This study examines the legal challenges associated with the commercialization of non-fungible tokens (NFTs) in Europe and Brazil. This paper provides a comprehensive analysis of the European and Brazilian legal frameworks, identifying key legal challenges related to intellectual property rights, consumer protection, taxation, and anti-money laundering (AML) regulations. Through a comparative analysis, we highlight the similarities and differences between the two jurisdictions, as well as best practices for addressing these legal challenges. The paper also discusses recent developments and court decisions, demonstrating the evolving legal landscape for NFTs in both regions. The findings of this paper have significant implications for the future of NFTs in Europe and Brazil, as well as for the broader digital economy, and offer valuable insights for policymakers, legal professionals, and market participants. Additionally, the paper identifies areas for further research, including the impact of technological advancements, the role of smart contracts, cross-jurisdictional issues, and the relationship between NFTs and traditional intellectual property rights.
Marco Ortu, Giacomo Ibba, Giuseppe Destefanis, Claudio Conversano · 5 authors
The expansion of smart contracts on the Ethereum blockchain has created a diverse ecosystem of decentralized applications. This growth, however, poses challenges in classifying and securing these contracts. Existing research often separately addresses either classification or vulnerability detection, without a comprehensive analysis of how contract types are related to security risks. Our study addresses this gap by developing a taxonomy of smart contracts and examining the potential vulnerabilities associated with each category. We use the Latent Dirichlet Allocation (LDA) model to analyze a dataset of over 100,040 Ethereum smart contracts, which is notably larger than those used in previous studies. Our analysis categorizes these contracts into eleven groups, with five primary categories: Notary, Token, Game, Financial, and Blockchain interaction. This categorization sheds light on the various functions and applications of smart contracts in today's blockchain environment. In response to the growing need for better security in smart contract development, we also investigate the link between these categories and common vulnerabilities. Our results identify specific vulnerabilities associated with different contract types, providing valuable insights for developers and auditors. This relationship between contract categories and vulnerabilities is a new contribution to the field, as it has not been thoroughly explored in previous research. Our findings offer a detailed taxonomy of smart contracts and practical recommendations for enhancing security. By understanding how contract categories correlate with vulnerabilities, developers can implement more effective security measures, and auditors can better prioritize their reviews. This study advances both academic knowledge of smart contracts and practical strategies for securing decentralized applications on the Ethereum platform.
In 2021, President Nayib Bukele introduced Bitcoin as legal tender in El Salvador. This paper examines the relationship between right-wing populism and Bitcoin. Through textual and visual analyses, the paper shows how Bukele weaves the promises and techno-utopian ideology surrounding Bitcoin into classic populist narratives. Adopting Bitcoin adds the promise of technology-driven development and the realization of a techno-utopia to the populist narrative template, allowing Bukele to construct a populist myth of himself as a tech-savvy visionary. This brand of crypto-populism represents a novel addition to the right-wing populist repertoire, capitalizing on the promises of an ongoing digital revolution.
The objective of this research is to determine the impact of geopolitical developments on Bitcoin's value. It focuses on the events that occurred from October 7, 2023 including the attack on Israel by the militant group Hamas, the tension between Iran and Israel, and the conflict between Palestine and the US. Through a comprehensive event study, we can analyze the returns generated by these events. The results of the study Srevealed that Bitcoin performed well during the adjustment and anticipation periods, which showed that it could be a safe-haven asset. On the other hand, the negative AAR during the event day reflected the market's first reaction. The study also highlighted Bitcoin's dual nature as a speculative asset and a safe-haven asset providing investors with a deeper understanding of the risks that affect the cryptocurrency market.
Cedrick Agorbia-Atta, Imande Atalor, Rita Korkor Agyei, Richard Nachinaba
This study addresses the critical issue of terrorist financing through cryptocurrency platforms, a growing concern due to digital currencies' pseudonymous nature and global reach. The research explores the strategic role of Artificial Intelligence (AI) and Machine Learning (ML) in identifying, preventing, and disrupting the flow of illicit funds used to finance terrorism. Employing a mixed-methods approach, the study integrates qualitative case studies of documented instances of cryptocurrency-based terrorist financing with quantitative data analysis from significant cryptocurrency exchanges. Advanced AI and ML algorithms, including supervised learning models such as decision trees and neural networks, were applied to detect suspicious transactions indicative of terrorist activities. The findings reveal that AI and ML technologies significantly enhance the ability to identify patterns of terrorist financing within large and complex datasets, with models achieving precision and recall rates exceeding 90%. However, challenges remain, particularly regarding the quality and standardization of data across platforms, algorithmic biases, and the need for continuous updates to counter evolving tactics used by terrorist organizations. The study concludes that AI and ML present powerful tools for enhancing financial security. However, their successful implementation requires overcoming these challenges through collaborative efforts among stakeholders, including financial institutions, regulators, and technology providers. This research contributes to the growing field of economic crime prevention by offering a robust framework for integrating AI-driven solutions into the fight against terrorist financing on cryptocurrency platforms.
We examine cryptocurrency fraud cases prosecuted by Nigeria's Economic and Financial Crimes Commission (EFCC). We considered the lens of the Space Transition Theory (STT) in exploring the dynamics of these digital crimes. Our data analysis reveals common types of fraud, including cryptocurrency investment schemes. The results show an exclusive male demographic (100%), with the majority under 30 years old and only a quarter possessing a degree, providing insights into the socio-demographic characteristics of cryptocurrency fraudsters. Additionally, while most fraudsters (55%) targeted victims in the United States, Bitcoin, leveraging blockchain technology, was the most commonly used method (46%) for cryptocurrency fraud. Our examination of the methods and mediums used for cryptocurrency fraud supports some aspects of STT, while others do not. We advocate for a multifaceted strategy that prioritises stringent regulation, implementation, and heightened scrutiny of digital currency ecosystems in Nigeria and beyond. This study contributes to the broader discourse on cybercrime prevention and enforcement by emphasising the novel methodological approach utilised.
Eduardo Augusto de Medeiros Silva, Ivan da Silva Sendin
Selfish Mining is an attack on the proof-of-work-based cryptocurrency consensus mechanism, enabling attackers to gain more than their fair share of rewards. Its existence indicates that the Nakamoto consensus is not incentive compatible and could jeopardize blockchain security. Recently, a method employing the Z-Score to detect selfish mining was proposed. This paper introduces a non-parametric statistical technique to identify traces of selfish miners on the blockchain without assuming any specific statistical distribution for the analyzed data. Additionally, the applicability of this type of analysis is discussed.
Hany F. Atlam, Ndifon Ekuri, Muhammad Ajmal Azad, Harjinder Singh Lallie
Blockchain technology has gained significant attention in recent years for its potential to revolutionize various sectors, including finance, supply chain management, and digital forensics. While blockchainâs decentralization enhances security, it complicates the identification and tracking of illegal activities, making it challenging to link blockchain addresses to real-world identities. Also, although immutability protects against tampering, it introduces challenges for forensic investigations as it prevents the modification or deletion of evidence, even if it is fraudulent. Hence, this paper provides a systematic literature review and examination of state-of-the-art studies in blockchain forensics to offer a comprehensive understanding of the topic. This paper provides a comprehensive investigation of the fundamental principles of blockchain forensics, exploring various techniques and applications for conducting digital forensic investigations in blockchain. Based on the selected search strategy, 46 articles (out of 672) were chosen for closer examination. The contributions of these articles were discussed and summarized, highlighting their strengths and limitations. This paper examines the selected papers to identify diverse digital forensic frameworks and methodologies used in blockchain forensics, as well as how blockchain-based forensic solutions have enhanced forensic investigations. In addition, this paper discusses the common applications of blockchain-based forensic frameworks and examines the associated legal and regulatory challenges encountered in conducting a forensic investigation within blockchain systems. Open issues and future research directions of blockchain forensics were also discussed. This paper provides significant value for researchers, digital forensic practitioners, and investigators by providing a comprehensive and up-to-date review of existing research and identifying key challenges and opportunities related to blockchain forensics.