Cybersecurity Big Data and Analytics Sharing Platform

网络安全大数据和分析共享平台

• 批准号: 1719477
• 负责人: Hsinchun Chen
• 金额: $ 18万
• 依托单位: University of Arizona
• 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: 2017-03-15 至 2022-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1719477&HistoricalAwards=false
• 关键词: Cybersecurity; Big; Data; Analytics; Sharing

Cybersecurity has become a significant issue that presents new challenges to individuals, industry, and government. To help deal with complex cybersecurity challenges, the international Intelligence and Security Informatics (ISI) community has published high-impact, Big Data driven cybersecurity research since 2003. Despite the many novel advances in data-driven cybersecurity research, there is no sharing platform that aggregates and provides data and tools used and developed in cybersecurity research for the larger cybersecurity community. The proposed project aims to fill this gap by developing the Cybersecurity Big Data and Analytics Sharing Platform to encourage cybersecurity researchers to share their data, tools, and analytical approaches. In addition, the project will support two Security Big Data and Analytics Sharing Workshops to engage the community in the platform development. Upon project completion, the platform will be open for access by the broad cybersecurity research and education community.The proposed data sharing platform would enable the publication of high-impact, reproducible, and cutting edge research to advance scientific discoveries. Such a platform would also enhance the educational experience for cybersecurity students, specifically CyberCorps SFS students as they prepare to enter the cybersecurity workforce. The proposed project will provide value to both cybersecurity researchers and students by providing data for cutting-edge research and enhanced educational experiences. In addition, this project will also have significant value to government agencies and other organizations interested in developing cyber threat intelligence knowledge. The project team will consist of leading scholars in Big Data Security.

网络安全已成为一个重要问题，对个人、行业和政府提出了新的挑战。为了帮助应对复杂的网络安全挑战，自2003年以来，国际情报和安全信息学（ISI）社区已经发布了高影响力的大数据驱动的网络安全研究。尽管数据驱动的网络安全研究取得了许多新的进展，但没有共享平台可以为更大的网络安全社区聚合和提供网络安全研究中使用和开发的数据和工具。该项目旨在通过开发网络安全大数据和分析共享平台来填补这一空白，以鼓励网络安全研究人员分享他们的数据，工具和分析方法。此外，该项目还将支持两个安全大数据和分析共享研讨会，以吸引社区参与平台开发。项目完成后，该平台将向广大网络安全研究和教育界开放。拟议的数据共享平台将使高影响力，可重复性和前沿研究的出版物能够推动科学发现。这样的平台还将增强网络安全学生的教育体验，特别是CyberCorps SFS学生，因为他们准备进入网络安全劳动力市场。拟议的项目将为网络安全研究人员和学生提供价值，为尖端研究和增强教育体验提供数据。此外，该项目还将对政府机构和其他有兴趣开发网络威胁情报知识的组织具有重要价值。该项目团队将由大数据安全领域的顶尖学者组成。

项目成果

Detecting Cyber Threats in Non-English Dark Net Markets: A Cross-Lingual Transfer Learning Approach

• DOI: 10.1109/isi.2018.8587404
• 发表时间: 2018-11
• 期刊: 2018 IEEE International Conference on Intelligence and Security Informatics (ISI)
• 作者: Mohammadreza Ebrahimi;M. Surdeanu;Sagar Samtani;Hsinchun Chen

A Generative Adversarial Learning Framework for Breaking Text-Based CAPTCHA in the Dark Web

• DOI: 10.1109/isi49825.2020.9280537
• 发表时间: 2020-11
• 期刊: 2020 IEEE International Conference on Intelligence and Security Informatics (ISI)
• 作者: Ning Zhang;Mohammadreza Ebrahimi;Weifeng Li;Hsinchun Chen

Vulnerability Assessment, Remediation, and Automated Reporting: Case Studies of Higher Education Institutions

漏洞评估、修复和自动报告：高等教育机构案例研究

• 发表时间: 2018
• 期刊: 2018 IEEE Conference on Intelligence and Security Informatics
• 作者: C. Harrell, S. Samtani

Incremental Hacker Forum Exploit Collection and Classification for Proactive Cyber Threat Intelligence: An Exploratory Study

• DOI: 10.1109/isi.2018.8587336
• 发表时间: 2018-11
• 期刊: 2018 IEEE International Conference on Intelligence and Security Informatics (ISI)
• 作者: Richard Ryan Williams;Sagar Samtani;Mark W. Patton;Hsinchun Chen

Benchmarking Vulnerability Assessment Tools for Enhanced Cyber-Physical System (CPS) Resiliency

用于增强网络物理系统 (CPS) 弹性的基准漏洞评估工具

• 发表时间: 2018
• 期刊: 2018 IEEE Conference on Intelligence and Security Informatics
• 作者: E. McMahon, M. Patton