Towards trusted node selection using blockchain for crowdsourced abnormal data detection
【Author】 He, Xin; Yang, Haochen; Wang, Guanghui; Yu, Junyang
【Source】FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
【影响因子】7.307
【Abstract】Node selection plays an important role to design and implement the crowdsourced abnormal data detection system with the purpose of completing complex tasks to meet the requirements of computing performance. Even though the blockchain-based trusted node selection approaches improve the reliability of the crowdsourcing task results, they still need to consider the crowdsourcing cost during the node selection process so as to embody a tradeoff between reliability and cost. In this paper, we propose to study the node selection problem for the crowdsourced abnormal data detection under both reliability and cost requirements. First, the working node selection is modeled as an inverse 0 - 1 knapsack problem in order to minimize the crowdsourcing cost under the budget constraints of the trustworthiness of the selected working nodes, where blockchain is used to calculate the trustworthiness of the working nodes. Then, a trusted working node selection (TWNS) algorithm is developed to select trusted working nodes with the minimum crowdsourcing cost for crowdsourced abnormal data detection, where the branch and bound method is utilized to efficiently solve the inverse 0 - 1 knapsack problem. Finally, extensive simulations are conducted based on three groups of real world datasets. The results show that the trust value evaluation is accurate by using blockchain and the TWNS algorithm can ensure the reliability of the detection result. The crowdsourcing cost is minimized in trusted working node selection process. Compared to existing approaches without considering the cost, the TWNS algorithm reduces the crowdsourcing cost by 64.6%. (C) 2022 Elsevier B.V. All rights reserved.
【Keywords】Abnormal data detection; Trusted node selection; Blockchain; Inverse 0-1 knapsack; Crowdsourcing cost
【发表时间】2022 AUG
【收录时间】2022-06-18
【文献类型】理论性文章
【主题类别】
区块链治理-技术治理-异常/非法交易识别
wangjiaxin
今日有2篇链上数据分析相关的文章：https://linkinghub.elsevier.com/retrieve/pii/S0167739X22001017发表在FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE。 提出了基于区块链研究众包异常数据检测的节点选择问题，以降低任务的成本和提高可信度。文章首先将工作节点选择建模，以在所选工作节点可信度的预算约束下最小化众包成本，其中区块链用于计算工作节点的可信度。然后，开发了一种可信工作节点选择（TWNS）算法，用于选择具有最小众包成本的可信工作节点进行众包异常数据检测，其中利用分枝定界法有效求解问题。最后，基于三组真实数据集进行了广泛的模拟。
回复