William J. Buchanan, Jamie Gilchrist, Keir Finlow-Bates
The ECDSA (Elliptic Curve Digital Signature Algorithm) is used in many blockchain networks for digital signatures. This includes the Bitcoin and the Ethereum blockchains. While it has good performance levels and as strong current security, it should be handled with care. This care typically relates to the usage of the nonce value which is used to create the signature. This paper outlines the methods that can be used to break ECDSA signatures, including revealed nonces, weak nonce choice, nonce reuse, two keys and shared nonces, and fault attack.
The rapid advancement of quantum computing presents a fundamental challenge to modern cryptographic security, particularly in the domain of hash functions that ensure data integrity, authentication, and blockchain security. Traditional crypto graphic hash functions such as SHA-256, SHA-3, and BLAKE2 rely on computational hardness assumptions that become obsolete in the presence of large-scale quantum computers. Shor’s algorithm can efficiently break RSA and ECC-based cryptosys tems, while Grover’s algorithm reduces the security of traditional hash functions by square root complexity, significantly weakening their preimage and collision resistance. This quantum threat necessitates the development of post-quantum secure hashing techniques that remain resilient against both classical and quantum adversaries. This paper proposes Quantum Hashing, a novel cryptographic framework that integrates quantum entanglement, lattice-based cryptography, and hybrid quantum classical hashing to construct post-quantum secure hash functions. We introduce a formal model for Quantum Collision Resistance (QCR) and provide entropy-based ran domness enhancement to ensure unpredictable hash outputs. Unlike classical hashing approaches, our framework leverages the hardness of lattice problems (e.g., Shortest Vector Problem, Learning with Errors) to withstand quantum attacks while incorpo rating Quantum Key Distribution (QKD) mechanisms to enhance entropy and key management. Furthermore, we evaluate the security of Quantum Hashing under various attack models, comparing its resistance against Grover’s search and collision attacks. We benchmark its performance against NIST Post-Quantum Cryptography (PQC) final ists, including CRYSTALS-DILITHIUM, SPHINCS+, and Falcon, demonstrating that our approach offers superior resilience while maintaining computational feasibility. Additionally, we present an implementation of Quantum Hashing using Qiskit, show casing its practical applicability in quantum circuits and quantum-secure blockchain architectures. Our findings highlight that Quantum Hashing provides a scalable, entropy-efficient, and post-quantum resilient cryptographic primitive suitable for next-generation cryptographic applications. This work paves the way for secure post-quantum digital signatures, blockchain consensus mechanisms, and zero-knowledge proof systems that require tamper-resistant hashing in a quantum computing era.
Primavera De Filippi, Morshed Mannan, Wessel Reijers
ABSTRACT Emerging technologies pose many new challenges for regulation and governance on a global scale. With the advent of distributed communication networks like the Internet and decentralized ledger technologies like blockchain, new platforms emerged, disrupting existing power dynamics and bringing about new claims of sovereignty from the private sector. This special issue addresses a gap in the literature by focusing the discourse on the issue of trust and confidence in the digital realm. In particular, looking at the evolution of the web (from Web 1.0, to Web 2.0, and then Web 3), this article analyses how every iteration reflects a different way of dealing with the problem of trust online, resulting in a different regulation and governance landscape. Technology is often regarded as a new lever of regulation, attempting to resolve the problem of “trust” online, either through the introduction of a new trusted authority (Web 2.0) or through the introduction of technological guarantees that provide more assurance—or “confidence”—in the way interactions can be operationalized (Web 3). Yet, each of these technologies also introduce new risks and governance costs, ultimately shifting the problem of trust in a new direction rather than resolving it or removing the need for trust altogether. The main contribution of the articles in this special issue is providing a better understanding of the trust challenges faced and posed by emerging technologies and demonstrating how they affect institutional governance—in both theory and practice—with a view to help policymakers find appropriate answers to these challenges.
This paper introduces a certificate verification system powered by blockchain technology to prevent document forgery and ensure authenticity. By using a distributed ledger, the system creates a permanent and transparent record for issuing and verifying certificates. In this Block chain technology, block chain performs Secure Certificate Storage with hash encryption, real time data verification & decentralized network of nodes validation. By using block chain technology, we can prevents Forgery from tampering and ensure authenticity. It ensures the data integrity while doing real time verification and it is more efficient than other technology. It minimizes the verification cost. This application is more scalable and used in multiple areas like the educational sector for document verification and health industry to validate the medical records and Supply chain management. This project demonstrates the potential of blockchain technology in securing certificate verification, preventing forgery, and enhancing trust in document authenticity.
ABSTRACT Self‐sovereign identity management systems operate in open network environments and face security threats from semi‐trusted or malicious adversary models. In such environments, verifiable credentials are susceptible to attacks such as theft and forgery. In response to the privacy risks associated with verifiable credentials during issuance and revocation, this article proposes a privacy protection scheme for user information during the issuance and revocation processes of verifiable credentials in self‐sovereign identity management based on blockchain technology. First, a privacy‐preserving method that does not rely on a single identity provider and resists Sybil attacks has been designed using secure multi‐party computation cryptographic techniques. Second, the consortium blockchain committee nodes act as the issuer of verifiable credentials. By combining attribute commitments and zero‐knowledge proof techniques, the user's identity information is hidden, achieving the privacy protection goal during the issuance of verifiable credentials. Furthermore, in order to protect user privacy during the revocation of verifiable credentials (VCs), we employ a cryptographic accumulator technique to implement the revocation operation. This approach ensures the security of user privacy while effectively managing the revocation of credentials. Finally, this paper conducts a security analysis and performance evaluation of the proposed scheme. The results show that our scheme strikes a balance between security needs and time efficiency.
Atefeh Zareh Chahoki, Maurice Herlihy, Marco Roveri
Conthereum is a concurrent Ethereum solution for intra-block parallel transaction execution, enabling validators to utilize multi-core infrastructure and transform the sequential execution model of Ethereum into a parallel one. This shift significantly increases throughput and transactions per second (TPS), while ensuring conflict-free execution in both proposer and attestor modes and preserving execution order consistency in the attestor. At the heart of Conthereum is a novel, lightweight, high-performance scheduler inspired by the Flexible Job Shop Scheduling Problem (FJSS). We propose a custom greedy heuristic algorithm, along with its efficient implementation, that solves this formulation effectively and decisively outperforms existing scheduling methods in finding suboptimal solutions that satisfy the constraints, achieve minimal makespan, and maximize speedup in parallel execution. Additionally, Conthereum includes an offline phase that equips its real-time scheduler with a conflict analysis repository obtained through static analysis of smart contracts, identifying potentially conflicting functions using a pessimistic approach. Building on this novel scheduler and extensive conflict data, Conthereum outperforms existing concurrent intra-block solutions. Empirical evaluations show near-linear throughput gains with increasing computational power on standard 8-core machines. Although scalability deviates from linear with higher core counts and increased transaction conflicts, Conthereum still significantly improves upon the current sequential execution model and outperforms existing concurrent solutions under a wide range of conditions.
The integration of privacy-preserving transactions into public blockchains such as Ethereum remains a major challenge. The Stealth Address Protocol (SAP) provides recipient anonymity by generating unlinkable stealth addresses. Existing SAPs, such as the Dual-Key Stealth Address Protocol and the Curvy Protocol, have shown significant improvements in efficiency, but remain vulnerable to quantum attacks. Post-quantum SAPs based on lattice-based cryptography, such as the Module-LWE SAP, on the other hand, offer quantum resistance while achieving better performance. In this paper, we present a novel hybrid SAP that combines the Curvy protocol with the computational advantages of the Module-LWE technique while remaining Ethereum-friendly. In contrast to full post-quantum solutions, our approach does not provide quantum security, but achieves a significant speedup in scanning the ephemeral public key registry, about three times faster than the Curvy protocol. We present a detailed cryptographic construction of our protocol and compare its performance with existing solutions. Our results prove that this hybrid approach is the most efficient Ethereum-compatible SAP to date.
<p>This study explores how Metaverse technologies can be applied to wine tourism. First, the background section reviews sensory mapping and experience economy theories and introduces the definition of Metaverse, technologies related to wine tourism, and differences from traditional tourism. Second, the research analyzes the application scenarios of immersive vineyard tours, simulated wine-tasting environments, online cultural activities, remote wine knowledge learning, experiential shopping, visitor interaction, and post-tour experience sharing. This study adopts a qualitative approach based on a literature review to explore these themes. Then, the changes of Metaverse technology on tourism organization are proposed, including benefit sharers, co-creation of tourism product value, personalized product customization, virtual digital communication, virtual product promotion, technology bridging, and non-fungible token (NFT) wine investment. Meanwhile, possible problems and coping strategies for Metaverse wine tourism are discussed. Finally, suggestions and practical guidance for future research are presented to promote the further development of the field.<strong></strong></p>
The prevalence of counterfeit medicines poses a significant threat to public health and safety, largely due to the opaque nature of traditional medicine supply chains. This research introduces a blockchain-based solution designed to bring transparency, traceability, and enhanced security to the medicine distribution process. The proposed system records every transaction in the supply chain, thereby preventing tampering and ensuring the authenticity of pharmaceutical products. Smart contracts are utilized to automate the verification and transfer of products between stakeholders such as manufacturers, distributors, and retailers. A decentralized application (DApp) was developed using React to facilitate user interaction, while the backend was implemented using the Truffle framework and connected to a local Ethereum blockchain via Ganache and Web3.js. The system supports real-time tracking of medicines and reduces dependency on intermediaries, which not only improves operational efficiency but also enhances the overall integrity of the supply chain. This blockchain-based approach represents a significant advancement over conventional methods by offering a transparent, tamper-resistant, and verifiable solution for medicine supply chain management. Keywords: Blockchain, Smart Contracts, Drug Counterfeiting, Supply Chain, Product Traceability, Security.
Smart grid technology is an amicable improvement of the conventional power grid characterized by improved communication, control, and computing technologies that enhance improved energy distribution. A smart grid is an improvement on the existing electric grid system that allow for more intelligent controlling of electricity from the generation point right down to the consumer. Consequently, the ICS (Industrial Control Systems) of smart grids have become more exposed to cyber risks resulting from enhanced network integration and digitalization. The complexity of smart grids with many DERs (Distributed Energy Resources), sensors, and systems make the security problem challenging. Reasons why decentralised smart grids have to be secure and more resilient mean that new approaches that can enable detection, prevention, and mitigations of cyber-attacks are desirable. Deep learning and smart grid cybersecurity based on decentralization has a bright outlook as it enables improving the detection of anomaly cases and potential threats and increasing the general level of resilience of the grid.Smart grids are a major evolution of conventional power grids that employ ICT (Information and Communication Technology) to optimize the delivery of electrical energy. Elements of smart grid include smart meters for consumers, automated distribution network, and communication network. Smart grids can be decentralised as it includes multiple DERs like solar power, wind mills or energy storage systems, that are usually integrated at the outskirts of the smart grid. Such decentralization adds more challenges to the grid's physical structure and also adds more vectors by which a cyber-threat can penetrate the network [1]. As such, cybersecurity emerged as a focal topic to protect the safe and reliable functioning of smart grids. It has also shown a commanding success in several contexts, which is due to the deep learning's inclusion capabilities of key features from accesses data [2]. A major advantage of deep learning is that models are able to detect the abnormal flow of traffic since they hold knowledge of normal traffic flow patterns [3]. Pattern recognition is another important factor; deep learning networks can recognize even complex pattern in a given data. However, deep learning models include scalability hence making them capable of analyzing a large quantity of data produced by, for instance, smart grids [4].The decentralized smart grids are the most vulnerable because of the localized architecture and large connections with IoT gadgets. The different systems that are used in smart girds are not homogenous and have different protocols and hence the weakness are provided [5]. Lack of computational capacity of many IoT devices due to resource constraints precludes such approaches and traditional security techniques cannot be implemented [6].Despite the potential of deep learning in smart grid cybersecurity, there are a number of issues before it. Concerning a few key points, it is important to mention data confidentiality as the training data can be considered sensitive. Another, there is an interpretability problem since, unlike traditional machine learning techniques, deep learning's models are considered 'black box' [7]. Another limitation of deep learning is that it demands massive computation, which may well not be readily feasible in low-power devices of smart grid [8]. There is also a big issue related to integration with legacy systems because such systems might be incompatible with deep learning solutions [9].Future research directions encompass the development of Smart grids which are decentralized and also experience a higher level of risk with relation to cybersecurity because of the deployment of several IoT devices. Table 1 summarizes robust deep learning approaches for smart grid cybersecurity, highlighting their advantages, challenges, and future directions. While these methods show high accuracy in detecting cyber threats (ranging from 92% to 99.5%), they face issues like high computational demands, vulnerability to adversarial attacks, and scalability concerns. Future research focuses on improving real-time integration, enhancing model interpretability, and developing more robust AI-driven cybersecurity frameworks.The most suitable solution for smart grid cybersecurity protection combines Federated Learning with Blockchain and Adversarial Deep Learning. With FL the grid nodes can participate in decentralized training processes without exchanging actual data which protects their information security and privacy. The combination of Blockchain technology and adversarial training creates an unalterable security framework which secures communication while building resistance against complex cyber threats. The implementation of this combined method becomes necessary because smart grids function through decentralized systems that connect many vulnerable IoT-enabled energy production networks to cyber security threats. Maximum security models become ineffective because they suffer from dimensional problems alongside privacy weaknesses and developing electronic strike threats. Through an integration of FL and Blockchain technology organizations achieve real-time threat detection with adaptive capabilities and lower IT overhead costs. Industrial security in the energy sector needs sophisticated AI-enabled solutions which must scale effectively to defend against infrastructure attacks and disruption of power supply. By utilizing this model organizations maintain autonomous cybersecurity operations which produce efficient proactive threat protection suitable for advanced smart grid systems against developing cyber attacks. Deep learning in the decentralised smart grid cybersecurity is a revolutionary way of handling the huge and dynamic risks. Based on the real-time data processing characteristic and the ability to recognize patterns of deep learning models, it is possible to improve the density of anomaly detection, threats' prediction, and systems' robustness. However, there are challenges that the use of deep learning in this area holds among them the fact that it calls for usage of a lot of computational power, data security issues, and the issues related with initiation and incorporation of integration of such complex technologies in the existing systems. To overcome these challenges new approaches, need to be created more efficiently, focus on to build effective privacy preservations, and integrate with other existing systems. For future work, the focus should be made on introducing new sophisticated and flexible frameworks of deep learning for the smart grid that will function in the given distributed environment. In this way, the industry can progress and advance towards building a smarter grid, that can address novel cyber threats and protect and enhance the reliability of the energy distribution systems.
Zero-Knowledge Proofs (ZKPs) are a rapidly growing technique for privacy-preserving and verifiable computation.ZKPs enable one party (a prover: P) to prove to another (a verifier: V) that a statement is true or correct without revealing any additional information.This powerful capability has led to ZKPs being applied and proposed for application in blockchain technologies, verifiable machine learning, and electronic voting.However, ZKPs have yet to see widespread, ubiquitous adoption due to the exceptionally high computational complexity of the proving process.Naturally, there has been recent work to accelerate ZKP primitives and protocols using GPUs and ASICs.However, the protocols considered so far face one of two challenges: they require a trusted setup for each new application or generate large proofs with high verification costs, limiting their applicability in scenarios with numerous verifiers or strict verification time constraints.HyperPlonk is a state-of-theart ZKP protocol that supports both one-time, universal setup and small proof sizes/verification costs expected by publicly verifiable, consensus-based systems (e.g., blockchain).While HyperPlonk's setup and verifier properties are highly desirable, the proving phase is costly.A HyperPlonk prover must compute on large bitwidths (e.g., 255-381b) and polynomials (e.g., of degree 2 24 ), employs computationally (e.g., MSM) and bandwidth (e.g., SumCheck) intensive kernels, and the complete protocol comprises many steps, each constituting distinct kernels.We present an accelerator, zkSpeed, to
Nuno Braz, João Santos, Tiago Dias, Miguel Correia
Blockchain technology has seen adoption across various industries and the real estate sector is no exception. The traditional property leasing process guarantees no trust between parties, uses insecure communication channels, and forces participants who are not familiar with the process to perform contracts. Blockchain technology emerges as a solution to simplify the traditional property leasing process. This work proposes the use of two blockchain oracles to handle, respectively, maintenance issues and automate rent payments in the context of property rental. These two components are introduced in a blockchain-based property rental platform.
Corruption in public procurement remains a challenge to good governance, especially in developing nations. Blockchain technology has been espoused as a new paradigm for achieving sustainable public procurement practices for effective service delivery and, by extension, promoting sustainable development. Given the potential of blockchain technology, its implementation has been slow in developing countries. Additionally, there is an inadequate decision support framework to prioritize corruption-prone stages of the public procurement cycle for strategic blockchain integration at the most critical corruption-prone stages of the public procurement cycle given the scarce resources available in developing countries. Therefore, we employed a matured theory that is the principal-agent theory to identify key agency problems related to public procurement in developing countries. An interview with 25 experts and a thorough review of Ghana’s Auditor General produced seven public procurement cycle stages. Further, a survey was designed for experts and stakeholders to prioritize the identified procurement stages under the agency problems through the Analytic Hierarchy Process (AHP). Our results revealed that tender evaluation was the most critical stage susceptible to corruption, followed by contract management and procurement planning in the public procurement stages. Additionally, for the relative importance of the criteria, information asymmetry was ranked first, followed by moral hazard, and then adverse selection. This study offers a targeted framework for blockchain deployment in public procurement from an African country perspective. The outcome of this study provides insights for policymakers and procurement practitioners to know the most critical stages of public procurement stages and leverage blockchain technology given the scarcity of resources in developing countries to aid sustainable public procurement. The proposed blockchain framework can enhance service delivery, citizens’ trust, and international donor confidence in partnership and funding for public procurement projects in developing countries.
Blockchain technology, originally introduced through Bitcoin cryptocurrency in 2008, has rapidly expanded beyond its financial roots, offering innovative solutions for secure data management across various sectors, including education. Higher education institutions, faced with challenges in managing academic records, verifying degrees, assessing skills, and safeguarding personal data, have increasingly looked to blockchain for answers. Blockchain’s transparent, immutable, and decentralized nature provides potential solutions to these longstanding problems. This systematic review assesses blockchain-based proposals for academic certificates management, aiming to highlight globally recognized best practices, explore the latest applications, and identify key challenges hindering the widespread adoption of blockchain technology in education. A thorough discussion based on the findings introduces potential solutions to mitigate these challenges and provides insights into possible future research directions that could help overcome these obstacles.
The emergence of the Metaverse as a decentralized digital ecosystem has transformed traditional contract enforcement by introducing smart contracts, self-executing agreements embedded in blockchain systems. This study conducts a comparative legal analysis of the regulatory frameworks governing smart contracts within Metaverse operations in Nigeria and Uganda. Employing a doctrinal legal method, the research critically examines primary legal sources such as statutory laws and case law, alongside scholarly literature, to assess legal recognition, enforceability, and institutional preparedness. The study reveals a significant regulatory gap in Nigeria, where the absence of a comprehensive legal framework creates uncertainty in the enforceability of smart contracts, despite growing blockchain policy initiatives. In contrast, Uganda has established more definitive legal provisions, particularly through its Electronic Transactions and Signature Acts, which explicitly validate digital contracts. The novelty of this study lies in its regional comparative focus on emerging economies and its analysis of how traditional contract principles interact with decentralized digital platforms. The urgency of this inquiry is underscored by the rapid digitalization of commerce, which necessitates timely legal adaptation to prevent regulatory obsolescence and safeguard stakeholders. This research contributes to the discourse on digital governance by proposing a legal reform agenda for Nigeria, advocating for the adoption of a smart contract-enabling framework modeled after Uganda’s approach. Ultimately, it calls for regional and international harmonization to ensure legal certainty, consumer protection, and dispute resolution within Metaverse-driven economies.
S.H. Anak Agung Alit Satya Prananda, Kadek Januarsa Adi Sudharma
This research examines the regulations and law enforcement efforts concerning the use of cryptocurrency as a money laundering tool in both Indonesia and the United States. Using normative legal research methods and a comparative approach, the study compares the legal frameworks of the two countries. In the United States, agencies such as FinCEN, IRS, and SEC play a critical role in enforcing laws against the use of cryptocurrencies for money laundering, with comprehensive laws and sophisticated enforcement mechanisms. Meanwhile, Indonesia relies on BAPPEBTI to oversee and regulate cryptocurrency activities. Although Indonesia’s legal framework may not be as extensive as the United States', the country has taken significant steps, such as adopting the "Travel Rule" to monitor cryptocurrency transactions. However, both countries face a common challenge: the anonymity offered by cryptocurrencies, which complicates investigations into money laundering. To address this challenge, both countries require more detailed regulations and enhanced international cooperation to effectively combat the misuse of cryptocurrencies for money laundering. The research suggests that strengthening legal measures and improving global collaboration are essential to mitigate the risks associated with cryptocurrency-based financial crimes.
This article compares event-driven architectures for real-time financial transactions, examining leading streaming technologies through the lens of financial industry requirements. The transition from batch processing to real-time event processing has been driven by customer expectations, regulatory mandates, and competitive pressures in modern financial services. Through evaluation of architectural patterns including event sourcing, CQRS, and saga patterns, the article demonstrates how different streaming technologies address immutability, consistency, and performance challenges unique to financial contexts. Performance characteristics and security considerations are assessed across platforms, providing decision frameworks for financial institutions balancing throughput, latency, and compliance requirements. Additionally, the article explores emerging technological trends that promise to further transform financial processing capabilities, including serverless computing, multi-cloud strategies, artificial intelligence integration, distributed ledger technologies, and edge computing solutions.
Cryptocurrencies have revolutionized digital finance, offering decentralization, anonymity, and cross-border transactions. However, these very attributes have also facilitated money laundering, posing significant challenges for regulators. This paper examines the risks associated with cryptocurrency in relation to money laundering, emphasizing India’s legal and regulatory framework. It discusses the role of the Prevention of Money Laundering Act (PMLA), the Reserve Bank of India (RBI) directives, and recent policy developments concerning digital assets. Additionally, the paper explores international regulatory frameworks and suggests policy measures to strengthen anti-money laundering (AML) mechanisms in India.
Distributed Ledger Technologies (DLTs) and smart contracts are revolutionizing industries by enabling transparent, decentralized, and automated transactions. However, the security of smart contracts remains a significant concern, as vulnerabilities can undermine the reliability of such systems and lead to substantial financial losses. Despite the critical importance of ensuring their integrity, there is a notable lack of automated frameworks to comprehensively assess smart contracts' security throughout their lifecycle, leaving them susceptible to various threats. This position paper proposes a framework to enhance smart contract security auditing, i.e., to efficiently and effectively support smart contract code analysis and testing and identify critical vulnerabilities. The framework encompasses several key components: identification of a target security profile, prioritization of potential vulnerabilities, systematic testing planning and execution, and a robust auditing and certification process. By establishing a structured approach to testing, we aim to enhance the security and reliability of smart contracts. In addition, we analyze the open challenges that must be addressed to build this framework effectively.
Anuj J. Ghom, Atharv N. Phuse, Harish S. Chopade, Mahesh A. Ghongade · 5 authors
Crowdfunding has emerged as a vital mechanism for raising funds, enabling startups, social causes, and creative projects to receive financial support from a broad audience.However, traditional crowdfunding platforms face challenges such as high transaction fees, lack of transparency, centralized control, and risks of fraud or fund mismanagement.To address these issues, we propose a Blockchain-Based Decentralized Crowdfunding Platform that leverages blockchain technology and smart contracts to enhance security, transparency, and trust in fundraising.By eliminating intermediaries, the system facilitates direct peer-to-peer transactions, ensuring immutability and automated fund distribution based on predefined conditions.This implementation utilizes the Ethereum blockchain to create an environment where fundraisers and backers can interact securely.The paper details the system architecture, smart contract design, security considerations, and a comparative analysis with traditional crowdfunding models.The results demonstrate improved transparency, reduced operational costs, and enhanced trust in the crowdfunding ecosystem.
The round complexity of interactive proof systems is a key question of practical and theoretical relevance in complexity theory and cryptography. Moreover, results such as QIP = QIP(3) (STOC'00) show that quantum resources significantly help in such a task. In this work, we initiate the study of round compression of protocols in the bounded quantum storage model (BQSM). In this model, the malicious parties have a bounded quantum memory and they cannot store the all the qubits that are transmitted in the protocol. Our main results in this setting are the following: 1. There is a non-interactive (statistical) witness indistinguishable proof for any language in NP (and even QMA) in BQSM in the plain model. We notice that in this protocol, only the memory of the verifier is bounded. 2. Any classical proof system can be compressed in a two-message quantum proof system in BQSM. Moreover, if the original proof system is zero-knowledge, the quantum protocol is zero-knowledge too. In this result, we assume that the prover has bounded memory. Finally, we give evidence towards the “tightness” of our results. First, we show that NIZK in the plain model against BQS adversaries is unlikely with standard techniques. Second, we prove that without the BQS model there is no 2–message zero-knowledge quantum interactive proof, even under computational assumptions.
Cryptocurrencies and blockchain technology have revolutionized the financial sector, offering decentralized, secure, and efficient transaction mechanisms. However, these innovations have also introduced new challenges, particularly in the realm of financial crimes such as money laundering, illicit trade, and fraud. This paper explores the dual-use nature of cryptocurrencies, examining their potential for both financial innovation and criminal exploitation, with over $20 billion in illicit transactions recorded in 2023 (Chainalysis, 2023). By reviewing case studies, regulatory responses, and technological solutions, this paper provides a comprehensive analysis of the risks and opportunities presented by cryptocurrencies and blockchain technology. Current regulatory frameworks, such as the EU’s MiCA Regulation (2023) and FATF recommendations and guidelines, have significantly influenced cryptocurrency adoption by balancing innovation with risk mitigation. The paper concludes with actionable recommendations for enhancing regulatory frameworks, fostering international cooperation, leveraging AI and other technological advancements, and creating educational initiatives to mitigate financial crimes in the digital age.
By combining behavioral finance theory and big data analysis technology, this study explores the mechanism of the impact of investor sentiment on cryptocurrency market price anomalies. Based on the fusion database of traditional exchange historical market data and social media sentiment data, the research team constructed multidimensional sentiment indicators to quantify the emotional fluctuations of market participants. The research design adopts the strict data cleaning process, feature engineering processing, and the hybrid modeling method combining the traditional statistical model and the machine learning algorithm. The empirical results show that extreme optimism or pessimism is significantly associated with abnormal price events, and the predictive ability of the composite sentiment index is better than that of the single volatility index. This research reveals the transmission pathways of cognitive biases such as overconfidence and the anchoring effect in the cryptocurrency market, confirming the significant influence of irrational psychological factors on the price formation of digital assets. The findings not only deepen our understanding of the interaction mechanism between investor psychology and market behavior, but also provide an innovative analytical framework for risk management and quantitative investment strategies in the cryptocurrency field.
Edgar Roberto Dulce Villarreal, Giovanni Hernández, Jesús Insuasti, Julio Ariel Hurtado Alegría · 5 authors
The exchange of medical information significantly benefits people's quality of life, improving their care and treatment. The interoperability of the entire healthcare ecosystem is a constant challenge. Blockchain technology is an alternative to find a balance in the healthcare ecosystem. Smart contracts (SC) are decentralized and self-executing programs that allow the automation of agreements without intermediaries to improve operational efficiency. However, the constant development of new Blockchain technologies and programming languages for smart contracts is a growing problem. This work presents the validation by expert judgment of the MUISCA (Mechanism for UnIversal SmartContrAct) tool, which uses Model Driven Engineering (MDE). MUISCA uses transformations of models and models to text to generate smart contracts in healthcare environments and specific to Blockchain platforms. The validation is conducted by smart contracts development experts, who show positivity in the perceived usefulness.