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96,040 results · page 272 of 4,002
Rahmatullah Mohammed
No abstract is available for this record.
Yuxian Li, Xiaoguo Li, Guomin Yang, Haoxin Tu · 6 authors
Private Smart Contracts (PSCs) aim to settle the privacy protection issue for sensitive data on the blockchain (a.k.a., on-chain data) while inheriting the computation functionality of general smart contracts. However, most of the existing PSCs focus on secure computation and ignore the secure and flexible management of on-chain data, making it difficult to support flexible user permission modes efficiently. Further, although a few on-chain data management schemes have been proposed to manage data on the blockchain, they provide insufficient support for scenarios where data must be managed concurrently by managers with different privilege levels. This paper proposesMISC, a novel solution that features efficient and flexible data management capabilities for managing on-chain data in private smart contracts.MISCleverages a novel Double Trapdoor Homomorphic Proxy Re-encryption (DT-HPRE) scheme and Trusted Execution Environments (TEEs) to ensure (1) low-overhead, flexible permission control over on-chain data and (2) a harmonious mechanism for both privileged and constrained managers. We prove the security ofMISCunder the Universal Composability (UC) framework to demonstrate its data confidentiality guarantees, user revocation, and computation integrity. Further, we implementMISC, and the performance evaluation shows that on-chain data access for one hundred data points is practically achieved in 5.8 s (under privileged managers) and 9.7 s (under constrained managers) using its off-chain design.
Junjia Chen, Zhijie Zhong, Yuren Zhou
No abstract is available for this record.
Sandeepan Banerjee
The use of blockchain technology in smart contracts is changing the way businesses are run in the modern world, with the ability to perform automated, transparent and additional contractual terms without being tampered with. This paper examines how smart contracts can be utilised with real-time business performance analytics to improve the efficiency of operations, accountability and strategic decision-making. Smart contracts can be utilized to validate transactions in a decentralized system by including a set of rules that ensure that the transactions are automatically validated immediately, minimize the reliance on intermediaries and minimize human error. Through the integration of the real-time analytics tools, the organizations will be able to track the key performance indicators (KPI), financial operations, supply chain operations and compliance indicators more precisely and promptly. The integration of these technologies promotes integrity of data, reinforcement of audit trails and predictive insights due to the continuous flow of data stream. Moreover, the study points to its use in finance, supply chain management, healthcare and digital services, noting that it has better transparency, cost reduction in operations and the trust of stakeholders. In spite of the benefits, there are still issues like scalability, interoperability, regulatory unpredictability and data privacy. The paper comes to a conclusion that a combination of smart contracts and real-time analytics offers a strategic platform to data-driven companies, which make agility decisions and sustainable competitive edges in dynamic digital markets.
Lei Song, Xiaolong Guo, Fasheng Xu, Yiqun Chen
No abstract is available for this record.
Anna Hupe
No abstract is available for this record.
Nia Chen, Jennifer Chan, Linh Nghiem
No abstract is available for this record.
Muhammad Abubakr Naeem, Madiha Kiran, Nadia Arfaoui
No abstract is available for this record.
Anna Gambaro, Leandro Benito, Bertolosi Cristina, Paola Zocchi · 5 authors
No abstract is available for this record.
Shashi Tiwari
No abstract is available for this record.
Xinqi Dong, Yijia Wang, Yijia Wang, Xu Zhang · 6 authors
No abstract is available for this record.
Tanmayi Jandhyala, Guang Gong
No abstract is available for this record.
Hyeonbum Lee, Seunghun Paik, Hyunjung Son, Jae Hong Seo
An inner product argument (IPA) is a cryptographic proof system that serves as a fundamental building block for various applications, such as zero knowledge proofs and verifiable computation. Bulletproofs (IEEE S&P 2018), a well-known IPA under the discrete logarithm (DL) assumption, features a short, logarithmically-sized proof, making it suitable for blockchain applications. However, its major drawback is the linear verifier cost (O(N)), which presents a significant bottleneck in settings like verifiable computation. To address this, recent advancements have successfully reduced the verification complexity to square-root order (O(√N)) under the same assumption (e.g., Asiacrypt 2022, IEEE TIFS). In thiswork, we propose Cougar, a novel IPAthat breaks this square-root barrier to achieve an unprecedented cubic-root verifier complexity (O(3√N)), while strictly maintaining the compact logarithmic proof size (O(logN)) characteristic of Bulletproofs. To achieve this, Cougar introduces a generalized two-tier commitment framework combined with adisjoint interpolationstrategy for efficient consistency checks. We implemented Cougar in Rust and performed a comprehensive benchmarking against Bulletproofs and Leopard (IEEE TIFS). Our evaluation demonstrates that while Cougar incurs a moderate increase in prover overhead, its verification time scales significantly better for large instances. Concretely, for a witness size ofN= 220, Cougar achieves a 50× verification speed-up over Bulletproofs and exhibits a superior asymptotic growth rate compared to existing sublinear IPAs.
Tolibjon Mansurov, Bobir Boltaev, Khumoyun Barоtov, Makhliyo Sharifova · 5 authors
No abstract is available for this record.
Anshika Malsaria, Pankaj Vyas
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.
Chiang Liang Kok, Jie Heng, Brendon Choo, Nicholas Tan · 5 authors
No abstract is available for this record.
Priyanga K. K, Josheena Jose
No abstract is available for this record.
Laura Atmanavičiūtė, Mykolas Rutkauskas, Aristidas Lukas Končius, Gintarė Košubienė · 5 authors
No abstract is available for this record.
CHRISTIAN RODRIGUES PEREIRA
No abstract is available for this record.
Michael Schallop
No abstract is available for this record.
Sami Rashid Mohammed Shibah
No abstract is available for this record.
Haoyang Gao, X Wang
With its decentralized, tamper proof, transparent and traceable characteristics, blockchain technology has shown great potential in fields such as finance, supply chain, and the Internet of Things. However, the public transparency of its ledger poses a serious challenge to user transaction privacy. Traditional privacy protection schemes such as homomorphic encryption and zero knowledge proofs can enhance privacy, but often struggle to balance computational overhead, communication costs, and data availability. This article explores the innovative application of neural networks in blockchain privacy protection and proposes a transaction obfuscation model based on generative adversarial networks. This model utilizes a generator to learn the statistical features of raw transactions and generate difficult to track obfuscated transactions, while ensuring the validity and compliance of obfuscated transactions through discriminators and blockchain verification contracts. The experimental results show that compared with traditional obfuscation methods and differential privacy methods, the proposed model significantly reduces the consumption of privacy budget and computation delay while ensuring high transaction utility (such as reducing address correlation by more than 85%), achieving a better balance between privacy and utility. This study provides new ideas for building efficient and practical blockchain privacy enhancement solutions.
Shehzad Ahmed, Rafiqul Bhuyan
No abstract is available for this record.