CSR: Medium: Highly Scalable and Accurate System Support for Detecting Misbehaving Users and Mitigating Criminal Activities in Realtime Online Video-Based Services

CSR：中：高度可扩展且准确的系统支持，用于检测行为不当的用户并减少实时在线视频服务中的犯罪活动

• 批准号: 1162614
• 负责人: Shivakant Mishra
• 金额: $ 70万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-15 至 2016-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1162614&HistoricalAwards=false
• 关键词: CSR; Medium; Highly; Scalable; Accurate

The main goal of this proposal is to understand the safety problems introduced by realtime online video-based services, and to develop highly scalable and accurate solutions and systems that protect the safety of interactive video users. While realtime, online video-based services are newly emerging services, they have already gained tremendous popularity with millions of users. These services introduce new ways for people to interact and have the potential to significantly impact, even revolutionize, pervasive computing and online social networking services. Unfortunately, the presence of misbehaving users may jeopardize the entire utility of these services and bring harm to minors. This proposal investigates innovative ideas including fine-grained cascaded classification and a rule-based pre-classifier with logistic regression to improve scalability while preserving accuracy, incorporating contextual information from smartphone sensors and application scenarios to improve accuracy, and mechanisms to evaluate and circumvent cyber-bullying. The complete system will be deployed and evaluated using real-world data. With the growing popularity of realtime, online video-based services and the threat to minors of being exposed to unsuitable content or cyber-bullying attacks, developing effective techniques for detecting misbehaving users of these services will have significant and far-reaching beneficial impacts on society. All software developed from this project will be released as open source. The project will develop and integrate educational course modules on Internet safety topics into relevant middle and high school courses via an on-going NSF GK-12 project. Undergraduate and minority students will be recruited via the Colorado Diversity Institute and annual REU supplements.

该提案的主要目标是了解实时在线视频的服务引入的安全问题，并开发高度可扩展，准确的解决方案和系统来保护交互式视频用户的安全性。实时，基于在线视频的服务是新兴新兴的服务，但他们已经在数百万用户中获得了巨大的知名度。这些服务为人们提供了新的方式互动，并有可能影响，甚至革新，普遍计算和在线社交网络服务。不幸的是，行为不善的用户的存在可能会危害这些服务的全部效用并对未成年人造成伤害。该提案调查了创新的想法，包括细粒度的级联分类和具有逻辑回归的基于规则的前分类器，以提高可扩展性，同时保持准确性，并结合智能手机传感器的上下文信息和应用程序方案，以提高准确性，以提高准确性，以评估和避免网络欺凌。完整的系统将使用实际数据部署和评估。随着实时的越来越受欢迎，基于在线视频的服务以及对未成年人暴露于不合适的内容或网络欺凌攻击的威胁，开发有效的技术来检测这些服务的不当用户将对社会产生重大且深远的有益影响。该项目开发的所有软件将作为开源发布。该项目将通过正在进行的NSF GK-12项目将有关互联网安全主题的教育课程模块发展为相关的中学和高中课程。本科生和少数民族学生将通过科罗拉多州多样性研究所和年度REU补充剂招募。