Blockchain Papers

Steven Haynes

No abstract is available for this record.

Yuan Zhang, A. Damani

Technology labels are reshaping digital asset markets, yet little is known about what happens when those labels lose credibility. We examine whether regulatory enforcement against AI washing in traditional finance spills over to unregulated cryptocurrency markets, where disclosure is voluntary and technology claims are unverified. Employing an event study around three escalating SEC enforcement actions (2024–2025), we analyze AI-branded tokens against matched controls. Our findings reveal that AI tokens experience significant negative abnormal returns following early enforcement events, well beyond control token reactions. Notably, the market response attenuates by the third event, suggesting rapid investor learning. A pooled cross-sectional analysis confirms that the AI-specific penalty holds after accounting for token and platform characteristics. Together, these results demonstrate that technology category labels operate not merely as market descriptors but as strategic risk factors, with governance implications that extend well beyond formal regulatory boundaries.

Chih‐Cheng Lin, Hsiu-Yu Hung

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.

Varsha Ravindra Shetty, Mahesh Balan, Prajwal Vinod Naik, Nihaad Saleem · 5 authors

The study examines how institutional news media (Google news) and retail social media (Reddit) function as distinct information channels for the cryptocurrency market. Analyzing 55,282 records with dual sentiment methods, hypothesis testing, Granger causality, and Vector Autoregression, we identified how platform architecture can shape sentiment environments: Reddit exhibits higher positive sentiment than Google News. However, these differences do not have a drastic impact on predictive accuracy or trading returns. Critically, Granger causality reveals that Reddit sentiment leads Bitcoin returns at 3- and 7-days horizons, while Google News sentiment shows no predictive relationship with Bitcoin returns. These findings highlight that platform design determines whether a channel behaves as an early warning signal or a post-event commentary, with a foundation for certain decisions in the market.

Mrs. Meghana Dinesh Palkar

The rapid growth of urbanization in India has significantly increased the demand for efficient urban infrastructure, intelligent public services, and sustainable resource management. Cities are facing numerous challenges, including traffic congestion, rising energy consumption, water scarcity, environmental pollution, inefficient waste management, and increasing pressure on healthcare and public safety systems. Conventional urban management techniques are often inadequate for handling these complex and interconnected challenges because they rely heavily on manual monitoring and reactive decision-making. The Internet of Things (IoT), combined with smart electronic systems, has emerged as a transformative technology capable of addressing these issues by enabling real-time monitoring, automation, and intelligent decision-making. IoT-based smart electronics integrate sensors, embedded processors, wireless communication technologies, cloud computing, artificial intelligence, and data analytics to create interconnected systems that continuously collect, process, and exchange information. These technologies enable city administrators to monitor infrastructure, optimize resource utilization, improve service delivery, and enhance the quality of life for citizens. In India, the Smart Cities Mission has accelerated the adoption of IoT-enabled technologies across various sectors, including transportation, energy management, water distribution, environmental monitoring, healthcare, public safety, and digital governance. Smart electronics have enabled intelligent traffic control systems, smart street lighting, smart electricity meters, connected surveillance systems, and automated waste management solutions, thereby improving operational efficiency and reducing environmental impact. Despite significant progress, several challenges remain, including cybersecurity threats, interoperability issues, data privacy concerns, high deployment costs, and the need for standardized communication protocols. This paper presents a comprehensive discussion on the role of IoT-based smart electronics in building smart cities in India. It examines the technological architecture, key applications, implementation challenges, and future opportunities associated with IoT-driven urban development. The paper concludes that the integration of IoT with emerging technologies such as artificial intelligence, edge computing, fifth-generation (5G) communication, blockchain, and digital twin technologies will play a crucial role in achieving sustainable, resilient, and citizen-centric smart cities in India.

Feeroj Nasirkhan Pathan, Amarsingh Udhavrao Solanke, Mr. Wasim Taher Khan, Dr. Mangesh Manohar Dasare

The vision of Viksit Bharat 2047 seeks to transform India into a developed, inclusive, and globally competitive nation by the centenary of its independence. Achieving this vision requires a digitally enabled financial system that promotes innovation, expands financial inclusion, and supports sustainable economic growth. In this background, Financial Technology (FinTech) has emerged as a key driver of India's digital transformation. India's FinTech ecosystem has grown quickly with the support of Digital Public Infrastructure (DPI), including Aadhaar, Pradhan Mantri Jan Dhan Yojana (PMJDY), Unified Payments Interface (UPI), DigiLocker, India Stack and e-KYC. These initiatives have expanded access to financial services, accelerated digital payments, enhanced access to formal credit, strengthened public service delivery, and encouraged wider participation in the Indian economy. Emerging technologies such as artificial intelligence, blockchain, cloud computing, big data analytics, and application programming interfaces (APIs) have additionally enhanced the efficiency and accessibility of financial services. This chapter examines the role of FinTech in advancing the vision of Viksit Bharat 2047 by promoting financial inclusion, strengthening Digital Public Infrastructure, supporting entrepreneurship, improving governance, and fostering sustainable economic development. It also examines key challenges, that influence the long-term growth of the sector. It concludes that FinTech is more than a technological innovation; it is a strategic move of India's economic transformation.

Mohammed Sajedur Rahman, Nafiz Eashrak

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.

Sudeept Maharana, Deepak Saxena, Bharat Maheshwari

This paper examines investment decision-making processes in the context of disruptive technologies. While traditional decision-making frameworks assume that evaluation-relevant knowledge is readily available, this is not the case in the early stages of disruptive technologies. For disruptive technologies, the business case is not merely difficult to formulate but structurally unavailable at the point of decision. Based on data collected from senior executives across industries, this paper examines investment in disruptive technologies. Across categories including autonomous vehicles, solid-state batteries, blockchain, commercial drones, and generative AI, executives in our study note that the knowledge required to construct an investment case emerges primarily through the act of investing itself. In such cases, investment itself becomes a mechanism for generating evaluative knowledge, creating a recursive relationship between commitment and understanding.

Kristin Errett

Cross-chain bridges connect independent blockchains and carry the asset flows that make decentralized finance possible. Between 2021 and 2024, aggregate losses from major bridge exploits approached $3 billion, and the damage did not stop at the exploited bridges. Bridges hold pooled assets and issue derivative tokens that circulate as collateral across lending protocols and decentralized exchanges. A single exploit can cascade through chains and protocols with no direct relationship to the affected bridge. Empirical work on how bridge exploits propagate is limited. We apply network analysis to on-chain data from 15 cross-chain bridge exploits between 2021 and 2024 to trace how shocks spread through the ecosystem. The analysis extends financial contagion theory to decentralized infrastructure and identifies structural features associated with contained versus cascading failures.

Trinh Nguyen-Phan, Raghvendra Singh

Private blockchain adoptions are prone to failure, yet blockchain governance research has focused primarily on ecosystem-level structures rather than the micro-governance practices through which project leaders build internal legitimacy. Using an ethnographic case study of a successful Canadian public-sector-led private blockchain initiative in critical minerals mining, this study examines how leadership practices shape adoption success when leaders do not begin with superior blockchain expertise or sectoral prestige. The findings show that human-oriented values, project stewardship, and actionable optimism help build coordination capacity, collective learning, and internal credibility. Rather than treating expertise and prestige as prerequisites for success, we theorize how they can emerge through micro-governance enacted over time. The study contributes to blockchain governance and entrepreneurship research by explaining how leaders produce credibility inside private blockchain projects before it becomes externally recognized.

Divija Gadiraju, Deepak Khazanchi

This article addresses the growing integration of artificial intelligence (AI) and blockchain in enterprise incentive systems, highlighting gaps in the Information Systems literature regarding integrated governance frameworks. By developing a comprehensive AI–Blockchain governance framework, we leverage IT governance theory and sociotechnical systems perspectives, employing a conceptual design methodology alongside scenario-based simulations to assess architectural feasibility and governance efficacy. The proposed framework unifies AI lifecycle governance, programmable smart contract execution, and a metricized oversight model that translates key performance indicators such as security and fairness into measurable metrics. This integrated approach facilitates evaluation, execution, and continuous monitoring, offering managers a structured roadmap for the scalable deployment of tokenized AI incentive systems while advancing IT governance research through operationalized decision-right redistribution via programmable infrastructures.

Kiran Garimella, Shivendu Shivendu, Richard Ring

Inter-agency information sharing is central to effective public administration in national security contexts, yet tensions between confidentiality, authorization, and accountability hinder collaboration. While prior research examines administrative determinants, organizational trust, or blockchain-enabled mechanisms in isolation, the literature lacks an integrated digital governance architecture that embeds enforceable controls directly into public-sector information infrastructures. This study investigates whether administrative processes, organizational behavior, and technology-mediated trust are perceived as key determinants of effective inter-agency information sharing. A survey of thirty professionals across U.S. defense, intelligence, and law enforcement contexts provides empirical support for the importance of these governance dimensions. Building on these findings, we propose a conceptual blockchain-enabled governance architecture, the National Security Intelligence Chain (NSIC), that operationalizes authorization, classification enforcement, traceability, and accountability at the infrastructure level. By embedding governance rules into digital infrastructure, the proposed framework advances accountable and auditable inter-agency coordination in public administration.

Yi Yang, Likoebe M Maruping

The core attributes of public blockchain have enabled it to function as a decentralized platform-enabled ecosystem that fuels novel products and services developed by various participants. There have been debates about how decentralized the platform governance should be in order to coordinate innovation activities. This raises an essential question regarding which governance approaches can be well suited for innovations in public blockchain ecosystems. Studying the core attributes of public blockchain ecosystems, we identify two key tensions about governance: the tension raised by the participation of multiple actors with different incentives and the tension regarding where governance is targeted to facilitate innovation. To address these tensions, we develop a two-layer conceptual framework of governance in public blockchain-enabled ecosystems and argue that the tensions can be alleviated by aligning the locus of authority and target of governance. To capture the dynamics of the governance activities, we utilize vector autoregression to test our conceptual model. Our findings reveal that decision control activities at the application layer play a critical role in influencing decision management activities at the architecture layer, highlighting the importance of distributed actors in shaping protocol evolution. We also find dynamic inter-relationships among governance activities. We discuss both the theoretical and practical implications of these findings.

Hafsteinn Hjartarson, Anna Sigríður Íslind, Gísli Hjálmtýsson

Immigrants often encounter significant barriers to integration, including limited recognition of prior education, restricted access to learning opportunities, and low levels of trust in digital systems, all of which contribute to social exclusion in host societies. Although blockchain technology offers mechanisms for transparency, reduced reliance on intermediaries, and verifiable records, its potential for fostering inclusion remains underexplored. This paper presents EduChain, a permissioned blockchain architecture designed to explore how blockchain-based systems can support inclusion and trust among immigrants through academic credential verification and incentive-based learning. Drawing on documented challenges in education and academic credential verification reported in prior migration and integration studies, the paper identifies key design requirements that inform the system architecture. The study adopts an Action Design Research approach, implementing a prototype of a credential verification component while exploring the learning component conceptually in an analogous real-world setting.

Arthur Carvalho, Chad Anderson, Mala Kaul

Play-to-earn (P2E) games backed by blockchain technology enable players to earn tangible rewards through in-game activities. P2E has emerged as a revolutionary convergence of gaming and decentralized finance that ensures transparency, security, and verifiable ownership, fostering economic empowerment and novel digital interactions. In this paper, we investigate the technological and socio-economic dimensions of P2E by examining popular games (Axie Infinity and Hamster Kombat) and platforms (Sandbox). Through these examinations, we identify four critical challenges faced by the P2E ecosystem, namely community sustainability, player health, affordability, and fair rewards. We further present actionable research opportunities to address these challenges, including the potential to explore solutions based on game theory, mechanism design, and information systems theories. Overall, our findings highlight the transformative potential of P2E games and underscore the unique opportunity for the information systems community to contribute to the evolution of this dynamic digital ecosystem.

Ahmet Melih Karauğuz, Ali Yıldırım

Decentralized Autonomous Organizations (DAOs), built upon blockchain technology, have emerged as a novel governance model that distributes decision-making authority across participatory networks rather than relying on hierarchical processes. This study theoretically evaluates the DAO phenomenon from the perspective of public administration and examines the model’s transformative capacity concerning governance theory and practice. Furthermore, adopting an integrative approach, the study develops a five-dimensional analytical framework: participation, transparency, accountability, efficiency, and legitimacy. For each dimension, the paper discusses a triad comprising the theoretical promise of the DAO model, the patterns observed in the literature and practical cases, and its structural limitations. The findings indicate that DAOs possess robust potential in the dimensions of transparency and efficiency; however, in terms of participation, accountability, and democratic legitimacy, they face structural challenges, such as the plutocratic tendency of token-weighted voting and the absence of legal recognition. In this context, the central thesis of this study posits that the DAO model should be evaluated as a complement to the existing e-governance architecture rather than a substitute. Ultimately, the study reveals that while DAOs hold significant potential—particularly in local-scale, narrow-purpose, and participatory budgeting-style processes—fundamental barriers exist regarding legitimacy, accountability, and legal recognition that hinder macro-level substitution.

Uzma Shereen, Lubna Nausheen

This research introduces a novel Unified Quantum-Resilient Blockchain-Zero Knowledge Proofs Privacy Authentication Framework (QBC-ZKPAF) aimed at enhancing security in IoT environments. The system combines post-quantum cryptography, blockchain technology, and Zero Trust Architecture (ZTA) to provide secure communication, access management, and privacy-preserving authentication. It uses a Deep Q-Network Multi-Factor safe Key (DQN-MFSK) for dynamic key selection, a hybrid Reinforcement-Lattice Blockchain Key Generation for quantum-resilient key creation, and Zero-Knowledge Proofs for privacy-preserving signatures to ensure a safe Internet of Things environment. Data privacy, secrecy, auditability, traceability, and resistance to changing threats, such as quantum attacks, are all guaranteed by this architecture. Transparency and thorough post-event audit trails are supported by the blockchain ledger's immutability, which records all access attempts, data exchanges, and device interactions in an unchangeable way. Through a tracing key kept on the audit server within the Zero Trust Architecture, the architecture allows accurate source tracing in the event of suspicious activity or breaches. QBC-ZKPAF provides strong security and privacy solutions for Internet of Things networks by adopting multi-factor authentication and decentralizing identity management. The framework's efficacy is confirmed by experimental results, which show 98% privacy preservation, 700 TPS throughput, 0.98 quantum resilience, and 96% access control effectiveness, making it ideal for contemporary blockchain and IoT applications.

Joao C. Ferreira

Transparency in public affairs interactions between companies and governments is critical to democratic legitimacy, yet existing lobby registers suffer from fragmented reporting, weak record integrity, limited traceability, and compliance gaps. This paper reports a Design Science Research (DSR) study that develops and evaluates a permissioned blockchain architecture for mandatory Public Affairs transparency. Two stakeholder surveys provided empirical grounding: Survey 1 (N = 61 domain professionals) elicited functional, non-functional, and GDPR compliance requirements, while Survey 2 (N = 14 practitioner evaluators) assessed a proof-of-concept implementation on Hyperledger Fabric following a live demonstration. Findings reveal widespread concerns over non-repudiation and auditability in current systems — 87% rated existing record integrity as weak—alongside strong endorsement for blockchain’s immutability, versioned audit trails, and hybrid on-/off-chain design to ensure GDPR-aligned traceability. Post-demonstration evaluation achieved a mean score of 4.6/5 for traceability and integrity, and 86% of evaluators recommended real-world piloting. The study makes three contributions: (i) an empirically derived requirements model and information-lifecycle framework; (ii) a hybrid permissioned-blockchain blueprint implemented on Hyperledger Fabric; and (iii) a replicable stakeholder-centric DSR methodology for sociotechnical artefact design in regulated governance contexts.

Preston Vander Vos, Daniel Cason

Tendermint is among the most widely studied and deployed Byzantine fault-tolerant (BFT) consensus protocols, owing in part to its native leader-rotation mechanism that subsumes complex view changes. Like most partially-synchronous BFT protocols, Tendermint tolerates $f 5f$ setting that decides in two communication steps in the good case, while preserving Tendermint's leader-rotation structure. Fast Tendermint collapses Tendermint's prevote and precommit steps into a single voting step and merges the $locked$ and $valid$ state. We give proofs of agreement, validity, and termination, and a formal specification in Quint, a modern surface syntax for TLA+, used to model-check the protocol.

Zeta Avarikioti, Dimitris Karakostas, Karl Kreder, Shreekara Shastry

Our work presents a defense mechanism against Maximal Extractable Value (MEV) opportunities in distributed ledgers. The mechanism relies on the idea of enforcing a verifiable delay when generating transactions, such that a block creator cannot react to the appearance of a MEV opportunity without breaking liveness. We present positive results both in the Byzantine setting and in a game theoretic model of rational participants. We additionally present negative bounds that outline the limitations of this line of defense. Finally, we explore real-world implementation details of verifiable delays and show that, based on historical MEV data, our mechanism could realistically help prevent most existing MEV threats.

Sofia Bobadilla, Humaira Afrin, Angela Novelli, Martin Monperrus

Blockchains are among the most adversarial environments in computing. Billions are stolen by cybercriminals who exploit vulnerabilities. This is an open problem and no concept or technique has proven to really make a difference. In this paper, we claim that the classical notion of program invariant is perhaps the most powerful solution to the problem. We devise anoriginal experimental protocol to 1) study how invariants would have protected against past real-world attacks and 2) whether state-of-the-art automated tools can find them. The experimental toolchain is sophisticated. It is based on INVARIANTEVAL, a benchmark of 28 real Ethereum exploits, each paired with a human-authored invariant that blocks the attack. We validate every invariant with PONDEREPLAY, a replay framework that re-executes transactions in order to prove the correctness and soundness of smart contract invariants. We demonstrate that smart contract invariants block all the cybercriminal attacks in INVARIANTEVAL, fully validated by replaying 108,637 historical transactions. Our large-scale experiments clearly demonstrate that smart contract invariants protect against cybercriminals.

Dorottya Zelenyanszki, Zhe Hou, Kamanashis Biswas, Vallipuram Muthukkumarasamy

Public blockchain data enables large-scale DeFi-related analysis, but many existing approaches are application-specific, difficult to scale, or hard to interpret. This research proposes a scalable, application-agnostic framework for \emph{persistent behavioural pattern discovery} from large-scale blockchain activity. It constructs behaviour sentences enriched with contract, token and market context, then applies a two-step embedding process: sentence-level embeddings capture individual actions, while sequence-level embeddings capture user behaviour over time. An interpretable behavioural profiler characterizes discovered communities through behavioural motifs, routines, temporal dynamics, entity exposure, and suspiciousness evidence. Evaluation on Ethereum using over 30 million transactions shows that the framework uncovers both routine and malicious behavioural patterns, including decentralised exchange (DEX) trading, NFT activity, phishing, bot operations, oracle manipulation, and rug-pull schemes. Importantly, many patterns remain stable across independent observation windows, enabling the identification of long-term behaviours beyond a single analysis period. The proposed framework combines scalability, interpretability, and persistence analysis, supporting blockchain forensic investigation, behavioural attribution, and threat discovery.

Zexing Lu

The rapid development of cryptocurrencies, stablecoins, and central bank digital currencies (CBDCs) has transformed the global monetary landscape and accelerated the transition toward a cashless society. While critics argue that digital currencies threaten financial stability due to volatility, disintermediation, energy consumption, and regulatory concerns, this paper contends that the increasing competition among digital and fiat currencies can generate significant economic benefits. By examining the evolution of cryptocurrencies, the emergence of stablecoins, the global adoption of CBDCs, and the case of Zimbabwe's hyperinflation, this study argues that currency competition encourages governments to pursue more disciplined fiscal and monetary policies, strengthens policy credibility, and helps anchor inflation expectations. Greater monetary credibility also expands policymakers' ability to respond effectively to future economic downturns. Although digital currencies present important risks, many of these challenges can be mitigated through technological innovation, appropriate regulation, and institutional development. Overall, this paper concludes that a wellmanaged transition toward a cashless society can promote competition, innovation, and long-term economic resilience rather than undermine financial stability.

Giovanni De Luca, Angelo Montanino

Although stablecoins occupy a segment of digital-asset markets in which price stability is central by design, their temporary departures from reference values may reveal important information about latent risk and market stress. In this paper, we examine whether bubble and crash signals extracted from traditional cryptocurrencies and stablecoins improve volatility, Value-at-Risk, and Expected Shortfall forecasting and, in connection with these forecasting gains, contribute to the assessment of cross-asset contagions. The analysis applies the Bubble Crash–GARCH models, in which extreme price phases are identified through the Phillips, Shi, and Yu real-time monitoring procedure and incorporated into the conditional mean of returns through event-based dummy variables. For stablecoins, extreme episodes are not inferred from price dynamics in isolation but from deviations between the observed price and the asset-specific reference value. The empirical investigation focuses on Bitcoin, Ethereum, Tether’s USD-pegged (USDT), and Tether Gold and evaluates asset-specific bubble–crash effects and bidirectional contagion channels between traditional cryptocurrencies and stablecoins, using Bitcoin and Tether as the leading representatives of the two market segments. The findings indicate that accounting for bubble and crash episodes leads to more accurate volatility forecasts than standard GARCH benchmarks. For Value-at-Risk and Expected Shortfall, the bubble–crash specifications can improve tail risk forecasting at several tail probability levels through more accurate coverage, lower quantile loss, and stronger ESR backtesting performance. The results also reveal different degrees of price exuberance across the two asset categories: while extreme price dynamics are more evident among traditional cryptocurrencies, deviations from fundamentals are rare for stablecoins. Among stablecoins, USDT exhibits limited but detectable exuberance, whereas Tether Gold does not display extreme price episodes. However, when such deviations occur, as in the case of USDT, they generate significant contagion effects on major cryptocurrencies. Notably, extreme episodes originating in USDT have a stronger impacts on Bitcoin and Ethereum than the reverse spillovers from traditional cryptocurrencies to USDT. Overall, the evidence suggests that stablecoins are not merely passive instruments within the digital-asset ecosystem. Even temporary deviations from their reference values contain valuable information for risk forecasting and contagion monitoring.