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2,071 results ¡ page 3 of 87
Garima Ratra, Akriti Kumari, Vimmi Malhotra
No abstract is available for this record.
N. Mohankumar, V. Sindhu, N. Nageswari, N. Silambarasan
Safe and transparent e-voting is becoming more and more important in modern democracies, as the confidence of citizens in electoral systems is determined by the issues of trust, privacy and scalability. Existing e-voting systems, however, have privacy, impersonation vulnerability, lack of transparency, and coercive weaknesses, and so they must be improved through cryptographic and identity solutions. In an attempt to provide security at these points, to propose a voting system that uses Aadhaar-linked decentralized identities together with iris scan biometrics to authenticate voters, zk-SNARKs to produce zero-knowledge proofs of voter eligibility without revealing their personal data, and homomorphic encryption to ensure ballot confidentiality and allow vote counting to be verifiably processed. Moreover, coercion resistance is ensured by a revoting mechanism, as only the last authenticated vote is included in the counting, thereby mitigating external pressure or vote-buying. The results demonstrate that the proposed design is capable to concurrently deliver strong authentication, biometric-based impersonation resistance, privacy preservation, end-to-end verifiability, and scalability in e-voting. In general, this framework eliminates major weaknesses of the old systems in addition to increasing voter confidence and integrity of the elections. The integration of decentralized identity, biometric iris recognition, and modern cryptography allows the model to provide a secure, transparent, and non-coercible framework of next-generation democratization procedures in India and can present an open-source, globally replicable solution with large-scale elections.
A. G. Ramakrishnan, Shubham Agarwal, Sharmila Kumari Selvanayagam, Kunwar P. Singh
As image generation models grow increasingly powerful and accessible, concerns around authenticity, ownership, and misuse of synthetic media have become critical. The ability to generate lifelike images indistinguishable from real ones introduces risks such as misinformation, deepfakes, and intellectual property violations. Traditional watermarking methods either degrade image quality, are easily removed, or require access to confidential model internals â making them unsuitable for secure and scalable deployment. We are the first to introduce ZK-WAGON, a novel system for watermarking image generation models using the Zero-Knowledge Succinct Non-Interactive Argument of Knowledge (ZK-SNARKs). Our approach enables verifiable proof of origin without exposing model weights, generation prompts, or any sensitive internal information. We propose Selective Layer ZK-Circuit Creation (SL-ZKCC), a method to selectively convert key layers of an image generation model into a circuit, reducing proof generation time significantly. Generated ZK-SNARK proofs are imperceptibly embedded into a generated image via Least Significant Bit (LSB) steganography. We demonstrate this system on both GAN and Diffusion models, providing a secure, model-agnostic pipeline for trustworthy AI image generation.
Manasa S. Desai, M. B. Nirmala, Yogesh Kumar, G. C. Varsha ¡ 6 authors
No abstract is available for this record.
Guohui Lan, Cheng Zhang
ABSTRACT This study investigates an audit data privacy protection mechanism based on blockchain technology and constructs a secure and efficient computational model. The system is designed to support practical domains such as medical record systems and financial audit platforms, ensuring data integrity, traceability, and confidentiality. Leveraging a distributed ledger and optimized consensus mechanism, the model automates data sharing and audit processes through smart contracts. A hybrid encryption approach is proposed, integrating RSA algorithm with chaos theory to enhance encryption complexity and randomness. Experimental resultsâconducted on realâworld medical audit dataâdemonstrate that, compared to baseline methods, the proposed scheme improves privacy protection by up to 50%, increases ciphertext complexity by 45%, and reduces encryption and verification time by approximately 20 s. The system also supports up to 500 concurrent users with a throughput of 583.49 requests/s, indicating strong scalability and efficiency.
Yuxi Wang, Lin Teng
No abstract is available for this record.
Tin Tironsakkul, Pradip Kumar Sharma
The advancement in smart mobility communication technology allows intelligent vehicles to interconnect and communicate with each other to improve traffic safety and efficiency. However, the highly dynamic nature of the smart mobility network and vehicle behaviour creates the requirement for effective authentication systems to establish secure and reliable communication between vehicles. The implementation of a reputation system has been proposed to establish trust among untrusted vehicles, where the reliability of a propagated message is assessed based on the reputation of the sender vehicle. Thus, preventing malicious vehicles from potentially broadcasting misleading messages that can cause accidents or disrupt the network. This paper proposes a novel decentralised and dynamic reputation management and computation model based on a consortium blockchain and a multi-signature smart contract. The implementation of blockchain and a smart contract provides a secure and transparent framework for registering vehicles, submitting events, voting feedback, evaluating reputation, and blocking malicious vehicles. To demonstrate the feasibility of the proposed model, we conducted security and performance analyses. The results demonstrate how our model can provide resistance against various attacks, such as data tampering, message forging, self-promotion, vote duplication, bad-mouth, onoff, time-dependent, and collusion attacks.
Mingwang Zhang, Liming Zhang, Tao Tan, Yang Zhao-jun ¡ 5 authors
ABSTRACT With the rapid advancement of autonomous driving, the privacy and credibility of highâdefinition (HD) maps, which serve as an essential foundation for driving safety, are receiving increasing attention. Traditional ciphertextâdomain digital watermarking technology encounters high computational overhead and risks of privacy leakage, making it challenging to balance data security, privacy protection, and trustworthiness verification. Against this background, a zeroâknowledge watermark (ZKW) algorithm based on compressed sensing is proposed. First, the highâprecision map data in OpenDrive format is dynamically encrypted using DNAâbased techniques to enhance data security and privacy. Secondly, to ensure the credibility of data verification, a zeroâknowledge watermark is generated using compressed sensing and embedded into the attribute values of ciphertextâdomain data as invisible characters. Experimental results demonstrate that the proposed ZKW scheme is commutative with the encryption scheme and can achieve zeroâknowledge proof (ZKP) in both ciphertext and plaintext domains. Furthermore, the scheme exhibits excellent robustness against various security threats, including geometric attacks, cropping attacks, and combined attacks.
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 blockchainâs 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.
M Savitha Devi, Ningthoujam Chidananda Singh, Thoudam Basanta Singh
Abstract - The explosion of Internet of Things (IoT) devices calls for the design of computationally light blockchain consensus mechanisms immune to quantum threats. The conventional consensus protocols such as Proof-of-Work (PoW) and Proof-of-Stake (PoS) may have quantum cryptanalysis and incur high computational overhead on resource-limited IoT devices. In this paper, we introduce QR-LightChain, a new quantum-robust light weight consensus algorithm with the combination of lattice-based cryptography and a brand-new Proof-of-Lightweight-Work (PoLW). Our proposal is based on formalism Learning With Errors (LWE) as a quantum resistant based scheme, also, but with the use of the adaptive difficulty tuning and energy efficient mechanism to validate the hashing. Experimental results show that QR-LightChain reduces the computational overhead by 52.3% with respect to traditional quantum-resistant approaches, while preserving security against both classical and quantum adversaries. The protocol shows good performance in IoT: The average block validation time of 1.2 sec is achieved and there is 40% less energy consumed than for current quantum-resistant consensus in the literature. Our work fills the important research challenge of providing 1 Post-Quantum Cryptography and Blockchain Modern internet of things (IoT) blockchain net- works are being developed in resource-constrained environments such as smart cities, while QCs Key Words: Quantum resistance, IoT blockchain, lightweight consensus, lattice-based cryptography, post-quantum cryptography, Proof-of-Lightweight-Work, resource-constrained devices
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 RĂŠnyi 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 .
R. Praveen Kumar, G. Gautham Kumar, Arun Amaithi Rajan, V. Vetriselvi ¡ 5 authors
Remote sensing and satellite imaging have become essential in various geological and surveillance applications. These systems often rely on cloud platforms for storing satellite and aerial images, introducing trust and security concerns, especially in sensitive domains like border surveillance, monitoring, and reconnaissance. Traditional cloud solutions are prone to data breaches and adversarial attacks, highlighting the need for a secure, end-to-end framework. To address this, we propose a comprehensive security architecture for storing and retrieving sensitive remote sensing images. Our system ensures confidentiality, integrity, and access control, while also resisting adversarial attacks during image retrieval. It adopts a three-phase structure: secure authentication, secure storage, and secure retrieval. Authentication is achieved using a combination of Zero-Knowledge Proof and Quantum Key Distribution, establishing a tamper-proof user verification process. In the storage phase, quantum-based cryptography secures the images, while a deep hashing model resistant to adversarial attacks enables efficient indexing and retrieval. A watermark embedding mechanism helps detect insider threats and support forensic tracking in case of data breaches. Evaluated on a remote sensing image dataset using various backbone networks, our system achieved a retrieval accuracy of 94.77%, outperforming existing models by 8â12%. The framework is well-suited for high-security environments, including military applications.
Mahendra Kumar Jhariya, Vasudev Dehalwar, Jyoti Bharti
No abstract is available for this record.
Abdullah Ayub Khan, Asif Ali Laghari, Hamad Al-Mansour, Leila Jamel ¡ 8 authors
The multimedia environment has undergone significant growth, particularly in the area of multimedia data and its migration to cloud platforms, which has raised issues about security, confidentiality, data integrity, and privacy protection. While Blockchain Distributed Ledger Technology (BDLT) offers decentralized trust and transparency the advent of Quantum Computing threatens classical cryptographic primitives, which make multimedia data increasingly vulnerable. This paper proposes a novel and secure framework that collaborates BDLT with quantum-resilient, mainly known post-quantum cryptographic schemes to ensure long-term data integrity and privacy preservation in cloud-based infrastructures. Due to this, the proposed solution enables secure, efficient, and transparent that helps in public auditing of multimedia content without compromising stakeholder confidentiality. It leverages Zero-Knowledge Proofs (ZKPs), lattice-based cryptography, and smart contract automation, which model fortifies data authenticity verification against quantum attacks. Simulation results illustrate the effectiveness of the proposed framework that achieves a 98.21% accuracy in data integrity verification, a 96.84% reduction in quantum vulnerability, and an 87.85% efficiency gain in auditing speed compared to classical BDLT-enabled platforms. In addition, privacy leakage in multimedia systems is reduced by 92.47% proving the frameworkâs robustness. This solution underscores the potential of synergizing BDLT, quantum secure cryptography, and cloud computing to build a future-proof solution for privacy-protected multimedia data management and public auditing.
Jia Liu, Mark Manulis
No abstract is available for this record.
Kentaro Sako, Shinâichiro Matsuo, Tatsuya Mori
We propose N-choice game (NCG), a decentralized method for generating pseudo-random numbers for smart contracts. NCG involves multiple participants, each of whom chooses a value between 0 and \(N-1\) and whose collective choices determine the generation of a pseudo-random number. The design of NCG has three key objectives: incentivizing participants to make random choices, assessing randomness in a decentralized environment, and achieving high operational performance. Implemented in Solidity and rigorously tested, NCG has shown remarkable effectiveness. Our results show that the randomness of the numbers generated by NCG is high and consistent, even under a strict NIST randomness test, provided that there is no collusion between the majority of participants. Not only is it impossible to customize the outputs generated by NCG, but it is also impractical to make them non-random. Therefore, it is rational to engage NCG for the purpose of rewards rather than the output values it produces. Selecting values in a way that is not predicted by other nodes yields the highest expected value, and NCG incentivizes random selection. Furthermore, NCG demonstrates a significant performance advantage, being up to 158 times faster at generating random numbers than the existing Random Bit Generator framework [ 3 ]. This efficiency underscores NCGâs potential to enhance blockchain applications.
Franco Frattolillo
Watermarking protocols represent a possible solution to the problem of digital copyright protection of content distributed on the Internet. Their implementations, however, continue to be a complex problem due to the difficulties researchers encounter in proposing secure, easy-to-use and, at the same time, âtrusted third partiesâ (TTPs)-free solutions. In this regard, implementations based on blockchain and smart contracts are among the most advanced and promising, even if they are affected by problems regarding the performance and privacy of the information exchanged and processed by smart contracts and managed by blockchains. This paper presents a watermarking protocol implemented by smart contracts and blockchain. The protocol uses a âlayer-2â blockchain execution model and performs the computation in âtrusted execution environmentsâ (TEEs). Therefore, its implementation can guarantee efficient and confidential execution without compromising ease of use or resorting to TTPs. The protocol and its implementation can, thus, be considered a valid answer to the âtrilemmaâ that afflicts the use of blockchains, managing to guarantee decentralization, security, and scalability.
Hojun Kang, Kyuyeon Hwang
No abstract is available for this record.
Sarthak Singh Rawat, Rajeev Mohan Sharma, Brian J. Peter, Mohammad Wazid ¡ 6 authors
Secure, verifiable, and transparent elections are the most crucial to democratic procedures. Blockchain technology can be utilized as a potential solution for tamper-resistant and decentralized voting schemes. The utilization of blockchain technology in e-voting systems is of significant interest because of its capacity to improve transparency, security, and integrity in digital voting. However, privacy and voter anonymity are imperative concerns. This paper presents a novel blockchain voting system that preserves vote integrity and voter anonymity by using zero-knowledge proofs (ZKPs). In this paper, we propose the system architecture, cryptographic primitives, implementation strategies, and compare security and performance to conventional e-voting systems. The new paradigm preserves voter anonymity, correctness of votes, and ensures end-to-end verifiability. Further, the practical implementation of the proposed scheme is provided to measure the performance of important parameter, like, total votes cast, total gas used, number of mined blocks, transactions per seconds, etc.
X. Zheng, Chengyong Liu
No abstract is available for this record.
Yichen Tan, Yuyang Cheng, Lu Ding, Yong Zhao
Account-based anonymous blockchain systems can provide robust privacy protection for users. However, they become highly inefficient when handling high-frequency micro-payment scenarios. This paper presents systematic optimizations for batch processing and micro-payment transactions in account-based anonymous blockchain systems to enhance both privacy and efficiency. Building on BlockMaze, the first account-based anonymous blockchain system fully protecting transaction privacy, we propose innovations in batch transfers, batch receipts, and micro-payment handling. By reducing redundant data, improving circuit design, and optimizing zk-SNARK proof generation, we achieve up to 55.90% and 23.02% reductions in overall time consumption for batch transfers and receipts, respectively, significantly cutting computational cost and memory use. For micro-payments, a solution encapsulating the payment deadline reduces transaction delays and fund freezing. Experimental results show only slight increases in proof generation timeâ1.41 seconds for transfers and 1.02 seconds for paymentsâwhile maintaining privacy protection. This research lays a foundation for practical applications of account-based anonymous blockchain systems, enhancing privacy, processing efficiency, and transferability to other systems. ⢠Optimized batch processing and improve transaction efficiency in account-based anonymous blockchain systems. ⢠Optimized circuit design reduces redundant data and shortens zero-knowledge proof times. ⢠Time consumption decreased by up to 55.90% in batch transfer function and 23.02% in batch receipt function. ⢠Highly transferable to other account-based anonymous blockchain systems, offering strong flexibility and application potential. ⢠Offers future research directions to improve blockchain efficiency and privacy protection.
Anjana Nagaria, Chetan Shingadiya
Encouraging just, secure, and open election processes is a fundamental aspect of any democratic culture. Traditional and even modern electronic voting systems are plagued by persistent issues like the failure to provide anonymity for voters, forgery risks, scalability, and the absence of verifiable trust. This paper proposes a blockchain-based digital voting framework designed to address these systemic limitations by leveraging distributed ledger technology and smart contracts. The proposed solution offers end-to-end verifiability, vote immutability, and decentralized auditing mechanisms through a mobile-accessible platform built on Ethereum using Solidity and Hardhat, with Node.js and React.js for frontend interfacing. Experimental results demonstrate improved system scalability, resistance to tampering, and support for remote voting, while maintaining ballot privacy and affordability. The research also evaluates key performance indicators under various test scenarios, establishing the systemâs effectiveness and practical relevance in real-world electoral environments.
Anwar Ali Sathio, Muhammad Malook Rind, Shafique Ahmed Awan, Sameer Ali
No abstract is available for this record.
Alamelu alias Rajasree S, V. Mohanraj, R Charumathi, N. Shunmuga Karpagam ¡ 6 authors
Beyond cryptocurrencies, blockchain's ability to create permanent, tamper-proof records is finding increasing application in domains such as supply chain management, insurance, healthcare, e-governance, and voting. Recently, researchers have shown significant interest in how blockchain technology could improve the voting process. However, despite its potential, blockchain remains complex, and setting it up, even for a small-scale election, can be challenging. This paper proposes a lightweight blockchain-based e-voting framework with reduced computational overhead, making it more practical for small-scale elections. The objective of the framework is to enhance voter trust in the e-voting process. The framework was designed following a comprehensive comparative analysis of zero-knowledge proof (ZKP) and consensus algorithms. A mock election was conducted to validate the proposed framework. Evaluation results indicated that the proposed framework outperformed existing solutions in terms of efficiency and ease of implementation.