Reputation‐based partition scheme for IoT security

IF 1.5 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Zhikui Chen, Muhammad Zeeshan Haider, Naiwen Luo, Shuo Yu, Xu Yuan, Yaochen Zhang, Tayyaba Noreen
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引用次数: 0

Abstract

With the popularity of smart terminals, such as the Internet of Things, crowdsensing is an emerging data aggregation paradigm, which plays a pivotal role in data‐driven applications. There are some key issues in the development of crowdsensing such as platform security and privacy protection. As the crowdsensing is usually managed by a centralized platform, centralized management will bring various security vulnerabilities and scalability issues. To solve these issues, an effective reputation‐based partition scheme (RSPC) is proposed in this article. The partition scheme calculates the optimal partition size by combining the node reputation value and divides the node into several disjoint partitions according to the node reputation value. By selecting the appropriate partition size, RSPC provides a mechanism to ensure that each partition is valid, as long as the maximum permissible threshold for the failed node is observed. At the same time, the RSPC reorganizes the network periodically to avoid partition attacks. In addition, for cross‐partition transactions, this paper innovatively proposes a four‐stage confirmation protocol to ensure the efficient and safe completion of cross‐partition transactions. Finally, experiments show that RSPC improves scalability, low latency, and high throughput for crowdsensing.
物联网安全的基于信誉的分区方案
随着物联网等智能终端的普及,众测是一种新兴的数据聚合模式,在数据驱动应用中发挥着举足轻重的作用。在众筹的发展过程中,存在着平台安全和隐私保护等关键问题。由于众测通常采用集中式平台进行管理,集中式管理会带来各种安全漏洞和可扩展性问题。为了解决这些问题,本文提出了一种有效的基于信誉的分区方案(RSPC)。分区方案通过结合节点的信誉值计算出最优的分区大小,并根据节点的信誉值将节点划分为多个不相交的分区。通过选择适当的分区大小,RSPC提供了一种机制来确保每个分区都是有效的,只要观察到故障节点的最大允许阈值。同时,RSPC定期对网络进行重组,避免分区攻击。此外,对于跨分区交易,本文创新性地提出了一种四阶段确认协议,以确保跨分区交易的高效、安全完成。最后,实验表明,RSPC提高了群体感知的可扩展性、低延迟和高吞吐量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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80
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