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Content Abuse and Privacy Concerns in Online Social Networks.

机译:在线社交网络中的内容滥用和隐私问题。

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摘要

Online Social Networks (OSNs) have seen an exponential growth over the last decade, with Facebook having more than 1.49 billion monthly active users and Twitter having 135,000 new users signing up every day as of 2015. Users are sharing 70 million photos per day on the Instagram photo-sharing network. Yahoo Answers question-answering community has more than 1 billion posted answers. The meteoric rise in popularity has made OSNs important social platforms for computer-mediated communications and embedded themselves into society's daily life, with direct consequences to the offline world and activities. OSNs are built on a foundation of trust, where users connect to other users with common interests or overlapping personal trajectories. They leverage real-world social relationships and/or common preferences, and enable users to communicate online by providing them with a variety of interaction mechanisms.;This dissertation studies abuse and privacy in online social networks. More specifically, we look at two issues: (1) the content abusers in the community question answering (CQA) social network and, (2) the privacy risks that comes from the default permissive privacy settings of the OSNs. Abusive users have negative consequences for the community and its users, as they decrease the community's cohesion, performance, and participation. We investigate the reporting of 10 million editorially curated abuse reports from 1.5 million users in Yahoo Answers, one of the oldest, largest, and most popular CQA platforms. We characterize the contribution and position of the content abusers in Yahoo Answers social networks. Based on our empirical observations, we build machine learning models to predict such users.;Users not only face the risk of exposing themselves to abusive users or content, but also face leakage risks of their personal information due to weak and permissive default privacy policies. We study the relationship between users' privacy concerns and their engagement in Yahoo Answers social networks. We find privacy-concerned users have higher qualitative and quantitative contributions, show higher retention, report more abuses, have higher perception on answer quality and have larger social circles. Next, we look at users' privacy concerns, abusive behavior, and engagement through the lenses of national cultures and discover cross-cultural variations in CQA social networks.;However, our study in Yahoo Answers reveals that the majority of users (about 87%) do not change the default privacy policies. Moreover, we find a similar story in a different type of social network (blogging): 92% bloggers' do not change their default privacy settings. These results on default privacy are consistent with general-purpose social networks (such as Facebook) and warn about the importance of user-protecting default privacy settings.;We model and implement default privacy as contextual integrity in OSNs. We present a privacy framework, Aegis, and provide a reference implementation. Aegis models expected privacy as contextual integrity using semantic web tools and focuses on defining default privacy policies. Finally, this dissertation presents a comprehensive overview of the privacy and security attacks in the online social networks projecting them in two directions: attacks that exploit users' personal information and declared social relationships for unintended purposes; and attacks that are aimed at the OSN service provider itself, by threatening its core business.
机译:过去十年来,在线社交网络(OSN)呈指数级增长,截至2015年,Facebook每月活跃用户超过14.9亿,Twitter每天有135,000新用户注册。用户每天在网上分享7,000万张照片Instagram照片共享网络。 Yahoo Answers问答社区已经发布了超过10亿个答案。流行的迅速增加已使OSN成为计算机介导通信的重要社交平台,并将其嵌入到社会的日常生活中,从而直接影响到离线世界和活动。 OSN建立在信任的基础上,在该信任基础上,用户与具有共同兴趣或个人轨迹重叠的其他用户建立联系。它们利用现实世界中的社交关系和/或共同的喜好,并通过向用户提供各种交互机制使用户能够在线交流。;本论文研究了在线社交网络中的滥用和隐私。更具体地说,我们研究两个问题:(1)社区问答(CQA)社交网络中的内容滥用者,以及(2)OSN的默认允许隐私设置带来的隐私风险。滥用用户会对社区及其用户造成负面影响,因为它们会降低社区的凝聚力,绩效和参与度。我们调查了Yahoo Answers(这是最古老,规模最大和最受欢迎的CQA平台之一)中来自150万用户的1000万个经过编辑策划的滥用行为报告的报告。我们描述了内容滥用者在Yahoo Answers社交网络中的贡献和地位。基于我们的经验观察,我们建立了机器学习模型来预测此类用户。;用户不仅面临将自己暴露于虐待性用户或内容的风险,而且由于薄弱且允许的默认隐私策略而面临其个人信息泄露的风险。我们研究了用户的隐私问题与他们参与Yahoo Answers社交网络之间的关系。我们发现,与隐私相关的用户在定性和定量方面的贡献更高,保留率更高,报告了更多滥用行为,对答案质量的认知度更高,社交圈更大。接下来,我们通过民族文化的视角审视用户的隐私问题,虐待行为和参与度,并发现CQA社交网络中的跨文化差异。但是,我们在Yahoo Answers中的研究表明,大多数用户(约87% )不要更改默认的隐私政策。此外,我们在不同类型的社交网络(博客)中发现了类似的故事:92%的博客作者未更改其默认隐私设置。这些关于默认隐私的结果与通用社交网络(例如Facebook)一致,并警告了用户保护默认隐私设置的重要性。我们在OSN中建模并实现默认隐私作为上下文完整性。我们提出了一个隐私框架Aegis,并提供了参考实施。 Aegis使用语义Web工具将预期的隐私建模为上下文完整性,并专注于定义默认的隐私策略。最后,本文对在线社交网络中的隐私和安全攻击进行了全面概述,并从两个方向进行了预测:利用用户的个人信息和出于非预期目的声明的社交关系的攻击;通过威胁OSN服务提供商的核心业务而针对OSN服务提供商本身的攻击。

著录项

  • 作者

    Kayes, Md Imrul.;

  • 作者单位

    University of South Florida.;

  • 授予单位 University of South Florida.;
  • 学科 Computer science.
  • 学位 Ph.D.
  • 年度 2015
  • 页码 228 p.
  • 总页数 228
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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