Follow blockchain research across journals, conferences, and preprint repositories.
2,608 results · page 6 of 109
Tuan-Dung Tran, Tran Hoang Hai, Quang Dai Hoang Phuc
No abstract is available for this record.
Subhasis Thakur, John G. Breslin
No abstract is available for this record.
Gourav Singh, Arjun Pataskar
The integrity of electoral systems is fundamental to democratic governance; however, traditional voting mechanisms suffer from security vulnerabilities, lack of transparency, and accessibility constraints. This paper proposes a blockchain-based voting system leveraging distributed ledger technology to ensure secure, transparent, and tamper-resistant elections. The system integrates cryptographic techniques such as Zero-Knowledge Proofs (ZKPs) and Elliptic Curve Cryptography (ECC) within a permissioned blockchain framework using Hyperledger Fabric and Practical Byzantine Fault Tolerance (PBFT) consensus. A three-tier architecture consisting of Application, Blockchain, and Data Storage layers ensures scalability and efficiency. Security mechanisms including multi-factor authentication, end-to-end encryption, and AI-based anomaly detection mitigate potential threats such as Sybil attacks and denial-of-service attacks. Comparative analysis indicates improved security, transparency, and cost-effectiveness over traditional systems. The proposed framework demonstrates strong technical feasibility and provides a foundation for future advancements in digital electoral systems.
Liang Xue, Xiaodong Lin, Xuemin Sherman Shen
No abstract is available for this record.
Mrs.Dhanalakshmi.J, Gokul Pandi.P, Gurumoorthi.P, Ragul Pranav.A
Traditional and electronic voting systems face significant challenges in ensuring transparency, security, and voter trust. Issues such as centralized control, lack of auditability, vulnerability to tampering, and potential for fraud undermine the integrity of electoral processes. This paper proposes a novel blockchain-based electronic voting system designed to address these shortcomings through decentralized ledger technology and smart contracts. The system ensures vote integrity, voter anonymity, and public verifiability while preventing double voting and eliminating single points of failure. By employing cryptographic techniques such as zero-knowledge proofs and ring signatures, voter privacy is maintained without compromising transparency. The proposed architecture is evaluated through simulation, demonstrating scalability, reduced transaction costs, and robustness against common cyber threats. This work contributes to the advancement of trustworthy digital democracy and provides a feasible framework for real-world electoral deployment.
Baixuan Tian
This dissertation presents the design, implementation and evaluation of a blockchain-based e-voting prototype which supports ballot confidentiality, verifiability and auditability by combining homomorphic encryption, zero-knowledge proofs and Merkle inclusion proofs. The key innovation of this work lies in a unified on-chain protocol that cryptographically binds each ballot's Poseidon commitment to its ElGamal ciphertext through a shared binding hash, enabling Groth16-verified tallying and anonymous receipt-based audit without any trusted middleware. In the voting phase, the voter encrypts a one-hot ballot, computes a commitment and a ciphertext-binding hash, and submits them together with a zero-knowledge proof that the ballot is well formed without revealing the selected candidate. During the tallying stage, all encrypted ballots are off-chain aggregated, the final results are accompanied by a proof of correct decryption. Voters can confirm their ballots are included by using locally stored receipts and an audit bundle provided by the administrator. The prototype is implemented with Solidity for the smart contracts, Circom and snarkjs for zero-knowledge circuits, JavaScript for frontend interaction and Python for local serving and cryptographic validation. It was tested locally with Hardhat and then deployed to the Sepolia testnet for more realistic on-chain execution and gas measurement. The results show that the system functions as a research prototype, although further hardening is still needed before any production use.
Prof. Abhijeet More, Tejashree B. Patil, Deep Kharate, M P Akhil · 5 authors
As the multi-chain digital assets, decentralized finance (DeFi) and non-fungible tokens (NFTs) seeing rapid development, cryptocurrency portfolio management is causing strong pain among users.With the growing number of blockchain networks like Ethereum and a variety of chains, users commonly have assets across multiple wallets, protocols and dApps.Classic portfolio tracking services often require the constant relationship between client and server, with centralized servers, offering heavy privacy issues and security implications.Manual and account based access Many of these systems require data to be manually entered or employees to sign in with their accounts, which opens up the possibility for data leaks, inaccurate reporting, and divulgence of sensitive financial information.More centralized trackers unfortunately have a very poor understanding of more advanced DeFi functions such as staking, joining liquidity pools, and yield farming positions, total or just plain token approval permissions leading to either incomplete or worse yet misleading asset summaries.To solve the above issues, this system suggests a completely decentralized cryptocurrency portfolio tracker on client-side.The code utilizes APIs like Alchemy, Zapper and CoinGecko to read real-time token balances, NFTs creatures or positions (for DeFi), and allowances from the current network directly offchain.Being exclusively client side, the tracker does not rely on centralized databases and it is designed to minimize privacy compromises.The built-in on-chain security module is its most noticeable feature, as it detects any potentially malicious or extremely large token approvals given to smart contracts.Suspicious approvals can be detected, and then revoked in a timely manner through signed wallet transactions without needing to reveal any private keys.The results show that this decentralized tracker would provide significantly better user privacy, data accuracy and overall security.As a serverless applications service, that bypasses central authentication, as well as database storage, it offers a transparency, user-centric and scalable way to manage digital assets securely.
Ke Ding, Xiaoyan Hu, Zhuozhuo Shu, Guang Cheng · 6 authors
Non-Fungible Tokens (NFTs) have completely changed digital ownership and the decentralized economy. However, their anonymity and encrypted communication, conducted over encrypted tunnels, pose a significant obstacle to regulating illegal activities. Despite advances in encrypted traffic analysis, fine-grained identification of NFT behaviors over encrypted tunnels faces two critical challenges: 1) inexact segmentation of continuous behavioral traffic, and 2) feature homogeneity due to encryption-induced pattern obfuscation. In this paper, we propose NFTracker, a novel framework to identify fine-grained NFT behavioral traffic over encrypted tunnels. We design a traffic segmentation method to isolate behavioral units by leveraging traffic bursts and distribution discrepancies. To combat feature homogeneity, we introduce a sliding-window-based spatio-temporal feature extraction mechanism that captures localized action fingerprints. Furthermore, we utilize a hybrid CNN-Transformer model to integrate spatial patterns and temporal dependencies for robust behavior identification. We evaluate NFTracker on real-world datasets covering five NFT behaviors (browsing, wallet login, purchasing, selling, and minting). Experimental results demonstrate that NFTracker achieves an average F1-score of 0.9212 on identifying NFT behavioral traffic, outperforming state-of-the-art methods in encrypted tunnel scenarios.
Naufal Ziyaadaturrahman
No abstract is available for this record.
Huijuan Wang, Dongfang Zhang
No abstract is available for this record.
Thanh Trung Nguyen, Minh Thà nh Tạ
No abstract is available for this record.
Mohammad Javad Jannati, Abolfazl Iraninasab, Mehrshad Eskandarpour
As blockchain adoption accelerates, smart contracts have become attractive targets for attackers, often resulting in significant financial losses. While many studies focus on well-known vulnerabilities like reentrancy or integer overflows, weaknesses in pseudo-random number generation (PRNG) remain a persistent and critical challenge despite their role in decentralized applications such as lotteries, games, and token distribution. In Ethereum, randomness is often derived from predictable environmental variables like block timestamps or sender addresses, making these systems vulnerable to manipulation. This paper presents a rigorous investigation into PRNG vulnerabilities in Ethereum smart contracts and introduces two practical attack strategies. The first method relies on brute-force contract deployment to obtain a desired output, incurring high gas costs. The second approach leverages the CREATE2 opcode to precompute candidate contract addresses off-chain, reducing gas usage by over 90%. However, since final outcome prediction depends on block.timestamp at execution time, attack success is contingent on network timing stability and validator behavior. Through formal analysis and empirical evaluation on a controlled local test network, we demonstrate success rates of 100% for Method 1 and 98% for Method 2 under fixed-timestamp conditions. Under simulated live-network congestion, Method 2 success drops to 87% due to block.timestamp sensitivity. Our findings highlight the urgent need for secure randomness solutions, such as verifiable random functions (VRFs) and decentralized randomness beacons. Without adopting such mechanisms, blockchain applications across Ethereum and other EVM-compatible platforms remain exposed to critical security risks.
Pedro Cosme
No abstract is available for this record.
Mingzheng Lv, Chen Liang, Baokun Zheng, Tianqing Zhu · 7 authors
The exponential growth of connected devices and embodied intelligent systems in B5G and 6G networks demands secure, adaptive, and autonomous communication among distributed agents. However, ensuring privacy-preserving coordination among these Agentic AI systems remains a major challenge, particularly in decentralized environments where transparency conflicts with confidentiality. To address this issue, we propose a Smart-contract-based Embodied Covert Agent Communication Architecture (SECA), which integrates Ethereum election contracts with image steganography to enable covert, high-bandwidth communication among intelligent agents. In this framework, Blockchain-based agents utilize candidate images as visual carriers to embed encrypted messages, achieving imperceptible data exchange during on-chain interactions. We further design a Stackelberg Minimal Control Algorithm (SMCA) that enables adaptive manipulation of voting agents to ensure communication reliability with minimal control cost. Experimental results demonstrate that our approach achieves a transmission bandwidth up to 103× higher than ORIM-based covert channels and passes multiple detection benchmarks (K-S and χ2tests), all without incurring additional gas costs. This work provides a foundational perspective for secure Agentic AI communication frameworks, bridging embodied intelligence, decentralized networking, and covert information transmission in emerging 6G environments.
Massimo Franceschet, Enrico Bozzo
Token-based voting systems are increasingly adopted in digital governance contexts such as decentralized autonomous organizations and participatory budgeting, yet their standard aggregation rules often lead to undesirable outcomes, including oligarchic dominance or voter apathy. This paper introduces a general mathematical framework for token-based voting that interpolates between one-person-one-vote and one-token-onevote paradigms through the notion of radical voting functions. These functions map voting tokens to actual votes via concave transformations that preserve incentives for participation while compressing excessive voting power. We formalize consensus as an aggregation of transformed votes and study its structural properties using tools from convex analysis and majorization theory. We show that radical voting functions reward broad and evenly distributed support and penalize highly concentrated voting patterns, thereby favoring pluralistic outcomes over individualistic ones. Quadratic voting emerges as a special case within this framework, characterized by linear marginal voting costs. The analysis is extended to account for voter heterogeneity by incorporating similarity measures into the consensus function, linking voting outcomes to diversity among participants. Overall, the framework provides a principled foundation for designing voting mechanisms that balance merit, inclusiveness, and resistance to capture in token-based governance systems.
Ravinjeet Singh
Blockchain-based voting systems provide transparency and auditability but introduce significant privacy risks due to publicly observable metadata. Existing approaches rely on mixnets or heavy cryptographic primitives to achieve anonymity, resulting in high computational overhead and limited scalability. In this paper, we propose a novel privacy-preserving voting protocol that eliminates the need for full ciphertext mixnets by introducing a selective metadata mixing mechanism. Our protocol combines zero-knowledge proofs for vote validity, homomorphic encryption for confidential aggregation, and randomized metadata transformations to achieve unlinkability. We formalize security properties including ballot secrecy, unlinkability, and end-to-end verifiability, and prove security under standard cryptographic assumptions. We further provide a gas-aware smart contract model and evaluate scalability for elections with one million voters under Layer-2 rollup deployment. Our results show that the proposed protocol reduces anonymization complexity from O(n log n) to O(n) while maintaining strong privacy guarantees.
Samuel A. Ughili, Joshua U. Ngwuoke
Traditional electoral systems exhibit critical vulnerabilities including vote manipulation, centralized points of failure, and compromised transparency that undermine democratic integrity. This research presents BLOCKELECT, a decentralised blockchain-based secure voting system designed to address these fundamental challenges. The system employs Ethereum smart contracts written in Solidity to enforce immutable voting rules, Web3.js for blockchain integration, and MetaMask wallet authentication for secure voter verification. The proposed architecture implements dual interfaces for voters and electoral commissions, with distributed consensus mechanisms ensuring real-time transaction validation. Smart contracts automatically enforce electoral rules while maintaining cryptographic immutability of all voting transactions. The decentralised design eliminates single points of failure by distributing vote storage and validation across multiple network nodes. System validation employed comprehensive testing including unit, integration, system, and security testing methodologies. Results demonstrate successful prevention of vote tampering, elimination of double voting, and provision of transparent, auditable election results. Implementation utilised Truffle framework, Ganache blockchain simulation, and Node.js back-end services following an Agile Prototype-based Iterative Development methodology. This research demonstrates the feasibility of blockchain technology in creating trustworthy electoral systems, indicating that blockchain-based voting represents a viable solution for enhancing democratic processes while addressing persistent challenges of electoral fraud and lack of public confidence in traditional voting mechanisms.Traditional electoral systems exhibit critical vulnerabilities including vote manipulation, centralized points of failure, and compromised transparency that undermine democratic integrity. This research presents BLOCKELECT, a decentralised blockchain-based secure voting system designed to address these fundamental challenges. The system employs Ethereum smart contracts written in Solidity to enforce immutable voting rules, Web3.js for blockchain integration, and MetaMask wallet authentication for secure voter verification. The proposed architecture implements dual interfaces for voters and electoral commissions, with distributed consensus mechanisms ensuring real-time transaction validation. Smart contracts automatically enforce electoral rules while maintaining cryptographic immutability of all voting transactions. The decentralised design eliminates single points of failure by distributing vote storage and validation across multiple network nodes. System validation employed comprehensive testing including unit, integration, system, and security testing methodologies. Results demonstrate successful prevention of vote tampering, elimination of double voting, and provision of transparent, auditable election results. Implementation utilised Truffle framework, Ganache blockchain simulation, and Node.js back-end services following an Agile Prototype-based Iterative Development methodology. This research demonstrates the feasibility of blockchain technology in creating trustworthy electoral systems, indicating that blockchain-based voting represents a viable solution for enhancing democratic processes while addressing persistent challenges of electoral fraud and lack of public confidence in traditional voting mechanisms.
Sukhvinder Singh Bamber, Rajeev Kumar Dang
Voting is a cornerstone of democracy, enabling individuals to choose their leaders and influence decisions shaping their communities and future. Traditional voting systems, however, face numerous challenges, such as long queues, paper-based inefficiencies, and security vulnerabilities. To address these issues, blockchain technology has emerged as a transformative solution, leveraging its decentralized and secure infrastructure. This paper presents a blockchain-based e-voting system aimed at enhancing accessibility, security, and efficiency. By utilizing the Ethereum blockchain and smart contracts, the system ensures transparency, immutability, and tamper-proof vote recording. Furthermore, the integration of AI-powered facial recognition technology reinforces identity verification, guaranteeing that only authorized voters participate. Comprehensive testing, including simulations and stress analyses, confirms that the proposed model enhances the voting process by offering a secure, user-friendly, and reliable digital platform. This research highlights the potential of combining blockchain and AI to modernize voting systems, fostering trust and inclusivity in democratic processes. This paper introduces a blockchain-based e-voting system that simplifies the voting process while ensuring maximum security and trust. By using the Ethereum blockchain and smart contracts, votes are recorded and verified securely, leaving no room for manipulation. To make the system even more robust, AI-powered facial recognition is integrated to confirm voter identity, ensuring only eligible individuals can participate. The system has been tested extensively to ensure it’s not only secure but also easy to use, providing a seamless experience for voters. This combination of blockchain and AI has the potential to revolutionize voting, making it fairer, more inclusive, and efficient for everyone.
Priya M. S., Sangeetha Jose, Jino Joseph
Online voting with blockchain technology is a decentralised and secure live-voting system which can be implemented using an Ethereum blockchain. Our proposed blockchain-based voting system (BVote) uses the Ethereum blockchain technology to overcome the issues of the existing voting system, such as vote tampering, double voting, and hacking. Our system offers several benefits including increased security, transparency, and immutability. The immutability of blockchain ensures that once a vote is recorded, it cannot be altered or deleted, thereby enhancing the integrity of the election process. Additionally, voting and counting occur simultaneously, thereby providing partial results. Double voting is addressed using a unique digital identity for each voter that is verified in the blockchain network. To authenticate the user identity, each transaction should be digitally signed using a private key. This ensures that only voters can access and use their digital identity to cast a vote. To ensure the privacy of the voter, the data are hashed using a Secure Hash Algorithm. To ensure the anonymity of the voter, the vote is encrypted to break the link between voter and their vote. This helps to protect voters’ privacy and prevents attempts to trace their votes. By utilising the Elliptic Curve Digital Signature Algorithm, a digital signature is generated for each transaction that occurs during the voting process. This ensures the authenticity of the data stored on the blockchain and prevents any unauthorised modifications or tampering of the data, which further improves security.
Haotian Deng, Mengxuan Liu, Chuan Zhang, Wei Huang · 6 authors
Online harassment, incitement to violence, racist behavior, and other harmful content on social media can damage social harmony and even break the law. Traditional blocklisting technologies can block malicious users, but this comes at the expense of identity privacy. The anonymous blocklisting has emerged as an effective mechanism to restrict the abuse of freedom of speech while protecting user identity privacy. However, the state-of-the-art anonymous blocklisting schemes suffer from either poor dynamism or low efficiency. In this paper, we propose $\mathsf{ShadowBlock}$, an efficient dynamic anonymous blocklisting scheme. Specifically, we utilize the pseudorandom function and cryptographic accumulator to construct the public blocklisting, enabling users to prove they are not on the blocklisting in an anonymous manner. To improve verification efficiency, we design an aggregation zero-knowledge proof mechanism that converts multiple verification operations into a single one. In addition, we leverage the accumulator's property to achieve efficient updates of the blocklisting, i.e., the original proof can be reused with minimal updates rather than regenerating the entire proof. Experiments show that $\mathsf{ShadowBlock}$ has better dynamics and efficiency than the existing schemes. Finally, the discussion on applications indicates that $\mathsf{ShadowBlock}$ also holds significant value and has broad prospects in emerging fields such as cross-chain identity management.
A.K. SarveshKrishna, M. Anbarasan, M. Suguna
As the world transitions toward digital-first governance and civic participation, ensuring the security and integrity of voting systems has become a critical concern. Traditional evoting mechanisms, although convenient, suffer from a range of vulnerabilities - including voter impersonation, double voting, identity leaks, and tampering by insiders or external adversaries. ECC-EXONUM-eVOTING was previously proposed to mitigate many of these issues through elliptic curve cryptography (ECC), Zero-Knowledge Proofs (ZKP), and Exonum private blockchain. In this paper, we extend the capabilities of ECC-EXONUMeVOTING by integrating two novel modules aimed at enhancing both system intelligence and accessibility. First, we implement an AI-based fraud detection system using unsupervised anomaly detection techniques that proactively identify and block fraudulent voting behaviors in real time. Second, we introduce a secure offline voting architecture designed for voters in remote or lowconnectivity regions, using QR-based tokenization and Merkle-root-based integrity proofs for delayed blockchain synchronization. Through simulations, algorithmic validation, and comparative analysis, we demonstrate how these enhancements significantly increase the robustness, scalability, and real-world applicability of blockchain-based voting systems.
Jhuma Dutta, Mainak Pal, Subhas Barman, Matangini Chattopadhyay · 5 authors
New-generation traffic violation systems are often plagued by issues related to data tampering, transparency, and poor record-keeping. To overcome these limitations, this paper proposes EtherFineChain, a blockchain-based framework for traffic violation logging and cryptocurrency penalty enforcement utilizing smart contracts. The system records decentralized, tamper-proof and verifiable storage of key violations data like vehicle number, evidence references for legitimate stakeholders. A working prototype has built and deployed on the simulated environment - Ganache, enabling automated fine deduction and immutable record keeping. Experimental evaluation shows that the average transaction latency is 134.48 ms and transaction throughput is 7.43 transactions/sec(approx.), and handles over 500 records per hour under simulation. Although the current version is founded on pre-processed inputs, the architecture is designed to support real-time detection and automated pipelines in upcoming versions. EtherFineChain provides a scalable and independent foundation for digital traffic management, laying the groundwork for secure integration into smart-city infrastructures.
M. Anwar Hossain, Ahsan Ullah, Noshin Un Noor, Rafat Md. Shahriar Hoque Joy · 7 authors
As traditional and electronic voting methods are being increasingly scrutinized for security, transparency and availability, blockchain has emerged as a way to address some of these concerns. This paper describes a blockchain-based decentralized voting system which employs Ethereum smart contracts for controlling the voting procedure based on the features and characteristics of the public blockchain, such as security, immutability and transparency, hence guaranteeing a secure and fair electoral system. The voting process is automated and secured, thus a provable way to the votes casting or votes counting. Security scalability and user authentication are used to verify the system. The knowledge base system provides secure electronic voting, transparency of elections, builds trust among voters due to a real-time computational claimability of election results. This paper suggests a framework for building a blockchain-based voting system on a larger scale and more reliable than the existing voting system.
Davide Mancino, Davide Rezzoli
How users adapt after being sandwiched remains unclear; this paper provides an empirical quantification. Using transaction level data from November 2024 to February 2025, enriched with mempool visibility and ZeroMEV labels, we track user outcomes after their n-th public sandwich: (i) reactivation, i.e., the resumption of on-chain activity within a 60-day window, and (ii) first-time adoption of private routing. We refer to users who do not reactivate within this window as churned, and to users experiencing multiple attacks (n>1) as undergoing repeated exposure. Our analysis reveals measurable behavioral adaptation: around 40% of victims migrate to private routing within 60 days, rising to 54% with repeated exposures. Churn peaks at 7.5% after the first sandwich but declines to 1-2%, consistent with survivor bias. In Nov-Dec 2024 we confirm 2,932 private sandwich attacks affecting 3,126 private victim transactions, producing \$409,236 in losses and \$293,786 in attacker profits. A single bot accounts for nearly two-thirds of private frontruns, and private sandwich activity is heavily concentrated on a small set of DEX pools. These results highlight that private routing does not guarantee protection from MEV extraction: while execution failures push users toward private channels, these remain exploitable and highly concentrated, demanding continuous monitoring and protocol-level defenses.