Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Nayancy, a; * | Dutta, Sandipa | Chakraborty, Soubhikb
Affiliations: [a] Department of Computer Science and Engineering, Birla Institute of Technology, Mesra, Ranchi, India | [b] Department of Mathematics, Birla Institute of Technology, Mesra, Ranchi, India
Correspondence: [*] Corresponding author: Nayancy, Department of Computer Science and Engineering, Birla Institute of Technology, Mesra, Ranchi, India. E-mail: [email protected].
Abstract: Blockchain has attracted tremendous attention in recent years due to its significant features including anonymity, security, immutability, and audibility. Blockchain technology has been used in several nonmonetary applications, including Internet-of-Things. Though blockchain has limited resources, and scalability is computationally expensive, resulting in delays and large bandwidth overhead that are unsuitable for many IoT devices. In this paper, we work on a lightweight blockchain approach that is suited for IoT needs and provides end-to-end security. Decentralization is achieved in our lightweight blockchain implementation by building a network with a lot of high-resource devices collaborate to maintain the blockchain. The nodes in the network is arranged in sorted order w.r.t execution time and count to reduce the mining overheads and is accountable for handling the public blockchain. We propose a distributed execution time-based consensus algorithm that decreases the delay and overhead of the mining process. We also propose a randomized node-selection algorithm for the selection of nodes to verify the mined blocks to eliminate the double-spend and 51% attack. The results are encouraging and significantly reduce the mining overhead and keep a check on the double-spending problem and 51% attack.
Keywords: Blockchain, IoT, lightweight consensus, double-spend attack, 51% attack
DOI: 10.3233/IDA-230153
Journal: Intelligent Data Analysis, vol. 28, no. 5, pp. 1309-1319, 2024
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
[email protected]
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office [email protected]
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
如果您在出版方面需要帮助或有任何建, 件至: [email protected]