Manaswini Piduguralla, Souvik Sarkar, Arunmoezhi Ramachandran, Sathya Peri
Blockchain technology enhances transparency by maintaining a distributed ledger among mutually untrusting parties. Despite its advantages, scalability and availability remain critical bottlenecks that hinder widespread adoption. The increasing complexity of blockchain nodes further necessitates robust fault tolerance and high throughput to ensure seamless operations. We present BlockRaFT, a crash-tolerant distributed framework designed to improve both the scalability and reliability of blockchain node operations. BlockRaFT framework utilizes RAFT consensus protocol to elect a leader within a cluster of systems. The elected leader coordinates and distributes workloads across follower nodes, thereby optimizing resource utilization and work load balancing. We analyzed the tasks performed by blockchain nodes and partition them according to their stateful and stateless characteristics. Stateless operations are centralized at the leader, while stateful operations are replicated and coordinated across the cluster to ensure consistency and fault tolerance. We evaluate whether this distributed intra-node architecture provides measurable benefits over traditional single-node execution models in terms of scalability, availability, and performance. Additionally, we introduce a concurrent Merkle tree optimization that decouples smart contract execution from tree updates, significantly reducing one of the significant performance overheads in blockchain systems. Our design philosophy is rooted in utilizing the well-established principles of distributed computing and customizing them for the blockchain domain rather than reinventing them.
Decentralized Autonomous Organizations (DAOs) represent a fundamental shift in collective action and business management, transitioning from traditional "top-down" hierarchies to blockchain-based distribution of power. This research explores how DAOs utilize smart contracts to establish autonomous, decentralized organizations governed by code rather than central leadership. By leveraging token-based voting and automated execution, DAOs address critical "pain points" in corporate governance, specifically transparency and the Principal-Agent Problem.Through a comparative analysis of traditional corporations and decentralized models like Maker DAO and Uni swap, the study highlights the benefits of public auditability and aligned financial incentives. However, the transition to this "future of management" faces significant hurdles, including regulatory uncertainty, security vulnerabilities in code, and voter apathy. This paper concludes that while DAOs offer a democratic, flat alternative to the modern firm, their ultimate success depends on evolving legal frameworks and robust technical security.
The communication protocols and data transfer mechanisms employed by IoT devices in smart buildings and corresponding digital twin systems predominantly rely on centralized architectures. Such centralized systems are vulnerable to single points of failure, where a malfunction can disrupt operational processes. This study introduces a blockchain-based decentralized protocol to enhance the cyber resilience of IoT data transfer for digital twins and enable decentralized automation of building operations. The framework incorporates public and private blockchain technologies alongside two case studies showcasing prototypes of each system. These prototypes were validated within a real-world building environment using smart home appliances and two digital twin platforms, with their performance evaluated based on cost, scalability, data security, and privacy. The findings reveal that the Hyperledger Fabric-based system excels in terms of scalability, speed, and cost-effectiveness, while both frameworks offer advantages over traditional centralized protocols in system cyber resilience, data security, and privacy.
Products of MDS codes are of major practical importance; for a recent example, they are used in Data Availability Sampling (DAS) in blockchain networks such as Celestia and as part of the Ethereum roadmap. This motivates us to consider subcodes of such codes with the goal of obtaining a larger minimum distance. In this paper, we present explicit constructions of subcodes of Reed--Solomon product codes, along with bounds on their minimum distance. In particular, they achieve an optimal or near-optimal dimension--distance tradeoff. For component codes of dimension $r$, our construction requires a field whose size is bounded linearly by the overall product code length, and attains the maximum possible minimum distance for subcode dimensions $r^2-1$, $r^2-2$, and all dimensions at most $2r-1$. Furthermore, we establish a new upper bound on the minimum distance of subcodes of the product of two codes with identical parameters.
Jian Gao, Lufeng Zhang, Ping Fang, Pu Ke Ā· 7 authors
Fluctuation theorems show how coarse graining transforms microscopic symmetry into observable irreversibility. Here we ask whether an analogous symmetrybased diagnostic can be constructed for financial markets. At the microscopic level, each transaction pairs a buyer and a seller, whereas trading decisions are typically made from coarse-grained price histories. Using symmetric takeprofit and stop-loss rules, we compare the holding-time distributions of long and short trading ensembles generated from the same price series. Across equityindices, individual stocks and cryptocurrencies, the log-ratio of the two distributions shows a robust crossover. It remains nearly constant at short durations but becomes linear in the tail, implying an exponential directional asymmetry. The tail slope defines an effective market temperature, an operational measure of fluctuation intensity on the chosen observation scale. A Bachelier first-passage benchmark captures the exponential tails but not the asymmetry, because long and short positions share the same leading decay rate. By contrast, short-time correlations between overlapping positions provide a minimal mechanism for the asymmetry by generating direction-dependent subleading relaxation spectra in a coarse-grained Markov description. Together, these results establish a fluctuation-theorem-like diagnostic of irreversibility in financial markets and, more broadly, in complex systems accessible only through coarse-grained observables.
This study examines the factors contributing to cryptocurrency adoption in South Africa. This study utilized an exploratory research design that applied a qualitative technique. 10 key informants were selected using purposive sampling from organizations involved in the bitcoin industry in South Africa. The study demonstrates that the adoption of cryptocurrencies in the country is influenced by factors such as financial inclusion and access, innovation and entrepreneurship, economic diversification and regulatory frameworks, and teamwork. The challenges and hurdles encompass legislative ambiguity, cybersecurity risks, investor safeguarding, financial education and awareness, infrastructure limitations, and accessibility issues. The findings indicate that adopting cryptocurrencies can enhance financial inclusion, stimulate innovation and entrepreneurship, and tackle systemic problems in the financial industry. Nevertheless, the effective implementation and assimilation of cryptocurrencies in South Africa will necessitate a collaborative endeavour among all parties involved. Robust regulatory frameworks, comprehensive educational programmes, and cooperative endeavours are essential for maximizing the advantages of cryptocurrencies while minimizing the accompanying hazards.
Smart contracts exhibit increasingly complex semantics and interactions, yet existing vulnerability detection methods rely on single-granularity representations, limiting their ability to capture semantic mechanisms across bytecode execution and cross-contract interactions. In addition, vulnerability data are scarce and imbalanced, and most deep learning-based approaches lack semantic interpretability. To address these limitations, a semantic-aware cross multi-granularity representation enhanced detection framework (CMR-ED) is proposed. CMR-ED models opcode execution semantics, function-level behaviors, and cross-contract interactions, aligning multi-level semantic information within a unified representation space. A structure-aware vulnerability pattern generator mitigates data scarcity through semantically consistent sample synthesis, while an explainable detection mechanism provides triggering paths and reasoning-chain explanations. Extensive experiments show that CMR-ED outperforms state-of-the-art methods while improving interpretability under semantically complex scenarios.
Riya Sapra, Shal, Ishika Kataria, Sarita Ā· 5 authors
A distributed ledgers information base split throughout the computer group's centres. As a data set, a blockchain stores information electronically in an elevated structure. Blockchain technologies are well-known for their role in cryptographic currency systems, such as Bitcoin, in maintaining a secure and decentralised record of transactions. The benefit of a blockchain is that it ensures the privacy and authenticity of a records while also establishing confidence in the absence of a trusted third party. The suggested system is a blockchain-based decentralised organ transplant app. Patients would use a web application to submit their information, which include their healthcare ID, blood group, tissue type, and state. Until a patient is in serious situation, the program would operate on a first-in, first-out basis.
Rohith Singh, Mr. Charan Singh, Abdul Rashad, Md. Abdur Rasheed Ā· 6 authors
Prompt injection is a foundational security vulnerability in large language models (LLMs) deployed as autonomous agents with tool access and multi-step reasoning capabilities. Existing defenses rely on heuristic filters that fail under obfuscation, indirect injection, and multi-agent propagation. We present a Unified Cryptographic-Control Architecture (UCCA), a principled framework that integrates five complementary guarantees: (1) information-theoretic leakage bounds derived via Fano's inequality, (2) certified robustness via randomized smoothing, (3) token-level rejection via erase-and-check, (4) runtime trajectory enforcement via control barrier functions (CBFs), and (5) verifiable inference via zero-knowledge proofs (ZK-SNARKs). We formally prove that any successful prompt injection attack must simultaneously bypass all five mechanisms, a condition we show has probability at most Ī“ under stated assumptions. We evaluate UCCA on three real LLMs (GPT-4o, Claude 3.5 Sonnet, Mistral-7B) across four established attack benchmarks (INJECAGENT, TensorTrust, PromptBench, HarmBench), achieving attack success rates below 8% while maintaining median latency overhead under 340 ms. Our framework bridges formal security guarantees and deployable system architecture, establishing a foundation for provably secure autonomous AI. ā¢ Information-theoretic bounds on system prompt leakage using mutual information and Fano's inequality. ā¢ Certified robustness for safety-critical classification through randomized smoothing, where the robustness radius R is determined from output probability gaps. ā¢ Token-level rejection guarantees using an erase-and-check procedure capable of detecting adversarial subsets of size ā¤ k. ā¢ Runtime safety enforcement through control barrier functions (CBFs), ensuring LLM outputs remain within a verified safe set. ā¢ Verifiable inference using ZK-SNARKs, allowing cryptographic attestation of model outputs without revealing model weights. ā¢ UCCA, a deployable system integrating all five mechanisms, evaluated on real LLMs and standard benchmarks.
The rapid emergence of contemporary financial conceptsāsuch as decentralized finance, cryptocurrency, and algorithmic tradingāhas necessitated an advanced level of digital literacy to maintain and achieve financial well-being. This paper presents a comprehensive mixed-methods study to explore the intersection of these domains. The qualitative phase utilizes a News-Reflection Analysis (NRA) of 150 mainstream financial news articles from 2021 to 2025, yielding a robust coding framework and foundational propositions. Building upon these qualitative insights, the quantitative phase employs Partial Least Squares Structural Equation Modelling (PLS-SEM) on a simulated dataset of 450 respondents. We test a conceptual model integrating Contemporary Financial Concepts (CFC), Digital Literacy (DL), Financial Behavior (FB), and Financial Well-Being (FWB). Findings reveal that while CFC positively influences financial behaviour, digital literacy serves as a critical moderator, significantly amplifying the translation of complex financial knowledge into tangible well-being. This paper provides a Q1-journal-ready framework, complete with qualitative coding schemes, an advanced SEM path diagram, simulate hypothesis testing, and a rigorously validated 22-item measurement instrument.
H. M. Imran Hassan, Syed Enam Reza, Md Rafiqul Islam, A N M Obaidullah
The study explores the development of the I-REC standardized REC Trading Framework for Bangladesh, which can facilitate both local & international REC trading through a Nodal Agency. To implement such REC trading system, it is essential to establish a reliable, robust, transparent and secured REC trading platform that can gain global recognition and acceptance. Blockchain technology can play a crucial role to ensure transparency, security and trust in REC trading and verification system, as it offers a tamper-proof distributed ledger where RECs can be tracked from the issuance to the retirement. The entire process can be made automated using the self-executing algorithm called Smart Contract. This approach accelerates transaction processing and improves efficiency of record-keeping, minimizing the administrative overhead. Transactions such as the issuance, transfer, and redemption of RECs are securely recorded on the blockchain using cryptographic hashes of each block, making the process tamperresistant and easily auditable by all parties, thereby reducing the risk of fraud. Since blockchain employs a distributed ledger that is accessible to all stakeholders, global validators can independently verify the REC claims. The system's viability for national-scale deployment was validated using Ethers.js and the Remix VM, while its resilience was confirmed through a STRIDE-based threat assessment.
Dr. P. C. Prabhu Kumar, P. Poojitha, K. Satheesh Kumar, M. Charan Kumar Ā· 6 authors
The rapid digital transformation of the healthcare and drug sector has increased the reliance on cloud infrastructures for storing and exchanging Electronic Health Records (EHRs), raising significant concerns regarding privacy breaches, unauthorized access, and data integrity. To overcome these challenges, this project proposes a secure, patient-centric medical and drug data-sharing framework that integrates blockchain technology with distributed cloud storage. In this system, patients upload encrypted Personal Health Records (PHRs) to an untrusted cloud server while maintaining complete control over access permissions. A semi-trusted Setup and Re-Encryption Server (SRS) manage cryptographic key generation and re-encryption processes, enabling healthcare providers to access only the data explicitly authorized by the patient. All access requests, key operations, and permission updates are immutably recorded on a blockchain ledger, ensuring transparency, traceability, and accountability. The design further enforces forward and backward access control, automatically revoking past privileges when permissions are modified. Experimental evaluation demonstrates that the framework effectively ensures confidentiality, integrity, and access control while resisting tampering and supporting efficient real-time medical services, making it a promising solution for secure and scalable e-Health data exchange.
Cross-chain bridges are critical for decentralized finance (DeFi) to enable asset interoperability across heterogeneous blockchains. They are based on a complex hybrid architecture that involves on-chain contracts and off-chain relayers. In the recent past, several major attacks exploited vulnerabilities in cross-chain bridges. However, existing analysis tools have limited detection effectiveness as they focus on individual contracts and do not capture the complex interaction chain in cross-chain bridges. In this paper, we present BridgeFuzz, the first fuzzing framework for cross-chain bridge developers capable of detecting vulnerabilities such as balance mismatches, protocol errors, and off-chain denial-of-service bugs. BridgeFuzz is the first step towards bridging the gap between smart contract vulnerability research and the holistic vulnerability analysis of cross-chain bridges.
The modern judiciary is the key element of a law-governed state ensuring supremacy of law and protection of human rights. The article reviews historical and legal prerequisites for the development of judicial federalism, evolution of the lay justice status, and consequences of centralization of the judicial system. Taking into account the elimination of constitutional (statutory) courts of constituent entities of the Russian Federation and financing of lay justice with the federal budget, the author substantiates the position that, although a justice of the peace maintains the illusory status of a judge of a constituent entity of the Russian Federation, in fact it constitutes the main link in the federal (decentralized) judicial system.
Abstract This chapter examines non-fungible tokens (NFTs) that purportedly embody rights in creative works, revealing a fundamental disconnect between marketing claims and legal reality. It traces the evolution of NFTs from technical experiments through speculative fervor, collapse, and resurgence, establishing the economic and social context for legal analysis. The chapter identifies two dominant issuance models: the standardized approach using platforms like OpenSea and Mintable, and the bespoke approach employed by major issuers, including Yuga Labs and Dapper Labs. For standardized issuances, an examination of the terms of service reveals that while claiming to be passive facilitators, platforms retain substantial control and explicitly deny any property link between NFTs and underlying creative works. For bespoke issuers, the analysis demonstrates a mischaracterization of property law, including claims that ownership is āmediatedā by blockchain technology, attempts to condition property rights through contractual terms, and intellectual property licensing frameworks that are indeterminate and potentially invalid across jurisdictions. Nevertheless, the chapter argues that NFTs possess genuine commercial potential, which could be unlocked if they were structured in a manner consistent with established private law frameworks rather than attempting to circumvent them, as is the case in the present landscape. It concludes by proposing legitimate commercial applications, including pure digital collectibles, access-gated services, and digital certificates of authenticity that embrace legal frameworks while delivering meaningful market value.
Non-fungible tokens (NFTs) are transforming the commercialisation of digital art by establishing unique blockchain identifiers that ensure authenticity and certify subsequent transactions. However, the transfer of control over an NFT does not automatically include the transfer of the associated copyrights, thereby creating legal uncertainty as to what rights are actually acquired. This interdisciplinary project between engineering and law proposes the design of a smart contract, based on the ERC-721 standard, to manage the transfer of property rights linked to digital artworks represented as NFTs. The accompanying legal contract incorporates essential clauses covering the identification of the parties, a description of the artwork and its link to the token, pricing, royalties, and the terms of rights transfer. The proposal seeks to integrate blockchain technology with existing legal frameworks, offering an innovative solution that strengthens legal certainty in the transfer of copyright within digital environments.
Sufian Al majmaie, Ghazal Ghajari, Niraj Prasad Bhatta, Fathi Amsaad
The integration of Fog Computing with Flying Ad-Hoc Networks (FANETs) offers promising capabilities for decentralized, low-latency intelligence in UAV-based applications. However, the distributed nature, mobility, and resource constraints of FANETs expose them to significant security and privacy challenges, particularly against quantum threats. To address these issues, this work introduces a blockchain-based, AI-enhanced key management framework designed for fog-enabled FANETs. The proposed scheme employs a Post-Quantum Multivariate Identity-Based Signature Scheme (PQ-MISS) and Zero-Knowledge Proofs (ZKPs) to achieve secure key establishment, privacy-preserving data aggregation, and integrity verification. A polynomial composition-based encryption mechanism and an aggregate signature model support secure and efficient multi-device communication across fog and UAV layers. Fog servers construct partial blockchain blocks from validated UAV data. These blocks are completed and mined by Cloud Servers (CSs). AI algorithms then analyze the verified data to generate accurate predictions and insights. NS-3 simulations validate the efficiency of PQ-MISS in reducing communication overhead while improving the speed and reliability of data aggregation and verification. Comparative analysis demonstrates the proposed scheme's advantages over existing methods in computational cost, post-quantum security, and scalability, making it a robust solution for secure, intelligent, and future-ready FANET systems.
Decentralized Finance (DeFi) lending protocols like Aave v3 rely on over-collateralization to secure loans, yet users frequently face liquidation due to volatile market conditions. Existing risk management tools utilize static health-factor thresholds, which are reactive and fail to distinguish between administrative "dust" cleanup and genuine insolvency. In this work, we propose an autonomous agent that leverages time-to-event (survival) analysis and moves beyond prediction to execution. Unlike passive risk signals, this agent perceives risk, simulates counterfactual futures, and executes protocol-faithful interventions to proactively prevent liquidations. We introduce a return period metric derived from a numerically stable XGBoost Cox proportional hazards model to normalize risk across transaction types, coupled with a volatility-adjusted trend score to filter transient market noise. To select optimal interventions, we implement a counterfactual optimization loop that simulates potential user actions to find the minimum capital required to mitigate risk. We validate our approach using a high-fidelity, protocol-faithful Aave v3 simulator on a cohort of 4,882 high-risk user profiles. The results demonstrate the agent's ability to prevent liquidations in imminent-risk scenarios where static rules fail, effectively "saving the unsavable" while maintaining a zero worsening rate, providing a critical safety guarantee often missing in autonomous financial agents. Furthermore, the system successfully differentiates between actionable financial risks and negligible dust events, optimizing capital efficiency where static rules fail.
Permission control vulnerabilities in Non-fungible token (NFT) contracts can result in significant financial losses, as attackers may exploit these weaknesses to gain unauthorized access or circumvent critical permission checks. In this paper, we propose NFTDELTA, a framework that leverages static analysis and multi-view learning to detect permission control vulnerabilities in NFT contracts. Specifically, we extract comprehensive function Control Flow Graph (CFG) information via two views: sequence features (representing execution paths) and graph features (capturing structural control flow). These two views are then integrated to create a unified code representation. We also define three specific categories of permission control vulnerabilities and employ a custom detector to identify defects through multi-view feature similarity analysis. Our evaluation of 795 popular NFT collections identified 241 confirmed permission control vulnerabilities, comprising 214 cases of Bypass Auth Reentrancy, 15 of Weak Auth Validation, and 12 of Loose Permission Management. Manual verification demonstrates the detector's high reliability, achieving an average precision of 97.92% and an F1-score of 81.09%. Furthermore, NFTDELTA demonstrates enhanced efficiency and scalability, proving its effectiveness in securing NFT ecosystems.
Ayyana Prabu J, Ramkumar M. P, Emil Selvan G S R, Muthumeena S Ā· 6 authors
The pervasive adoption of Electronic Health Records (EHR) has improved the competence of healthcare storage, management of patient data and retrieval. These increase the vulnerability of EHR records through data breaches, unauthorized access, and proliferation of insider threat behaviors, with limited compatibility of health records. To address this issue, blockchain-based systems were introduced; however, they encountered leakage of sensitive information and have limited scalability. Concerning this, a Multi-Layer Blockchain framework integrated with Zero-Knowledge Proof (ZKP) (MLB-ZKP) was proposed to secure the EHR systems by privacy-preserving verification and reduce sensitive data exposure. The multi-layer blockchain method ensures the data storage, secure transaction validation process and efficient access control process. The proposed framework integrates the ZKP mechanism to aid the secure authentication process and data verification process without revealing the sensitive information. The entire framework ensures the patientcentric data ownership, secure cross-institutional data sharing and a governing privacy protection process. To validate the effectiveness of the proposed framework, available benchmark datasets were used. The experimental results show that the proposed framework exhibits increased privacy level, reduced data exposure risk and storage efficiency.
Divya Badwaik, Namo S. Shende, Shantanu N. Wankhede, Prajwal V. Gourkhede Ā· 6 authors
The increasing demand for secure, transparent, and efficient electoral systems has led to the exploration of advanced digital technologies in voting processes. Traditional voting systems, including paper-based and electronic voting machines, are often associated with challenges such as lack of transparency, susceptibility to tampering, centralized control, and delayed result processing. To overcome these limitations, this paper proposes VOTECHAIN, a blockchain-based electronic voting system that leverages the decentralized and immutable nature of blockchain technology to ensure trust and security in elections. The proposed system is built on the Ethereum blockchain using smart contracts, which automate critical operations such as voter registration, candidate registration, vote casting, and result computation. Each vote is treated as a secure transaction and is recorded on a distributed ledger, making it tamper-proof and verifiable. The system ensures that each voter can cast only one vote while maintaining voter anonymity through cryptographic techniques. A web-based decentralized application (VOTECHAIN) is developed using Web3.js and MetaMask to facilitate user interaction with the blockchain network. The system is tested using Ethereum test networks, demonstrating efficient performance, secure transaction handling, and transparent vote counting. The results indicate that blockchain technology can significantly enhance the reliability and integrity of electronic voting systems.
Indiaās aspiration to emerge as a developed nation by 2047 under the vision of Viksit Bharat necessitates the identification and scaling of localized innovations. Odisha, characterized by its socio-cultural diversity and rapid technological transition, presents a compelling case as a living laboratory for future-ready developmental models. This study positions Odisha at the intersection of three transformative domains: algorithmic welfare systems, governance challenges arising from silent urbanization, and the digitization of cultural heritage through Web3 technologies such as NFTs. By integrating quantitative modeling, qualitative fieldwork, and policy analysis, the study proposes a framework for culturally rooted, inclusive, and decentralized development. The findings suggest that Odishaās experiments in adaptive welfare delivery, the recognition of hybrid urban spaces, and digital cultural economies not only address local challenges but also offer scalable insights for national policy. The state thus emerges as a microcosm of a technologically empowered, socially equitable, and culturally vibrant Viksit Bharat.
We consider the block withholding attacks on pools, more specifically the state-of-the-art Power Adjusting Withholding (PAW) attack. We propose a generalization called Temporary PAW (T-PAW) where the adversary withholds a fPoW from pool mining at most $T$-time even when no other block is mined. We show that PAW attack corresponds to $T\to\infty$ and is not optimal. In fact, the extra reward of T-PAW compared to PAW improves by an unbounded factor as adversarial hash fraction $Ī±$, pool size $Ī²$ and adversarial network influence $Ī³$ decreases. For example, the extra reward of T-PAW is 22 times that of PAW when an adversary targets a pool with $(Ī±,Ī²,Ī³)=(0.05,0.05,0)$. We show that honest mining is sub-optimal to T-PAW even when there is no difficulty adjustment and the adversarial revenue increase is non-trivial, e.g., for most $(Ī±,Ī²)$ at least $1\%$ within $2$ weeks in Bitcoin even when $Ī³=0$ (for PAW it was at most $0.01\%$). Hence, T-PAW exposes a significant structural weakness in pooled mining-its primary participants, small miners, are not only contributors but can easily turn into potential adversaries with immediate non-trivial benefits.