Preservation of Sensitive Data Using Multi-Level Blockchain-based Secured Framework for Edge Network Devices

IF 3.6 2区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Charu Awasthi, Prashant Kumar Mishra, Pawan Kumar Pal, Surbhi Bhatia Khan, Ambuj Kumar Agarwal, Thippa Reddy Gadekallu, Areej A. Malibari
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引用次数: 0

Abstract

The proliferation of IoT devices has influenced end users in several aspects. Yottabytes (YB) of information are being produced in the IoT environs because of the ever-increasing utilization capacity of the Internet. Since sensitive information, as well as privacy problems, always seem to be an unsolved problem, even with best-in-class in-formation governance standards, it is difficult to bolster defensive security capabilities. Secure data sharing across disparate systems is made possible by blockchain technology, which operates on a decentralized computing paradigm. In the ever-changing IoT environments, blockchain technology provides irreversibility (immutability) usage across a wide range of services and use cases. Therefore, blockchain technology can be leveraged to securely hold private information, even in the dynamicity context of the IoT. However, as the rate of change in IoT networks accelerates, every potential weak point in the system is exposed, making it more challenging to keep sensitive data se-cure. In this study, we adopted a Multi-level Blockchain-based Secured Framework (M-BSF) to provide multi-level protection for sensitive data in the face of threats to IoT-based networking systems. The envisioned M-BSF framework incorporates edge-level, fog-level, and cloud-level security. At edge- and fog-level security, baby kyber and scaling kyber cryptosystems are applied to ensure data preservation. Kyber is a cryptosystem scheme that adopts public-key encryption and private-key decryption processes. Each block of the blockchain uses the cloud-based Argon-2di hashing method for cloud-level data storage, providing the highest level of confidentiality. Argon-2di is a stable hashing algorithm that uses a hybrid approach to access the memory that relied on dependent and independent memory features. Based on the attack-resistant rate (> 96%), computational cost (in time), and other main metrics, the proposed M-BSF security architecture appears to be an acceptable alternative to the current methodologies.

使用基于多级区块链的边缘网络设备安全框架保存敏感数据
物联网设备的激增在几个方面影响了最终用户。由于互联网的利用能力不断增加,物联网环境中产生的信息数量达到千兆字节(YB)。由于敏感信息和隐私问题似乎始终是一个未解决的问题,即使使用一流的信息治理标准,也很难加强防御安全功能。通过区块链技术,跨不同系统的安全数据共享成为可能,区块链技术在分散的计算范式上运行。在不断变化的物联网环境中,区块链技术在广泛的服务和用例中提供了不可逆性(不变性)使用。因此,即使在物联网的动态环境中,也可以利用区块链技术安全地保存私人信息。然而,随着物联网网络变化速度的加快,系统中的每个潜在弱点都暴露出来,这使得保持敏感数据安全变得更具挑战性。在本研究中,我们采用了基于多级区块链的安全框架(M-BSF),在面对基于物联网的网络系统的威胁时,为敏感数据提供多级保护。设想的M-BSF框架包含边缘级、雾级和云级安全性。在边缘和雾级安全,婴儿kyber和缩放kyber密码系统应用,以确保数据保存。Kyber是一种采用公钥加密和私钥解密过程的密码系统方案。区块链的每个区块都使用基于云的Argon-2di哈希方法进行云级数据存储,提供最高级别的机密性。Argon-2di是一种稳定的散列算法,它使用混合方法访问依赖于依赖和独立内存特性的内存。基于抗攻击率(96%)、计算成本(时间)和其他主要指标,提议的M-BSF安全体系结构似乎是当前方法的可接受替代方案。
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来源期刊
Journal of Grid Computing
Journal of Grid Computing COMPUTER SCIENCE, INFORMATION SYSTEMS-COMPUTER SCIENCE, THEORY & METHODS
CiteScore
8.70
自引率
9.10%
发文量
34
审稿时长
>12 weeks
期刊介绍: Grid Computing is an emerging technology that enables large-scale resource sharing and coordinated problem solving within distributed, often loosely coordinated groups-what are sometimes termed "virtual organizations. By providing scalable, secure, high-performance mechanisms for discovering and negotiating access to remote resources, Grid technologies promise to make it possible for scientific collaborations to share resources on an unprecedented scale, and for geographically distributed groups to work together in ways that were previously impossible. Similar technologies are being adopted within industry, where they serve as important building blocks for emerging service provider infrastructures. Even though the advantages of this technology for classes of applications have been acknowledged, research in a variety of disciplines, including not only multiple domains of computer science (networking, middleware, programming, algorithms) but also application disciplines themselves, as well as such areas as sociology and economics, is needed to broaden the applicability and scope of the current body of knowledge.
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