Phase II IUCRC George Mason University: Center for Cybersecurity Analytics and Automation CCAA

第二阶段 IUCRC 乔治梅森大学：网络安全分析和自动化中心 CCAA

• 批准号: 1822094
• 负责人: Sushil Jajodia
• 金额: $ 49.96万
• 依托单位: George Mason University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1822094&HistoricalAwards=false
• 关键词: Phase; II; IUCRC; George; Mason

Cyber warfare has become a major threat to national security, and the increasing sophistication of cyber attacks calls for innovative analytical and automation capabilities to face advanced, persistent, and evolving adversaries. The Center for Cybersecurity Analytics and Automation (CCAA) will develop a range of such new capabilities through a collaborative and multidisciplinary approach involving three university sites and a broad range of industry and government sponsors. At the core of the Center's strategy is the goal to advance the state of art in sense-making, decision making, and resilience in order to enable systems to sustain cyber missions against sophisticated attacks. CCAA brings together experts in cybersecurity, formal modeling, and data-driven analytics to advance cyber defense on multiple fronts, namely, (a) robust and scalable sense-making for dynamic and predictive cyber analytics using large-scale heterogeneous cyber artifacts, (b) adaptive and autonomic decision-making for creating defense strategies and courses of action that are provably correct and operationally safe using mission requirements, security policies, guidelines, and system configurations, and (c) making resilience and agility inherent properties of cyber and cyber physical systems to enable real-time deterrence, deception, and mitigation. The George Mason University site will provide expertise in attack modeling, software security, and stochastic optimization. The Center's research will advance the state of the art in cyber defense against the most sophisticated threats. Through an increased focus on technology transfer, CCAA will enable organizations to deploy new tools and analytical capabilities to effectively and efficiently secure their systems against advanced threats capable of circumventing traditional defenses. Students at all levels will be actively involved in the research and will have ample opportunities to engage with industry sponsors and other university sites trough internships and extended cross-site visits. Participation of undergraduate and high school students, female students, and underrepresented minorities will also be actively promoted. The Center will create and maintain a center-wide repository to make research products such as datasets, code, tools, experimental results, and draft manuscripts available to all of the Center's members. The repository will be accessible through the Center's website (http://www.ccaa-nsf.org/ ). Consistent with the Center's bylaws and with any applicable requirements of individual universities or NSF, several of these products will be made available to the broader research and industry communities. The repository will be actively maintained during the entire duration of the Phase II effort, and it will remain online beyond the end of the project.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

网络战争已成为国家安全的主要威胁，网络攻击的日益复杂性要求创新的分析和自动化能力，以面对先进，持久和不断发展的对手。 网络安全分析和自动化中心（CCAA）将通过涉及三所大学以及广泛的行业和政府赞助商的协作和多学科方法开发一系列此类新功能。 该中心战略的核心是推进感知、决策和恢复能力的最新发展，以使系统能够抵御复杂的攻击。CCAA汇集了网络安全、正式建模和数据驱动分析方面的专家，以在多个方面推进网络防御，即：（a）使用大规模异构网络工件进行动态和预测性网络分析的稳健和可扩展的意义制定，（B）自适应和自主决策，用于创建防御战略和行动方案，这些战略和行动方案可证明是正确的，并使用使命要求进行操作安全，安全政策、指导方针和系统配置，以及（c）使网络和网络物理系统具有弹性和灵活性的固有属性，以实现实时威慑、欺骗和缓解。 乔治梅森大学网站将提供攻击建模、软件安全和随机优化方面的专业知识。该中心的研究将推进最先进的网络防御技术，以应对最复杂的威胁。 通过更加关注技术转让，CCAA将使组织能够部署新的工具和分析能力，以有效和高效地保护其系统免受能够绕过传统防御的高级威胁。 各级学生将积极参与研究，并将有充分的机会与行业赞助商和其他大学网站通过实习和扩大跨网站访问。 还将积极促进大学生和高中生、女生以及代表性不足的少数民族的参与。 该中心将创建和维护一个中心范围的存储库，使研究产品，如数据集，代码，工具，实验结果和草稿提供给中心的所有成员。 可通过中心的网站（http：//www.example.com）访问该储存库。www.ccaa-nsf.org/ 根据中心的章程以及各个大学或NSF的任何适用要求，其中一些产品将提供给更广泛的研究和行业社区。 在第二阶段的整个工作期间，该存储库将被积极维护，并将在项目结束后保持在线状态。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

An Outsourcing Model for Alert Analysis in a Cybersecurity Operations Center

网络安全运营中心警报分析的外包模型

• DOI: 10.1145/3372498
• 发表时间: 2020
• 期刊: ACM Transactions on the Web
• 影响因子: 3.5
• 作者: Shah, Ankit;Ganesan, Rajesh;Jajodia, Sushil;Cam, Hasan
• 通讯作者: Cam, Hasan

Late Deep Fusion of Color Spaces to Enhance Finger Photo Presentation Attack Detection in Smartphones

色彩空间后期深度融合增强智能手机中手指照片呈现攻击检测

• DOI: 10.3390/app122211409
• 发表时间: 2022
• 期刊: Applied Sciences
• 作者: Marasco, Emanuela;Vurity, Anudeep
• 通讯作者: Vurity, Anudeep

Capture the Bot: Using Adversarial Examples to Improve CAPTCHA Robustness to Bot Attacks

• DOI: 10.1109/mis.2020.3036156
• 发表时间: 2020-10
• 期刊: IEEE Intelligent Systems
• 影响因子: 6.4
• 作者: Dorjan Hitaj;B. Hitaj;S. Jajodia;L. Mancini

Biometric multi‐factor authentication: On the usability of the FingerPIN scheme

生物识别多因素身份验证：关于 FingerPIN 方案的可用性

• DOI: 10.1002/spy2.261
• 发表时间: 2023
• 期刊: SECURITY AND PRIVACY
• 影响因子: 1.9
• 作者: Marasco, Emanuela;Albanese, Massimiliano;Patibandla, Venkata Vamsi;Vurity, Anudeep;Sriram, Sumanth Sai
• 通讯作者: Sriram, Sumanth Sai

Detecting "0-Day" Vulnerability: An Empirical Study of Secret Security Patch in OSS

• DOI: 10.1109/dsn.2019.00056
• 发表时间: 2019-06
• 期刊: 2019 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)
• 作者: Xinda Wang;Kun Sun;A. Batcheller;S. Jajodia