Mohammad Y. Allaho, Mehmet H. Karaata, Israa A. Elgemiei
The distributed ledger systems rely heavily on miners, who are a vital component of the cryptocurrency ecosystem. Most cryptocurrencies cease to exist within five years of operation [1] due to churning. Most current cryptocurrency analyses in the literature focus on mining pools and ignore the individual miners’ perspective and in-depth analysis of the churning phenomenon and its possible reasons. In this study, we conducted a longitudinal and overall study on two of the most growing cryptocurrency networks, namely Bitcoin and Ethereum. The Bitcoin dataset used spans over 12 years (2009-2021). Whereas the Ethereum dataset spans over 8 years (2015-2023), including the two versions of Ethereum (before and after the merge). Our goal is to uncover the factors that drive miners’ churning and reveal essential characteristics of cryptocurrency mining, such as network fairness and centrality. Generally, both networks experience a decline in active miners over time. Our results confirm the centrality of the Bitcoin and Ethereum networks, whereas Bitcoin is found to be more distributed and fairer than Ethereum in both versions. Also, in Bitcoin, solo miners are less centralized and experience a fairer distribution of blocks formation than pool miners, however, pool miners have more mining rewards on average. Also, pools are found to decrease churning for pool miners compared to solo miners. Moreover, it is found that miners’ waiting time is a significant factor in miners’ churning. The existing protocols used require improvements to increase network decentralization and fairness, as well as reduce miners’ churn.
Shereen Ismail, Bashar Othman, Hassan Reza, Eden Teshome Hunde
Illegal, unreported, and unregulated (IUU) fishing activities have become one of the most critical challenges facing the global fish industry, particularly in developing countries, with the economic impact of fish fraud reaching billions of dollars annually. A major contributor to this problem is the limitation of conventional fish supply chain systems, which lack secure data sharing among stakeholders, fail to provide trusted product information to consumers, and offer insufficient transparency for regulatory authorities. These shortcomings facilitate fraud and weaken trust and oversight across the supply chain. Blockchain technology has demonstrated strong capability to address key cybersecurity challenges by enhancing traceability, transparency, and tamper-resistant data integrity across distributed supply chain stakeholders. In this paper, we present an enterprise-oriented prototype of a secure, permissioned blockchain-based fish supply chain system designed to enable trusted data sharing and end-to-end traceability across multi-stakeholder environments. Building upon our prior work in Ethereum-based seafood quality monitoring, this study contributes: (1) a modular, consortium-grade architecture implemented using Hyperledger Fabric and containerized via Docker, supporting scalable organizational participation; (2) formal UML-based system modeling of supply chain actors, assets, and lifecycle transitions; and (3) custom chaincode logic that enforces ownership transfer workflows and regulatory compliance policies. In addition, the architecture is designed as agent-ready, exposing standardized APIs that enable future integration of autonomous AI-driven client applications for proactive supply chain orchestration. By leveraging a private, permissioned network model, the functional prototype demonstrates the feasibility of improving data veracity and providing a practical foundation for mitigating fraud and enhancing regulatory oversight in the global fish industry.
Education endowment funds are increasingly promoted as sustainable financing instruments to support long-term educational development, particularly within decentralized governance systems. However, empirical evidence on how such funds are governed and implemented at the local level remains limited. This study examines the governance of the Education Endowment Fund in Bojonegoro Regency, Indonesia, focusing on the translation of policy intentions into institutional practices and school-level utilization. Drawing on qualitative data from in-depth interviews and policy document analysis, the study finds that although the fund operates within a formally structured governance framework, its implementation is characterized by centralized decision-making, compliance-oriented accountability mechanisms, and constrained local agency. Consequently, the fund is largely utilized to address short-term operational needs rather than to advance long-term sustainability objectives. The findings also reveal the importance of informal coordination and adaptive practices in navigating administrative complexity, albeit with uneven outcomes across institutions. This study contributes to debates on education financing governance by highlighting the critical role of local governance dynamics in shaping policy outcomes.
Cryptocurrency has developed into a modern form of digital investment, largely supported by rapid technological growth, wider internet access, and the strong presence of social media. Although it has gained significant popularity in recent years, many investors still do not fully understand how it works, the risks involved, or whether it can remain stable in the long run.This study explores how individuals view and understand cryptocurrency as an investment option. It examines their level of knowledge, main sources of information, perception of risk, expectations of returns, and the influence of demographic factors such as age, education, and income on their investment decisions. The research is based on primary data collected through a structured survey, which helped capture real experiences, opinions, and concerns of participants.The study also seeks to understand whether people treat cryptocurrency mainly as a short-term speculative opportunity or consider it a long-term investment alternative. The findings reveal that social media platforms and peer groups play a major role in shaping investment decisions. At the same time, investors remain concerned about price volatility and the lack of clear regulatory guidelines, which continue to create uncertainty in the market.Keywords: technological growth,cryptocurrency,speculative.
AbstractBlockchain technology has transformed digital transactions by providing a secure, decentralized way to record data. Its best-known use is Bitcoin, the first cryptocurrency to work without a central authority. This article examines a Bitcoin transaction to show how decentralization, transparency, and cryptographic security enable digital payments without third parties.
Dr. P. U. Anitha, G.Rachana, K. Sushmitha, A. V. Senthil Kumar · 5 authors
Electronic Know Your Customer (e-KYC) systems play a crucial role in verifying user identities for financial institutions, telecom operators, and other service providers. However, traditional eKYC frameworks rely heavily on centralized databases, making them vulnerable to data breaches, unauthorized access, single points of failure, and privacy risks. To address these challenges, this paper proposes a blockchain-based e-KYC system that enhances trust, security, and user privacy. The proposed architecture integrates distributed ledger technology with smart contracts to create a transparent, tamperproof, and decentralized identity verification platform. User data is encrypted and stored securely, while verification records are maintained on an immutable blockchain ledger. Authorized entities can access customer information only through permissioned smart contracts, ensuring controlled data sharing and minimizing exposure. This approach eliminates repeated KYC processes, reduces operational costs, prevents identity fraud, and strengthens user control over personal data.Over all, the blockchainenabled e-KYC system provides a more reliable, efficient, and privacy-preserving solution compared to conventional centralized models. It significantly improves trust among stakeholders and establishes a secure foundation for digital identity management in modern financial and governmental ecosystems.
Achilles was invincible in battle — except for one point of structural vulnerability that no amount of strength could compensate for. Modern LLM-based agent frameworks (LangChain, AutoGen, CrewAI, ReAct) share this property exactly: impressive capability in controlled settings, catastrophically exploitable in regulated production environments through a single architectural flaw — the language model controls the decision. Organizations in regulated sectors (finance, insurance, healthcare, legal, compliance) face a direct consequence: these frameworks cannot be deployed in workflows subject to EU AI Act, DORA, or GDPR Article 22, because they provide no structural guarantee of determinism, auditability, or equal treatment. Traditional symbolic agent systems (JADE, Jason, Jadex) satisfy regulatory requirements but cannot ingest the unstructured natural-language inputs that define real enterprise workflows. The industry needs both properties simultaneously. No existing framework provides them. AQUILES is a production architecture for AI agents in regulated domains that resolves this gap through principled separation of concerns, instantiating the HADD paradigm (Hybrid Agents with Deterministic Decisions). AQUILES organizes agent functionality into five cooperating layers: an Interface Layer converting unstructured input into typed, validated beliefs via LLM sensors; a Cognition Layer performing pure-function BDI deliberation fully determined by its inputs; a Planning Layer selecting from a pre-verified HTN plan library without runtime synthesis; an Execution Layer enforcing typed precondition and postcondition contracts on every capability invocation; and a transverse Observation Layer producing append-only audit entries synchronously with every state transition. Language models are confined strictly to the perception boundary — they parse input into beliefs, they never select goals, plans, or capabilities. The heel remains; it is simply no longer load-bearing. The HADD paradigm is codified as six architectural invariants: (I1) Typed Role Inversion — LLMs as sensors only, never as control-flow components; (I2) Deterministic Cognition — the reasoning layer is a pure function of beliefs, goals, and rules; (I3) Bounded Planning — execution draws exclusively from a pre-verified plan library; (I4) Validated Execution — every capability invocation passes typed pre/post-condition checks; (I5) Complete Observability — every decision is forensically reconstructable from the audit log; (I6) Epistemic Precondition — no belief enters the BDI cycle without satisfying freshness, non-contestation, and source triangulation, enforced by the EVR module (Epistemic Verification for RAG). Any implementation satisfying all six invariants acquires reproducibility, zero LLM hallucination in state, LLM provider independence, and structural alignment with EU AI Act Articles 12–15 — as architectural properties, not retrofitted compliance measures. AQUILES partitions agents into cognitive holons (BDI-HTN reasoning components subject to full HADD governance) and reactive holons (deterministic capability executors verified by typed contracts alone). In observed production deployments, 70–80% of holons by count are reactive, meaning governance complexity scales with the cognitive subset rather than with total component count. The AQUILES protocol is language-agnostic by design: cognitive holons are typically Python (Anthropic SDK, sentence-transformers, pypdf); endpoint-monitoring holons are Go (single-binary cross-compilation); blockchain and zero-knowledge holons are Rust (arkworks, halo2, revm). We prove a Language Neutrality property: HADD compliance is preserved across heterogeneous polyglot deployments. For autonomous field deployments, AQUILES derives MYRMIDON agents that execute a signed MissionPackage autonomously on constrained hardware, inheriting AQUILES's safety guarantees without requiring runtime connectivity. This paper makes five engineering contributions: (C1) the HADD paradigm formalized as six architectural invariants with rationale and derived operational properties; (C2) the cognitive/reactive holon distinction and its governance economy consequences; (C3) a polyglot holon model with Language Neutrality proof and domain-language affinity mapping across Python, Go, and Rust; (C4) a multi-tenant operational-cell formalism enabling cryptographically enforced tenant isolation for regulated multi-client deployments; (C5) four reusable design patterns extracted from production experience (Sensor Firewall, Belief Expiry, Capability Contract, Observation Fanout), together with measurement methodology, adoption guidance, and explicit characterization of the architecture's limits.
Abstract The rapid digitalization of financial systems has significantly transformed the landscape of anti-money laundering (AML) frameworks, reshaping both the opportunities for financial innovation and the risks associated with illicit financial flows. While technological advancements such as cryptocurrencies, artificial intelligence (AI), blockchain technology, and fintech innovations have enhanced operational efficiency, transaction speed, and financial inclusion, they have simultaneously introduced complex vulnerabilities that can be exploited for money laundering and related financial crimes. These developments challenge the adequacy of traditional AML mechanisms, which were primarily designed for centralized and institution-based financial systems. This paper critically examines the evolution of AML frameworks, tracing their development from rule-based and compliance-driven approaches to more dynamic, risk-based, and technology-enabled systems. It explores how digital transformation has altered the typologies of money laundering, enabling increasingly sophisticated methods such as the use of decentralized finance (DeFi), mixing services, and cross-platform transactions that obscure financial trails. The study further analyzes key challenges arising in the digital era, including the pseudonymity and anonymity of digital assets, the speed and scale of cross-border transactions, regulatory fragmentation across jurisdictions, and limitations in data integration and information sharing. Additionally, it highlights the growing tension between effective AML enforcement and the protection of individual privacy and data rights. A central focus of the paper is the identification of critical regulatory gaps, particularly in the governance of digital assets, the lack of harmonized international standards, insufficient oversight of emerging financial technologies, and weaknesses in beneficial ownership transparency. These gaps reduce the effectiveness of AML regimes and create opportunities for regulatory arbitrage. The paper concludes by proposing a set of policy recommendations aimed at strengthening global AML compliance. These include enhancing international coordination, adopting advanced technological tools for monitoring and detection, developing comprehensive regulatory frameworks for digital assets, and promoting a balanced approach that safeguards both financial integrity and individual rights. Ultimately, the study argues that adaptive, technology-driven, and globally coordinated AML strategies are essential to effectively combat money laundering in the evolving digital financial ecosystem.
Lalithambikai S, R Kavinkumar, Sowndariya K, Barath M · 5 authors
While digital shifts have radically redefined modern governance and civil operations, the practice of casting ballots electronically continues to grapple with persistent obstacles concerning data transparency and operational robustness. Conventional, centralized digital voting systems typically harbor singular vulnerability points that attract cyber offensives, compounded by a distinct lack of mechanisms to rapidly manage arising voter concerns. In response to these pressing flaws, this study introduces a multifaceted architecture merging distributed ledger technologies with an intelligent, machine-learning-driven grievance resolution interface. Specifically, our model leverages a decentralised blockchain framework for immutable ballot storage, ensuring that individual vote modifications are virtually impossible and establishing a trustless verification environment devoid of centralized oversight. This schematic aims to seamlessly preserve data fidelity and supreme voter anonymity. Our comprehensive investigation of these distributed consensus rules and AI-guided triage methods indicates that unifying rigid cryptographic ballot handling together with responsive, automated complaint mechanisms dramatically elevates overall electoral resilience while reinforcing public faith in democratic workflows.
Abstract The rapid expansion of Initial Coin Offerings (ICOs), accompanied by widespread fraud and project failures, has underscored the need for more legally secure forms of blockchain-based fundraising. In this context, Security Token Offerings (STOs) have emerged as a potential alternative, combining distributed ledger technology with investor rights analogous to traditional equity instruments. This article examines the key legal and regulatory challenges faced by issuers of equity tokens within the European Union. It analyses the criteria for classification under EU financial law, outlines the applicable regulatory framework, and evaluates the impact of tokenisation models and cross-border offerings. Focusing on Estonia, Luxembourg and Poland, the study demonstrates that equity tokens remain subject to traditional securities regulation, resulting in fragmentation, legal uncertainty and significant compliance burdens.
Pakistan's most significant federalist initiative, the 18th Constitutional Amendment (2010), scrapped the Concurrent Legislative List and transferred wide-ranging legislative, administrative, and fiscal responsibilities to the provinces. But more than ten years on, devolution remains uneven. In this paper, we explore the administrative, political and institutional obstacles to devolution between 2010 and 2018, with a focus on Centre-Punjab relations, the pivot of Pakistan's federation. Through a qualitative documentary analysis of parliamentary proceedings, archival documents, institutional reports and academic work, we argue that bureaucratic mediation operates as a two-pronged process: provincial bureaucracies, especially in Punjab, facilitate some devolved functions, while federal bureaucracies continue to exert control via regulatory coordination, conditional fiscal transfers and legal grey areas. The National Finance Commission (NFC) Award, which increased provincial transfers, has not ended fiscal dependence: the provinces receive 60-70% of their budget from the centre. The removal of the Concurrent Legislative List resulted in unequal sectoral outcomes - provincialization in health and education, but contested labour and interprovincial coordination. We suggest that constitutional devolution in the absence of simultaneous bureaucratic, fiscal autonomy and effective intergovernmental coordination creates a hybrid governance form: constitutionally decentralized and operationally centralised. In the case of Punjab, we find that bureaucratic capacity is not enough; path dependence, bureaucratic opposition and political bargaining over devolution shape the outcomes. Our insights enrich understanding of decentralization theory by identifying bureaucratic mediation as a critical variable and provide policy lessons for other federations in the midst of reforms. References Adeney, K. 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Rethinking decentralization in developing countries. World Bank. Mustafa, Z. (2019). The 18th Amendment and Pakistan's federal evolution. The Lahore Journal of Economics, 24(2), 1–28. Naseer, A., & Khalid, I. (2021). Bureaucratic mediation in Pakistan's devolution. Asian Journal of Political Science, 29(3), 301–320. https://doi.org/10.1080/02185377.2021.1967304 National Assembly of Pakistan. (2014). Parliamentary debates on devolution implementation. Government of Pakistan. National Finance Commission. (2009). 7th National Finance Commission Award 2009. Ministry of Finance, Government of Pakistan. Niskanen, W. A. (1971). Bureaucracy and representative government. Aldine-Atherton. North, D. C. (1990). Institutions, institutional change and economic performance. Cambridge University Press. Oates, W. E. (1999). An essay on fiscal federalism. Journal of Economic Literature, 37(3), 1120–1149. https://doi.org/10.1257/jel.37.3.1120 Organisation for Economic Co-operation and Development. 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Aziz (Ed.), Pakistan’s constitutional journey (pp. 145–176). Oxford University Press. Stepan, A. (1999). Federalism and democracy: Beyond the U.S. model. Journal of Democracy, 10(4), 19–34. https://doi.org/10.1353/jod.1999.0072 Supreme Court of Pakistan. (2015). Government of Punjab v. Federation of Pakistan (Civil Appeal No. 12 of 2015). Talbot, I. (2015). Pakistan: A modern history. Oxford University Press. Thelen, K. (2004). How institutions evolve: The political economy of skills in Germany, Britain, the United States, and Japan. Cambridge University Press. Treisman, D. (2007). The architecture of government: Rethinking political decentralization. Cambridge University Press. United Nations Development Programme. (2013). Federalism in Pakistan: Opportunities and challenges. UNDP Pakistan. United Nations Development Programme. (2023). Devolution in Pakistan: Status, challenges and way forward. UNDP Pakistan. Waseem, M. (2019). Centre–province relations in Pakistan. In L. R. 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Open access
South Asian Studies and Conflicts
Politics and Conflicts in Afghanistan, Pakistan, and Middle East
While Large Language Models have achieved notable success on formal mathematics benchmarks such as MiniF2F, it remains unclear whether these results stem from genuine logical reasoning or semantic pattern matching against pre-training data. This paper identifies Architectural Reasoning: the ability to synthesize formal proofs using exclusively local axioms and definitions within an alien math domain, as the necessary ability for future automated theorem discovery AI. We use the Obfuscated Natural Number Game, a benchmark to evaluate Architectural Reasoning. By renaming identifiers in the Natural Number Game in Lean 4, we created a zero-knowledge, closed environment. We evaluate state-of-the-art models, finding a universal latency tax where obfuscation increases inference time. The results also reveal a divergence in robustness: while general models (Claude-Sonnet-4.5, GPT-4o) suffer performance degradation, reasoning models (DeepSeek-R1, GPT-5, DeepSeek-Prover-V2) maintain the same accuracy despite the absence of semantic cues. These findings provide a quantitative metric for assessing the true capacity for mathematical reasoning.
Open access
3 source records
Mathematics, Computing, and Information Processing
Cryptocurrencies and Decentralized Finance (DeFi) currently represent a fast growing trend in finance, which enables financial services on public blockchains. In contrast to traditional financial markets, ruled by well established corporations, DeFi is completely transparent, as it keeps publicly available records of all transactions that occur in the network. This availability of the data represents an opportunity to analyze and understand the market from the point of view of the complexity that emerges from the interactions among actors (users, bots, and companies) operating in the embedded market. In this paper, we focus on Ethereum to show that the underlying transaction network bears further and useful information to forecast the evolution of the market. We aim to separate the non-redundant effects of the blockchain transaction network from technical analysis and social media trends in the future price of the Ethereum native cryptocurrency. To this end, we build two machine learning models to predict the future trend of the price time series. The first model, serving as a base, considers the set of most relevant features according to the current scientific literature-including technical analysis and social media trends. The second model considers the features of the base model, incorporating the network properties computed from the transaction network. We find that the second model outperforms the base model and can anticipate 46% more rises in the price than the base model and 19% more falls. Thus, we conclude that new indicators based on network properties provide valuable information to forecast the future direction of the market that cannot be explained neither by technical analysis nor by social media trends alone. Hence, our results represent an important first step toward the definition of a new family of DeFi market indicators based on the complexity of the underlying transaction network.
Crowdfunding is an important mechanism for supporting innovative projects by connecting creators with distributed contributors. Prior research has identified persistent limitations in both traditional and blockchain-based crowdfunding platforms, including limited transparency, centralized control, passive contributor roles, and inflexible fund management processes. These limitations hinder accountability, equitable participation, and effective decision-making throughout the campaign lifecycle. This paper presents a blockchain-enabled crowdfunding framework designed as a decision-support artifact for adaptive fund allocation and participatory governance. The framework enables contributors to engage in spending-request governance through Quadratic Voting, which balances influence across heterogeneous financial stakes and mitigates dominance by large contributors. To support adaptive campaign management, the framework further integrates Ethereum smart contracts with a Markov Decision Process (MDP), enabling campaign-level decisions to respond to evolving contribution patterns and campaign states. The framework is implemented and evaluated through controlled experiments on the Sepolia Ethereum test network. The evaluation includes both an internal ablation of Quadratic Voting and MDP-based adaptive support and an external comparison against representative blockchain-based baselines. The results show that the combined Quadratic Voting and MDP design achieves lower approval latency and higher throughput than partial or static variants of the framework, and that the full proposed platform outperforms the compared baseline systems under increasing campaign workload. Overall, the study demonstrates how participatory governance, adaptive decision support, and transparent smart-contract execution can be systematically integrated into crowdfunding platforms, providing practical guidance for the design of scalable, efficient, and accountable decentralized crowdfunding systems.
Electronic voting systems are designed to modernise democratic processes by providing efficient, transparent, and accessible elections. They promise rapid tallying, reduced human error, and increased participation. However, large-scale deployment remains hindered by unresolved concerns around security, privacy, scalability, and trust. Direct recording electronic machines suffer from limited verifiability. In Internet voting, the more fundamental risks stem from compromised end-user devices, difficulty in achieving end-to-end verifiability that ordinary voters can meaningfully check, and exposure to coercion and vote buying, rather than generic cyberattacks alone. Blockchain-based approaches, while offering immutability and public auditability, face significant scalability limits. Network throughput and latency constrain election-sized workloads, fee volatility creates cost uncertainty, and per-vote on-chain actions, such as posting ballots and verifying cryptographic proofs, incur prohibitive costs that grow linearly with the number of voters. The openness of public ledgers also leaks metadata that can erode privacy. Consequently, achieving accountability and transparency without sacrificing individual ballot secrecy and practical efficiency remains a central challenge. This thesis addresses these challenges by providing the first thorough analysis of a ranked-choice blockchain election protocol that had not been previously examined in detail. The analysis identifies critical limitations related to privacy and efficiency that weaken unlinkability and verifiability. Building on these findings, the first significant contribution of this thesis is the design of a new, verifiable, and privacy-preserving voting framework that eliminates the need for a trusted tallying authority. The scheme employs anonymous participation tokens and nullifiers to enforce one-time eligibility. At the same time, voters cast encrypted ballots accompanied by zero-knowledge proofs that confirm eligibility, correctness, and uniqueness without disclosing their identity or the content of their vote. Tallying is achieved through a decentralised threshold decryption process that ensures fairness and confidentiality. The second significant contribution of this thesis is an efficient proof-batching and verification mechanism that addresses the scalability bottlenecks of existing blockchain-based approaches. By aggregating multiple proofs off-chain and submitting a single, succinct batch proof with updated commitments, the protocol reduces on-chain verification to a near-constant cost per voter. This significantly decreases computational and financial overhead, enabling scalability to large elections. The proposed framework is analysed under realistic adversarial models and shown to achieve privacy, eligibility, uniqueness, and universal verifiability. Performance evaluation demonstrates that the batching mechanism substantially lowers costs compared to existing protocols. Overall, this research advances the state of the art in blockchain-based electronic voting by providing the first comprehensive evaluation of a ranked-choice protocol and proposing novel mechanisms that overcome its limitations, thereby laying a foundation for secure, transparent, and scalable digital elections.
The rapid growth of geographically distributed cloud data centers has intensified the demand for secure, privacy-preserving, and resource-efficient collaboration among mutually untrusted cloud environments. This paper presents BlockFed, a blockchain-empowered federated learning framework designed to enable cyber-threat-resilient collaboration across geographically distributed data centers. In BlockFed, each data center independently trains local models using private workload data and shares only the computed gradients rather than raw data, with a centralized aggregation server through a secure blockchain layer. A Proof-of-Work consensus mechanism is employed to validate gradient transactions and maintain an immutable, tamper-resistant ledger, ensuring trust and integrity among participating entities. The centralized server aggregates blockchain-verified updates to construct a global model, which is iteratively redistributed to support collaborative learning. This integrated learning process enhances task-level resource demand prediction while simultaneously improving system security and operational efficiency across all participating data centers. Extensive simulations on the Google Cluster Dataset show that BlockFed outperforms state-of-the-art baselines, including ISTM, ETP-WE, First-Fit, Best-Fit, and Random-Fit, in resource utilization, power consumption, and active server reduction. BlockFed achieves up to 7-81% higher resource utilization, 41-58% lower power consumption, and 31-65% fewer active servers, while attaining a cyber-threat estimation accuracy of 93.19%.
Certificate management systems encompass aca-demic records; government-issued documents; professional li-censes; notary services.They play a vital role in creating a modern e-government system.Current certificate management methods are plagued by forgery, slow veri-fication, fragmented records between several institutions and vulnerability to compro-mise because of increasing numbers of data breaches.Blockchain innovations create the potential to address these different chal-lenges given their unique features such as: immutability, de-centralization, cryptographic security and full traceability via transparent auditability.The objective of this paper is to combine the current research on certificate management with blockchain technology via a systematic review of 12 peer-reviewed journals which focus on: Research methods used by each author.Data sets used by each author.The evaluation environment used by each author.The performance and security metrics that are being utilized in each author's research.The comparative findings of each author's research with respect to certificate management using public and permissioned blockchains.Results of this study demonstrate that the current core tech-nical functionality of certificate management using blockchain has been established; however, there are still major gaps in the current body of knowledge that need to be addressed, including:1. Privacy solutions, specifically zero-knowledge proofs.2. Ability to scale to the national level.3. Cross-platform interoperability.4. Validation of real-world prototypes.Additionally, we have described each of these gaps explic-itly and created a prioritized future agenda for research that addresses issues related to privacy, scalability, interoperability, security auditing and user-centered evaluation.
Biometric authentication has become a crucial element of digital identity systems, leading to a rise in significant challenges for information governance, privacy, and organizational trust. Current approaches address either biometric template protection or liveness verification in isolation, significantly overlooking their interdependence in privacy-preserving system design. In practice biometric privacy depends jointly on template protection, liveness verification, and compliance with biometric standards such as ISO/IEC 24745, which define irreversibility, unlinkability, and renewability requirements. Without integrating all three, biometric systems remain vulnerable. A cryptographically protected template may still be exploited if liveness checks fail, whereas standalone liveness mechanisms risk exposing sensitive biometric features. This research-in-progress paper presents ZKBioVault, a conceptual framework that integrates cancellable biometrics, fuzzy vault cryptosystems, and zero-knowledge proofs to support privacy-preserving authentication. Combining principles from the biometric template protection literature and ISO/IEC 24745 standards, the framework introduces a two-phase architecture that is designed for responsible digital infrastructure. A scenario-driven application example demonstrates how ZKBioVault can reduce organizational risk and strengthen the trust placed in biometric information management. This is extremely useful in environments which are increasingly affected by synthetic and AI-generated biometric artifacts.
Digital contracts are formal agreements created, signed, stored, verified and executed through digital platforms. These contracts require long-term protection because they often contain legally, financially and organisationally sensitive information. However, classical cryptographic methods used in current digital contract systems may become vulnerable with advances in quantum computing. This paper focuses on Quantum Internet of Contracts (QIoCs) as a future direction for preparing digital contracts for the quantum era. It examines post-quantum cryptography, quantum communication, blockchain, smart contracts, digital identity, zero-knowledge proofs and risk-based migration strategies. The paper argues that QIoCs cannot rely on a single security method. Instead, they require a layered approach that combines quantum-resistant blockchain protocols, privacy-preserving data authentication, secure audit trails, legal governance and staged migration from classical systems to quantum-safe contract infrastructures. The paper highlights the need for legal acceptance, governance standards and real-world testing of proposed post-quantum models. Overall, the paper provides a review-based framework for building safer and more reliable digital contracts in a quantum-safe future.