SaTC: CORE: Small: A Privacy-Preserving Meta-Data Analysis Framework for Cyber Abuse Research - Foundations, Tools and Algorithms

SaTC：核心：小型：用于网络滥用研究的隐私保护元数据分析框架 - 基础、工具和算法

• 批准号: 1718071
• 负责人: Sriram Chellappan
• 金额: $ 49.83万
• 依托单位: University of South Florida
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1718071&HistoricalAwards=false
• 关键词: SaTC; CORE; Small; Privacy; Preserving

This project develops and deploys a mobile communications metadata analysis platform, designed to predict incidents of youth harassment or abuse, drawing on participatory methods to drive research design decisions and maintain youth privacy. By analyzing communication patterns - rather than content - in collaboration with youth participants, this project makes innovative contributions by facilitating a contextualized understanding of youth abuse and harassment. In turn, this analysis supports the development of new, privacy-enhancing tools which allow for early intervention in instances of abuse and distress. Starting from the hypothesis that abused or distressed youth display observably different patterns of communication, the data collected allow researchers to visualize and analyze the everyday communication networks of youth in new ways, providing new opportunities to understand the structures and conditions of youth sociality and forms of abuse while simultaneously developing new predictive models and techniques.In particular, this project 1) designs new methods grounded in participatory design that allows for a better understanding of the ways in which youth conceptualize privacy, adult supervision and surveillance online; 2) develops a highly scalable and practically deployable mobile platform for performing large scale metadata and survey analysis, taking the privacy needs of end users as a core design principle as identified from the first outcome; 3) ensures that the platform guarantees full anonymity to participants, while also allowing for longitudinal and flexible survey administration, metadata collection, and seamless scaling; 4) extracts novel features in the spatial and temporal domain from communication metadata logs (from texts and calls) that associate with cyber harassment and abuse; 5) leverages the features extracted to design context aware machine learning algorithms to quickly detect abnormal patterns from metadata logs. The project trains a number of graduate and undergraduate student in inter-disciplinary research. Long term impact of this project scale well beyond youth populations, and the project more generally moves towards the development of a fully anonymous, confidential, needs-based social scientific research platform.

该项目开发和部署了一个移动的通信元数据分析平台，旨在预测青年骚扰或虐待事件，利用参与性方法推动研究设计决策并维护青年隐私。通过与青年参与者合作分析交流模式-而不是内容，该项目通过促进对青年虐待和骚扰的背景化理解，做出了创新性贡献。反过来，这种分析支持开发新的、增强隐私的工具，以便在虐待和痛苦的情况下进行早期干预。从被虐待或受虐待的青年表现出明显不同的交流模式这一假设出发，收集的数据使研究人员能够以新的方式可视化和分析青年的日常交流网络，为了解青年社会性的结构和条件以及虐待形式提供了新的机会，同时开发了新的预测模型和技术。该项目（1）设计了以参与式设计为基础的新方法，以便更好地了解青年如何将隐私、成人监督和在线监视概念化; 2）开发高度可扩展和实际可部署的移动的平台，用于执行大规模元数据和调查分析，将最终用户的隐私需求作为第一项成果确定的核心设计原则; 3）确保平台保证参与者完全匿名，同时还允许纵向和灵活的调查管理，元数据收集和无缝扩展; 4）从与网络骚扰和滥用相关的通信元数据日志（来自文本和呼叫）中提取空间和时间域中的新特征; 5）利用提取的特征来设计上下文感知机器学习算法，以快速检测元数据日志中的异常模式。该项目培训了一批跨学科研究的研究生和本科生。该项目的长期影响远远超出了青年人口的范围，该项目更普遍地朝着开发一个完全匿名、保密、基于需求的社会科学研究平台的方向发展。

项目成果

How smart your smartphone is in lie detection?

• DOI: 10.1145/3360774.3360788
• 发表时间: 2019-11
• 期刊: Proceedings of the 16th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services
• 作者: Md. Mizanur Rahman;Atanu Shome;Sriram Chellappan;A. Alim;Al Islam

On the feasibility of profiling internet users based on volume and time of usage

基于使用量和时间的互联网用户画像的可行性

• DOI: 10.1109/latincom.2017.8240155
• 发表时间: 2017
• 期刊: IEEE Latincom
• 作者: Sarmadi, Soheil;Li, Mingyang;Chellappan, Sriram
• 通讯作者: Chellappan, Sriram

Pairing Users in Social Media via Processing Meta-data from Conversational Files

通过处理会话文件中的元数据在社交媒体中配对用户

• DOI: 10.1007/978-3-030-37188-3_7
• 发表时间: 2019
• 期刊: Big-Data Analytics (BDA
• 作者: Chaudhary, Meghana Sharma

HEliOS: huffman coding based lightweight encryption scheme for data transmission

• DOI: 10.1145/3360774.3360829
• 发表时间: 2019-11
• 期刊: Proceedings of the 16th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services
• 作者: Mazharul Islam;Novia Nurain;M. Kaykobad;Sriram Chellappan;A. Islam

A Novel Privacy-Preserving Socio-technical Platform for Detecting Cyber Abuse

用于检测网络滥用的新型隐私保护社会技术平台

• DOI: 10.1007/978-3-030-34980-6_33
• 发表时间: 2019
• 期刊: Computational Data and Social Networks. CSoNet 2019. Lecture Notes in Computer Science
• 作者: Chellappan, Sriram Fisk