Blockchain Papers

Swagatika Sahoo, Raju Halder, Samrat Mondal

No abstract is available for this record.

Princi, Pratyush Pratyush, Chakridhar Reddy Lokireddy, Renu Mishra

There has been a major cause of concern, especially concerning the integrity of political financing, since the idea of existing electoral bonds lacks transparency, traceability, and accountability. Although these systems are meant to help formalize political contributions, they usually help to allow anonymous contributions and disclosure at will, violating both the trust of a population and democratic responsibilities. The paper entails the design, development, and flow of ElectraChain, a decentralized system and blockchain-based electoral bond management platform. With the help of smart contracts and privacy-preserving cryptographic schemes like Zero-Knowledge Proofs (ZKPs), ElectraChain will preserve the tamper-proofness of bond transactions recording and preserve donor anonymity. The architecture proposed has secure KYC processes included, automated compliance procedures, and publicly available dashboards to go to the next level of transparency without any breach of privacy. Blockchain technology has been a device that allows the development of a viable prototype that supports the feasibility, security, and scalability of the system. The paper also assesses the technical parameters of the system and comments on the possibilities of the use of such a system nationally, which becomes a major step towards transparent, accountable, and technology-driven political financing in democracies.

N.Shanmuga Priya, M. A. Gopinath, V Gunaseelan., K Guruganesh

This paper presents a new decentralized e-voting architecture designed to create tamper-proof, transparent, and secure election systems using the blockchain and smart contracts. The solution uses a permissioned blockchain structure that is private and Hyperledger Fabric-based in an effort to improve scalability and privacy while retaining the inherent features of decentralization. A zero-knowledge proof (ZKPs) based novel authentication method is implemented to provide eligibility checking and safeguard the privacy of the voter. The smart contracts are aimed at automating ballot tallying, publishing results, and checking their validity. The system is also resistant to traditional channels of attack such as denial-of-service, vote tampering, and voting redundancies based on its distributed ledger and consensus algorithms. A light-weight online interface has been implemented in an effort to promote usability and accessibility, thereby showing an unproblematic voter experience. Experimental results have now made it feasible to deploy the system in organizational and government voting applications, thereby testing its effectiveness within these settings. This method represents a tangible step towards an entirely reliable digital democracy.

Banri Yasui, Yutaka Watanobe

This paper proposes a hybrid access control system that integrates the usability of Web2 authentication (Google Login) with the transparency and integrity of Web3 technologies (blockchain and smart contracts). The system enables users to authenticate via their existing Google accounts without managing crypto wallets or private keys, while access permissions are securely recorded on-chain through smart contracts. To ensure cryptographic key security without relying on a centralized authority, the design incorporates Distributed Key Management (DKM). This approach addresses the challenge of balancing usability with verifiability in data access control. By embedding decentralized guarantees within a centralized web service interface, the system enables practical and transparent access control. The proposed architecture demonstrates the potential for a general-purpose, auditable module that facilitates user-consented data sharing with third parties.

Geetanjali Popat Rokade, Ruturaj Hendre, Vaishnavi Deshmukh, Sejal Wavhal · 5 authors

Integration of Federated Learning (FL) with Blockchain technology to decentralized privacy-preserving, and scalable framework for strengthening cybersecurity. As cyber threats like ransomware, malware, and network intrusions grow in complexity, there is an increasing need for collaborative threat detection and mitigation. However, traditional collaborative approaches often involve sharing sensitive information across organizations, raising significant privacy concerns and regulatory challenges under frameworks like GDPR and HIPAA. FL works to solve these problems through enabling multiple entities to work together on training machine learning models without sharing their original information. Despite its advantages, FL faces challenges such as the risk of model tampering, trust deficits between participants, and dependence on a centralized server for model aggregation. To overcome these limitations the Blockchain technologies will be in used so blockchain technology provides a distributed, transparent, and non-mutable ledger that safely manages FL operations. It helps preserve the accuracy and trustworthiness of model updates via smart contracts along with consensus mechanisms, bypassing the requirement fora central aggregator. In addition, blockchain enables incentivization by introducing token-based rewards, encouraging active participation in collaborative threat detection networks. Privacy- preserving techniques to boost information security, techniques like differential privacy and homomorphic encryption are also put into practice. Such a integration of FL and blockchain is particularly impactful in securing distributed systems such as IoT devices, critical infrastructure, and enterprise networks, where privacy, trust, and scalability are crucial. This project aims to demonstrate the practical implementation of this framework, paving the way for adaptive and globally scalable cyber security systems to combat evolving threats.

David Chaum, Richard Carback, Jeremy Clark, Liu Chao · 11 authors

Abstract We revisit “silent coercion” where an adversary gains access to a voter’s credential without the voter’s knowledge in an E2E verifiable, coercion-resistant Internet voting system. We argue that in this setting, casting an intended vote is impossible since the cryptographic backend can no longer distinguish the voter and adversary. However, we affirm that the voter can still act to nullify adversarial ballots, which is preferable to inaction. We provide a new instantiation of nullification using zero-knowledge proofs and multiparty computation, which improves on the efficiency of the current state-of-the-art. We also demonstrate an example voting system—VoteXX—that uses nullification. Our nullification protocol can complement new and existing techniques for coercion resistance (which all require voters to hide cryptographic keys from the coercer), providing a failsafe option for voters whose keys leak.

Chakridhar Reddy Lokireddy, Princi, Pratyush, Renu Mishra · 5 authors

The combination of voting bond financing transparency issues and misappropriation issues along with insufficient financial responsibility oversight has exposed the requirement for advanced transparent funding solutions. ElectraChain offers blockchain technology that develops a new political funding structure which maintains donation safety alongside full transparency and donor identity protection. ElectraChain uses Distributed Ledger Technology (DLT) in order to establish a tamper-proof decentralized system for transaction recording which surpasses corrupted conventional systems that allow selective disclosure. This paper explains the fundamental framework alongside technological infrastructure that ElectraChain adopts along with its consequences on policy making through an analysis of its election bond monitoring capacity. This study aims to create progress in electoral financing accountability by uniting privacy protection with transparency oversight in order to enhance democratic institution integrity.

Jingjuan Yu, Shundong Li, Ping Luo, Jiawei Dou

Elections and referendums play a vital role in a democratic society, which enable individuals to make collective decisions. In the Internet information era, electronic voting has replaced traditional paper voting. However, the centralized architecture of the electronic voting system is vulnerable to attacks and the voting records can be easily changed or even deleted. Blockchain, as a decentralized and trustworthy distributed network, offers new means for electronic voting systems. Current blockchain- based voting systems still face several challenges: they cannot achieve full verifiability in self-tallying, cannot tolerate invalid or abstained ballots, and cannot prevent Sybil attacks either. To address these challenges, we use some cryptographic primitives to construct a blockchain- based decentralized self-tallying verifiable referendum scheme to provide a transparent and secure remote electronic voting system. First, we use range zero-knowledge proofs to verify the ballot content, and for the first time, propose a novel method using bilinear pairing to verify decryption results, which significantly reduces computational burden and gas consumption during verification. Second, we ingeniously combine a threshold decryption system with a blockchain-based deposit mechanism: invalid or abstained ballots are excluded from the tally, and voters casting such ballots are incentivized to publish their partial private keys through the deposit mechanism, ensuring their exit from the decryption process without disrupting the election. We also establish an innovative access mechanism for smart contract that effectively prevents Sybil attacks. Theoretical analysis and experimental results demonstrate that our system is secure, feasible, and efficient.

Bruno M. F. Ricardo, Lucas C. Cardoso, Leonardo T. Kimura, Marcos A. Simplício · 5 authors

In 2023, Barreto and Zanon proposed a three-round Schnorr-like blind signature scheme, leveraging zero-knowledge proofs to produce one-time signatures as an intermediate step of the protocol. The resulting scheme, called BZ, is proven secure in the discrete-logarithm setting under the one-more discrete logarithm assumption with (allegedly) resistance to the Random inhomogeneities in a Overdetermined Solvable system of linear equations modulo a prime number p attack, commonly referred to as ROS attack. The authors argue that the scheme is resistant against a ROS-based attack by building an adversary whose success depends on extracting the discrete logarithm of the intermediate signing key. In this paper, however, we describe a distinct ROS attack on the BZ scheme, in which a probabilistic polynomial-time attacker can bypass the zero-knowledge proof step to break the one-more unforgeability of the scheme. We also built a BZ variant that, by using one secure hash function instead of two, can prevent this particular attack. Unfortunately, though, we show yet another ROS attack that leverages the BZ scheme’s structure to break the one-more unforgeability principle again, thus revealing that this variant is also vulnerable. These results indicate that, like other Schnorr-based strategies, it is hard to build a secure blind signature scheme using BZ’s underlying structure.

Arash Habibi Lashkari, Sepideh HajiHosseinKhani, J.M.V. Duarte, Isabella Lopez · 6 authors

With the shift from Centralized Finance (CeFi) to Decentralized Finance (DeFi), financial transactions have become trustless and self-executing through blockchain platforms, creating new opportunities while exposing the ecosystem to significant fraud risks. However, due to the lack of centralized oversight and the vulnerabilities in the blockchain platforms, DeFi transactions still face several security challenges, including fraud, identity theft, insider threats, and data breaches. Various methods, including regulatory frameworks, machine learning (ML), and deep learning (DL) techniques, are employed to detect these threats, particularly fraud, in DeFi transactions. Although these approaches help identify fraudulent activities, they face challenges related to accuracy and zero-day attacks due to insufficient data and the complexity of emergingfraud patterns. This study presents a novel approach for detecting and profiling fraud attacks, including zero-day ones in DeFi transactions, thereby eliminating the reliance on wallet transaction history, a limitation that previous research has heavily depended on. The proposed approach leverages two key components: a novel analyzer named DeFiTransLyzer (V1.0) and an Advanced Genetic Algorithm (AGA) for fraud transaction profiling. DeFiTransLyzer extracts 79 features from transaction and wallet data. At the same time, the AGA incorporates advanced techniques, including Penalized Fitness Evaluation, Elite Retention Strategy, Dynamic Mutation Rate, and dynamic generation, to create precise fraud profiles. By focusing solely on transaction features, the model ensures that all fraudulent activities, including zero-day ones, initiated within the first transaction of a new account can be effectively detected, without relying on prior wallet activity. To address the scarcity of comprehensive validation datasets, we introduce BCCCDeFiFraudTrans-2025, which comprises 1,026,867 annotated Ethereum transaction samples from the DeFi ecosystem. Additionally, the study establishes two taxonomies for systematic classification, covering the literature on fraud detection and profiling methods. Experimental results demonstrate that the proposed method achieves superior accuracy, precision, and efficiency while offering interpretability through its profiling mechanism. These promising outcomes highlight the potential of AGA profiling to enhance the detection and identification of fraudulent activities, including zero-day ones within DeFi transactions, contributing to the security and resilience of blockchainbased financial systems.

Tien-Chen Liu, Yang Liu, Dawei Zhang, Chang Chen · 5 authors

No abstract is available for this record.

Arpita Patil, Akanksha Mane, Poonam Todkar

Abstract: Ensuring the integrity, privacy and accessibility of electoral system remains a critical global challenge. This paper proposes a secure blockchain based e-voting framework enhanced with anti-spoofing facial recognition for voter authentication and zero-knowledge proofs to preserve voter anonymity while enabling verifiable results. The proposed system integrates seamlessly with existing election infrastructure, allowing transparent vote recording on a tamper-resistant distributed ledger while preventing identity fraud through advanced biometric anti-spoofing techniques. Zero Knowledge Proofs enable vote verification without revealing individual choices, ensuring both privacy and trust. By combining blockchain’s immutability, biometric security and cryptographic privacy guarantees, this approach addresses vote tampering, impersonation, and transparency concerns, offering a scalable , auditable, and privacy-preserving solution for modern elections. Keywords: Blockchain, E-Voting, Anti-Spoofing, Facial Recognition, Zero Knowledge Proofs, Election Security, Privacy preserving systems.

Madhavi Repe, Dr. Nilakshi Rajule, Vandana Katarwar, Ankita Bombatkar

In response to the growing demand for secure and transparent digital elections, this paper presents a blockchain based Smart Election System that leverages advanced cryptographic and artificial intelligence techniques to ensure privacy, scalability, and verifiability. The proposed system integrates multi-factor authentication, Zero-Knowledge Proofs (ZKPs), smart contracts, and a sharded blockchain ledger to enable real-time, tamper-proof voting. Additionally, an Artificial intelligence based anomaly detection module monitors voting behaviour to flag suspicious patterns.Experimental evaluation demonstrates that the system achieves an average vote transaction latency of 1100ms with sharding, compared to 2800ms without it. The throughput increases from 130 to 220 votes/sec when sharding is enabled. ZKP integration ensures privacy at the cost of a moderate increase in validation time from 130ms to 230ms. The anomaly detection model, based on supervised learning, attained 92% precision, 88% recall, and an F1-score of 90%, ensuring proactive fraud detection. These results confirm the system’s effectiveness in delivering a smart scalable, private, and trustworthy e-voting platform suitable for national and institutional elections.

Taaniel Kraavi, Jan Willemson

This paper studies the practical aspects of adding zero-knowledge proofs of vote correctness to Internet voting, specifically to the IVXV system used in Estonia. We discuss various available alternatives and present a concrete instantiation based on Bulletproofs together with implementation details and benchmarking results. As IVXV currently uses the ElGamal cryptosystem with a 3072-bit prime modulus for vote encryption, but Bulletproofs work most efficiently on elliptic curves, a group switching solution is also implemented and benchmarked. Despite all the extra work required, our solution is very performant and well capable of sustaining the load of votes, even during peak vote submission periods.

Kombou Victor, Qi Xia, Hu Xia, Jianbin Gao · 9 authors

Non-fungible token (NFT) markets present a dual analytical challenge: integrating heterogeneous data modalities (high-dimensional visual features and discrete transaction sequences) while preserving privacy for sensitive wallet addresses and trading strategies. Current approaches analyze visual attributes or transaction patterns in isolation, missing critical value drivers from cross-modal interactions. Meanwhile, existing multimodal techniques lack formal privacy guarantees, exposing participants to inference attacks. This article introduces PrivaMod, a privacy-preserving Bayesian framework that addresses these limitations through uncertainty-aware multimodal fusion. Our approach implements precision-weighted Bayesian fusion that dynamically adjusts modality contributions based on quantified uncertainty levels, while integrating Rényi Differential Privacy throughout the pipeline via calibrated noise injection and adaptive gradient clipping. Evaluated on 167,492 CryptoPunk transactions, PrivaMod achieves a market efficiency score of 0.874 and R 2 of 0.912, outperforming existing methods by 13.4% through superior cross-modal integration while maintaining strong privacy guarantees ( \(\varepsilon\) = 0.08, \(\delta\) = 1e-5) with membership inference attack success rates near random guessing (53.4%). The system demonstrates that privacy-preserving techniques can enhance rather than compromise analytical performance, establishing a foundation for responsible market analysis. To ensure reproducibility, we release our code, preprocessed datasets, and model checkpoints with detailed documentation and scripts to replicate all experiments. PrivaMod is available at https://github.com/kvjunior/PrivaMod/blob/main/README.md .

Samuel A. Ughili, Joshua U. Ngwuoke

<b>Abstract</b><br>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.

Priyanka Kokare, Deepali Vora, Komal Ghadage, Pooja Dhare · 5 authors

Due to digitalization and AI technology, whole world is moving towards the modernization of all digital applications. As there is a growing demand for conducting elections online to increase voting percentage and reduction in human resource need and time. Till date, India had not conducted any elections online, but there is big necessity to do this digitally as AI World is beginning now. We developed online voting system by adding Rivest Shamir Adleman-Key Encapsulation Mechanism (RSAKEM), Advanced Encryption Standard (AES) with Blockchain technology. The framework used to design a safe, attack proof and translucent methodology which will store user votes in more prominent secured way. Ethereum block chain with Ganache is used for local development to achieve immutability and transparency. Voting process is initialized by written smart contracts based on solidity. Solidity is used for registration of voters and counting of votes. A two factor authentication (2FA) and email verification through one time password (OTP) is used to guarantee the voter identification. Interplanetary file systems (IPFS) are used to store list of voters and votes casted by voters. The registration of voters, choices of ballots and authentication is made so simple. Java spring boot is used to develop backend which was used by Web3j. This backend was used to offer block chain interactions, authentication, and encryption. The framework will be useful for governmental organizations, multinational corporations, Educational institutions and commercial associations for conducting their elections smoothly. These new framework with respect of higher throughput achieved major outcomes with respect to security principles as confidentiality is preserved, integrity is achieved through Metamask and availability is maintained.

Trinh Gia Huy, Luong Nguyen Thanh Nhan, Nguyen Tan Cam

No abstract is available for this record.

Alice Niyonsaba, Dr.KN Jonathan, Djuma Sumbiri

This paper presents a comprehensive framework for deploying a blockchain-based electronic voting system in Rwanda to address challenges of transparency, security, and public trust in electoral processes. Through detailed analysis of the current Rwandan electoral infrastructure and limitations, we propose a multilayered blockchain architecture that incorporates advanced cryptographic techniques, a national digital identity framework, and mobile accessibility features tailored to Rwanda's unique socio-economic landscape. Our proposed system leverages permissioned blockchain technology with a hybrid consensus mechanism to ensure the immutability of vote records while maintaining voter privacy through zero-knowledge proofs. The paper further discusses implementation challenges specific to Rwanda's context, including digital literacy (UNESCO, 2019), infrastructure limitations, and regulatory considerations. Our findings suggest that progressive, phased implementation of blockchain voting systems can significantly enhance electoral integrity while maintaining cultural and technological accessibility for Rwanda's diverse population.

Pushpakumar R, S. Sathishkumar, G. Dheepak, G. Amirthayogam · 6 authors

Due to the increased levels of cryptocurrency transactions, novel frameworks are required to detect fraud in the real-time and make decentralized finance safe. It is suggested in this paper that SecureChainNet, which encompasses both CNNs and LSTM networks, would aid in the detection of fraud in cryptocurrency networks. The first phase involves the use of CNNs to discover difficult patterns within the structured transactions data that is largely undetected by traditional means. Subsequently, the transaction sequence is analyzed using LSTM module, which enhances the system to identify fraud patterns thus developing over time. When used together with blockchain, all the decisions made by a model are recorded into an immutable log, and the following auditing process reconfirms decentralized data verification and increased trust. Experimentally, SecureChainNet has been determined to possess a significantly higher degree of accuracy, precision, and recall compared to other methods when putting it to use with the real blockchain data. Additionally, the system has the capability of operating almost in real-time and so it can be used to trade cryptocurrencies being traded. The analysis notes that deep learning in conjunction with blockchain security has the potential of creating intelligent and dependable financial fraud systems.

Isaac Osei Asante, Libing Wu

No abstract is available for this record.

Jianhuan Wang, Bin Xiao

No abstract is available for this record.

Esha Tyagi, Arun Ahirwar, Deepak Khandelwal, Ashika Goyal · 5 authors

E-voting systems are gaining ground in international space, considering the versatility embedded in them in terms of making voting far more accessible and less expensive in logistics. Such systems, however, pose much higher security issues regarding privacy, especially while using biometric details, such as facial recognition, to verify the voter. The paper describes an e-voting system based on the blockchain architecture coupled with advanced privacy-preserving techniques like Zero-Knowledge Proofs (ZKPs) and end-to-end encryption. Voters have shied away from adopting this voting system as it is ensured by decentralization, transparency, and tamper-proofness, all at the cost of their identity and biometric data. In addition to this, this blockchain-based system also ensures that no one control is there for the voting process by any particular entity; hence, it guarantees impartiality. Because of ZKPs, it is ensured that voter verification can take place without exposing sensitive personal data in nature. Unlike the traditional e-voting-on-a-blockchain models, ours includes a dynamic key rotation mechanism for further anonymity of votes, with a multi-layer encryption to protect voter credentials even against potential quantum computing threats. Further, this blocking-based system makes sure that not a single entity is controlling the entire process of voting, thus guaranteeing impartiality. Voter verification takes place through the means of ZKP without any sensitive personal information being revealed. As a result, end-to-end encryption keeps intact the integrity of a vote from the moment it is cast until it is finally counted, further building confidence in the election process. It turns out to be a safe and scalable solution for future worldwide adoption of evoting.

Kohei Kawaguchi, Shunya Noda, Junpei Komiyama

Proof-of-Work cryptocurrencies employ miners to sustain the system through algorithmic reward adjustments. We develop a stochastic model of the multicurrency mining market and identify conditions for stable transaction speeds. Bitcoin's algorithm requires hash supply elasticity $\le$ 1 for stability, while ASERT remains stable for any elasticity and can be interpreted as a form of stochastic gradient descent algorithm under a certain loss function. Interactions with other currencies can relax Bitcoin's stability requirements. Using a ``halving'' event, we estimate miners' hash supply elasticity and conduct counterfactual simulations. Our findings reveal Bitcoin's heavy reliance on low hash-supply elasticity and interactions with smaller cryptocurrencies, suggesting an algorithm upgrade is crucial for stability.