DocumentCode :
116627
Title :
Cascading failures of social networks under attacks
Author :
Chengqi Yi ; Yuanyuan Bao ; Jingchi Jiang ; Yibo Xue ; Yingfei Dong
Author_Institution :
Sch. of Comput. Sci. & Technol., Harbin Univ. of Sci. & Technol., Harbin, China
fYear :
2014
fDate :
17-20 Aug. 2014
Firstpage :
679
Lastpage :
686
Abstract :
Although cascading failures have occurred on many real-world networks, to our best knowledge, no one has clearly identified this issue on a social network. In this paper, we identify this potential issue on social networks, and develop a theoretical model to analyze related issues. Note that highly-influential “super” users play critical roles on a social network. When they are suddenly unavailable, a large portion of the social network may be seriously disrupted. The proposed model captures this dynamic process and helps us better understand related issues. Furthermore, we evaluate the proposed model under four attack strategies based on real social network datasets collected on Twitter and Sina Weibo. We also analyze the connectivity, the persistent time, and the cascade effect of a social network under these attacks. Our results show that social network service providers have to pay closer attention to super users to avoid dramatic failures.
Keywords :
security of data; social networking (online); software fault tolerance; Sina Weibo; Twitter; cascading failures; dynamic process; real social network datasets; real-world networks; social network service providers; super users; Algorithm design and analysis; Load modeling; Power system faults; Power system protection; Twitter; Vectors; attack strategies; betweenness centrality; cascading failures; social network; super users;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Social Networks Analysis and Mining (ASONAM), 2014 IEEE/ACM International Conference on
Conference_Location :
Beijing
Type :
conf
DOI :
10.1109/ASONAM.2014.6921659
Filename :
6921659
Link To Document :
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