Title: Intervention algorithm for malicious information in online social networks based on trusted regulator

Authors: Deyu Yuan; Haichun Sun; Zhi Zhang; Han Ye; Shuhua Huang

Addresses: Police Information Technology and Cyber Security Institution, People's Public Security University of China, Beijing, China; Key Laboratory of Safety Precautions and Risk Assessment, Ministry of Public Security, Beijing 102623, China ' Police Information Technology and Cyber Security Institution, People's Public Security University of China, Beijing, China; Key Laboratory of Safety Precautions and Risk Assessment, Ministry of Public Security, Beijing 102623, China ' Police Information Technology and Cyber Security Institution, People's Public Security University of China, Beijing, China; Key Laboratory of Safety Precautions and Risk Assessment, Ministry of Public Security, Beijing 102623, China ' Police Information Technology and Cyber Security Institution, People's Public Security University of China, Beijing, China; Key Laboratory of Safety Precautions and Risk Assessment, Ministry of Public Security, Beijing 102623, China ' Police Information Technology and Cyber Security Institution, People's Public Security University of China, Beijing, China; Key Laboratory of Safety Precautions and Risk Assessment, Ministry of Public Security, Beijing 102623, China

Abstract: A lot of malicious information such as rumours are hidden in the massive data flow in social online networks. Once this type of malicious information spreads, it could affect social stability in severe cases. This paper introduces the concept of trusted regulator to select key nodes, and we propose a method to hinder the rapid spread of malicious information by blocking accounts and publishing clarification, so that the external disturbances from the chosen nodes and the malicious information could fight against each other. Local control strategy is applied to the propagation of malicious information. Specifically, we first introduce the SIMRT model and an importance indicator based on edge weight, then we propose the reverse intervention algorithm based on the importance indicator. Experiment results on different data sets show that the proposed algorithm can effectively suppress the spread of malicious information.

Keywords: malicious information; online social networks; reverse intervention.

DOI: 10.1504/IJWMC.2020.108532

International Journal of Wireless and Mobile Computing, 2020 Vol.18 No.4, pp.343 - 351

Received: 19 Jul 2019
Accepted: 01 Nov 2019

Published online: 03 Jul 2020 *

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