Secure blockchain-based reputation system for IIoT-enabled retail industry with resistance to sybil attack

IF 6.2 2区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS Future Generation Computer Systems-The International Journal of Escience Pub Date : 2025-01-02 DOI:10.1016/j.future.2024.107705
Wenjia Zhao , Xu Yang , Saiyu Qi , Junzhe Wei , Xinpei Dong , Xu Yang , Yong Qi
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Abstract

Leveraging the recent surge in the electronic retail industry, retailer reputation has emerged with increasing significance in shaping consumer purchasing decisions. Despite this, the existing reputation platforms remain largely centralized, thereby enabling retailers to exert total control over reputation services, a reality that compromises the authentic portrayal of retailers. In response, we introduce a secure blockchain-based reputation system, named BlockRep, designed explicitly for the Industrial Internet of Things (IIoT) enabled retail industry. By eliminating dependency on trust inherently foundation in established E-retail platforms, BlockRep effectively resists sybil attack while ensuring review anonymity and authenticity, both critical security requirements of reputation systems. Initially, we champion a hybrid framework designed to enhance user interaction with our system. This approach leverages the centralized E-retail platform to facilitate trade services, whilst unfolding upon a blockchain platform that firmly authenticates the legitimacy of individual reviews. The authentication process is thus anchored to the correctness of cryptographic tokens, which are subsequently deposited on the blockchain. Additionally, we introduce a novel concept, ‘tax-endorsed reviews,’ devised to resist sybil attacks, such as injecting fake positive reviews for itself. Consequently, this necessitates the implementation of a four-party collaboration protocol. Finally, the security analysis complemented with our experimental results, definitively showcase the security and efficiency of BlockRep.
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来源期刊
CiteScore
19.90
自引率
2.70%
发文量
376
审稿时长
10.6 months
期刊介绍: Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications. Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration. Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.
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