<italic>ProGuard</italic>: Detecting Malicious Accounts in Social-Network-Based Online Promotions
Online social networks (OSNs) gradually integrate financial capabilities by enabling the usage of real and virtual currency. They serve as new platforms to host a variety of business activities, such as online promotion events, where users can possibly get virtual currency as rewards by participatin...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2017-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/7820106/ |
| _version_ | 1818619646832541696 |
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| author | Yadong Zhou Dae Wook Kim Junjie Zhang Lili Liu Huan Jin Hongbo Jin Ting Liu |
| author_facet | Yadong Zhou Dae Wook Kim Junjie Zhang Lili Liu Huan Jin Hongbo Jin Ting Liu |
| author_sort | Yadong Zhou |
| collection | DOAJ |
| description | Online social networks (OSNs) gradually integrate financial capabilities by enabling the usage of real and virtual currency. They serve as new platforms to host a variety of business activities, such as online promotion events, where users can possibly get virtual currency as rewards by participating in such events. Both OSNs and business partners are significantly concerned when attackers instrument a set of accounts to collect virtual currency from these events, which make these events ineffective and result in significant financial loss. It becomes of great importance to proactively detecting these malicious accounts before the online promotion activities and subsequently decreases their priority to be rewarded. In this paper, we propose a novel system, namely ProGuard, to accomplish this objective by systematically integrating features that characterize accounts from three perspectives including their general behaviors, their recharging patterns, and the usage of their currency. We have performed extensive experiments based on data collected from the Tencent QQ, a global leading OSN with built-in financial management activities. Experimental results have demonstrated that our system can accomplish a high detection rate of 96.67% at a very low false positive rate of 0.3%. |
| first_indexed | 2024-12-16T17:40:48Z |
| format | Article |
| id | doaj.art-d06e4efdebdb4ffea6a5d72817f5b3a3 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T17:40:48Z |
| publishDate | 2017-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-d06e4efdebdb4ffea6a5d72817f5b3a32022-12-21T22:22:37ZengIEEEIEEE Access2169-35362017-01-0151990199910.1109/ACCESS.2017.26542727820106<italic>ProGuard</italic>: Detecting Malicious Accounts in Social-Network-Based Online PromotionsYadong Zhou0https://orcid.org/0000-0003-0345-3518Dae Wook Kim1Junjie Zhang2Lili Liu3Huan Jin4Hongbo Jin5Ting Liu6Ministry of Education Key Lab for Intelligent Networks and Network Security, Xi’an Jiaotong University, Xi’an, ChinaDepartment of Computer Science and Engineering, Wright State University, Dayton, OH, USADepartment of Computer Science and Engineering, Wright State University, Dayton, OH, USAMinistry of Education Key Lab for Intelligent Networks and Network Security, Xi’an Jiaotong University, Xi’an, ChinaTencent Technology (Shenzhen) Company Ltd., Shenzhen, ChinaTencent Technology (Shenzhen) Company Ltd., Shenzhen, ChinaMinistry of Education Key Lab for Intelligent Networks and Network Security, Xi’an Jiaotong University, Xi’an, ChinaOnline social networks (OSNs) gradually integrate financial capabilities by enabling the usage of real and virtual currency. They serve as new platforms to host a variety of business activities, such as online promotion events, where users can possibly get virtual currency as rewards by participating in such events. Both OSNs and business partners are significantly concerned when attackers instrument a set of accounts to collect virtual currency from these events, which make these events ineffective and result in significant financial loss. It becomes of great importance to proactively detecting these malicious accounts before the online promotion activities and subsequently decreases their priority to be rewarded. In this paper, we propose a novel system, namely ProGuard, to accomplish this objective by systematically integrating features that characterize accounts from three perspectives including their general behaviors, their recharging patterns, and the usage of their currency. We have performed extensive experiments based on data collected from the Tencent QQ, a global leading OSN with built-in financial management activities. Experimental results have demonstrated that our system can accomplish a high detection rate of 96.67% at a very low false positive rate of 0.3%.https://ieeexplore.ieee.org/document/7820106/Online social networksvirtual currencymalicious accountsintrusion detectionnetwork security |
| spellingShingle | Yadong Zhou Dae Wook Kim Junjie Zhang Lili Liu Huan Jin Hongbo Jin Ting Liu <italic>ProGuard</italic>: Detecting Malicious Accounts in Social-Network-Based Online Promotions IEEE Access Online social networks virtual currency malicious accounts intrusion detection network security |
| title | <italic>ProGuard</italic>: Detecting Malicious Accounts in Social-Network-Based Online Promotions |
| title_full | <italic>ProGuard</italic>: Detecting Malicious Accounts in Social-Network-Based Online Promotions |
| title_fullStr | <italic>ProGuard</italic>: Detecting Malicious Accounts in Social-Network-Based Online Promotions |
| title_full_unstemmed | <italic>ProGuard</italic>: Detecting Malicious Accounts in Social-Network-Based Online Promotions |
| title_short | <italic>ProGuard</italic>: Detecting Malicious Accounts in Social-Network-Based Online Promotions |
| title_sort | italic proguard italic detecting malicious accounts in social network based online promotions |
| topic | Online social networks virtual currency malicious accounts intrusion detection network security |
| url | https://ieeexplore.ieee.org/document/7820106/ |
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