SiMAIM:在一个以论坛为导向的社交媒体网站上识别子和木偶师
1Department of Information Management, National Dong Hwa University, No. 1, Sec. 2, Da Hsueh Road, Hualien, 97401 Taiwan, R.O.C.
概括
本研究引入了一种新模型,用于识别在论坛上由单个用户 (主) 控制的多个社交媒体帐户 (). 单站点多个账户识别模型 (SiMAIM) 能够有效地检测这些恶意账户.
科学领域:
- 计算机科学 计算机科学
- 社交媒体分析 社交媒体分析
- 网络安全 网络安全
背景情况:
- 社交媒体是日常生活中不可或缺的组成部分,但可以通过单个用户 (木偶师) 控制的多个帐户 () 实现垃圾邮件和争议等恶意活动.
- 识别木偶对于减轻有害的在线行为至关重要,但对单站点木偶检测的研究仍然有限.
研究的目的:
- 解决在面向单一论坛的社交媒体网站上识别木偶的研究缺口.
- 提出和验证一个新的框架,用于检测特定平台内由单个用户控制的多个帐户.
主要方法:
- 单站点多个账户识别模型 (SiMAIM) 框架的开发.
- 使用来自Mobile01的数据对SiMAIM的实证验证,这是一个流行的台湾论坛导向的社交媒体网站.
- 在各种数据集和设置中使用F1分数进行性能评估.
主要成果:
- 在识别子和木偶师方面,SiMAIM获得了高的F1分数,从0.6到0.9不等.
- 拟议的SiMAIM框架与现有方法相比表现优越,在F1得分方面表现优于现有方法6-38%.
- 该模型在检测单个社交媒体平台内的协调恶意活动方面被证明是有效的.
结论:
- SiMAIM提供了一个强大的解决方案,用于识别面向论坛的社交媒体网站上的子.
- 该框架成功地解决了网络安全研究中的一个关键缺口,即单一平台恶意帐户检测.
- 这些发现突显了SiMAIM在增强在线平台安全性和用户信任方面的潜力.
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