云计算中基于后量子密码的区块链网络安全增强方案

IF 0.5 Q4 AUTOMATION & CONTROL SYSTEMS
Sripriya Arunachalam
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引用次数: 0

摘要

基于点阵的密码学因其强大的安全性和通用性而被广泛采用,特别是在后量子公钥(PK)系统中。聚合签名方案将多个签名合并为一个简洁的加密签名,从而增强了可验证性。然而,随着量子计算能力的发展,传统方法遇到了安全漏洞,给实时和资源密集型应用带来了性能挑战。本研究介绍了一种称为后量子加密和身份加密增强(pqceeie)的解决方案,旨在通过利用基于圆形最优格的多重签名方案(ROLMSS)对抗量子攻击来解决区块链安全性问题。该研究在时间和存储方面显著提高了效率,同时降低了整体复杂性。与传统方法相比,它实现了最小的加密时间(5 ms)、解密时间(4.9 ms)、16个属性的密钥生成(80 ms)和执行时间(0.07s)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

An Effective Security Enhancement Scheme for Postquantum Cryptography Based Blockchain Networks in Cloud Computing

An Effective Security Enhancement Scheme for Postquantum Cryptography Based Blockchain Networks in Cloud Computing

Lattice-based cryptography is widely embraced for its strong security and versatility, particularly in postquantum public key (PK) systems. The incorporation of an aggregate signature scheme consolidates numerous signatures into a concise cryptographic signature, thereby enhancing verifiability. However, traditional methods encounter security vulnerabilities as quantum computing capabilities evolve, resulting in performance challenges for real-time and resource-intensive applications. This research introduces a solution, called postquantum cryptography and the enhancement of identity encryption (PQCEIE), aimed at addressing blockchain security by leveraging the round optimal lattice-based multisignature scheme (ROLMSS) against quantum attacks. The study significantly enhances efficiency in terms of time and storage, with reduced overall complexity. It achieves minimal encryption time (5 ms), decryption times (4.9 ms), key generation (80 ms) for 16 attributes, and execution time (0.07s) compared to conventional approaches.

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来源期刊
AUTOMATIC CONTROL AND COMPUTER SCIENCES
AUTOMATIC CONTROL AND COMPUTER SCIENCES AUTOMATION & CONTROL SYSTEMS-
CiteScore
1.70
自引率
22.20%
发文量
47
期刊介绍: Automatic Control and Computer Sciences is a peer reviewed journal that publishes articles on• Control systems, cyber-physical system, real-time systems, robotics, smart sensors, embedded intelligence • Network information technologies, information security, statistical methods of data processing, distributed artificial intelligence, complex systems modeling, knowledge representation, processing and management • Signal and image processing, machine learning, machine perception, computer vision
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