CAREER: Privacy Preserving Security Analytics: When Security Meets Privacy

职业：隐私保护安全分析：当安全遇到隐私时

• 批准号: 2308730
• 负责人: Yuan Hong
• 金额: $ 50万
• 依托单位: University of Connecticut
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-01 至 2026-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2308730&HistoricalAwards=false
• 关键词: CAREER; Privacy; Preserving; Security; Analytics

A fast-growing number of enterprises and organizations have outsourced their security analytics tasks to external managed security service providers (MSSPs) for security monitoring and threat detection. However, such cost-effective and reliable security solutions currently request their service tenants to continuously outsource their large-scale and disparate datasets. This project tackles the privacy risks in such security analytics outsourcing services with rigorous privacy guarantees. This project aims to create a new paradigm of privacy preserving data analysis to privately perform real-time anomaly detection on both structured and unstructured data (e.g., network traffic, surveillance videos, system logs, and emails). The main goal is to fundamentally advance differential privacy and secure multiparty computation in this new context of privacy preserving security analytics. To this end, we propose novel differential privacy mechanisms and secure multiparty computation protocols, explore provable privacy guarantees with theoretical studies, and deploy the privacy preserving techniques in scalable real-time systems. After addressing the fundamental challenges for mitigating privacy risks in a wide variety of data and applications while ensuring high utility and efficiency, the expected research results can be leveraged to many other online monitoring and analysis applications. This project also integrates the research and education at intersections of privacy, security and data analysis. It develops a comprehensive educational and outreach program, including cybersecurity workforce training, educational materials development and distribution, K-12 outreach, and research dissemination to broader communities.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.

快速增长的企业和组织已将其安全分析任务外包给外部托管安全服务提供商（MSSP），以进行安全监控和威胁检测。但是，这种具有成本效益且可靠的安全解决方案目前要求其服务租户不断将其大规模和不同数据集外包。该项目可以通过严格的隐私保证来解决此类安全分析外包服务中的隐私风险。该项目旨在创建一个新的隐私范式保存数据分析，以私下对结构化和非结构化数据（例如网络流量，监视视频，系统日志和电子邮件）进行实时异常检测。主要目标是从根本上促进差异隐私并在保存安全分析的新环境中确保多方计算。为此，我们提出了新颖的差异隐私机制和安全的多方计算协议，通过理论研究探索可证明的隐私保证，并在可扩展的实时系统中部署隐私保护技术。在解决了减轻各种数据和应用程序中的隐私风险同时确保高公用事业和效率的基本挑战之后，可以将预期的研究结果用于许多其他在线监控和分析应用程序。该项目还将研究和教育整合到隐私，安全和数据分析的交集。它开发了一项全面的教育和外展计划，包括网络安全劳动力培训，教育材料的开发和分销，K-12外展以及对更广泛社区的研究传播。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子和更广泛影响的评估来通过评估来获得支持的，审查了审查的审查标准。

项目成果

Interpretation Attacks and Defenses on Predictive Models Using Electronic Health Records

• DOI: 10.1007/978-3-031-43418-1_27
• 发表时间: 2023
• 作者: Fereshteh Razmi;Jian Lou;Yuan Hong;Li Xiong

WPES '22: 21st Workshop on Privacy in the Electronic Society

WPES 22：第 21 届电子社会隐私研讨会

• DOI: 10.1145/3548606.3563220
• 发表时间: 2022
• 期刊: Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security
• 作者: Hong, Yuan;Wang, Lingyu
• 通讯作者: Wang, Lingyu

Text-CRS: A Generalized Certified Robustness Framework against Textual Adversarial Attacks

• DOI: 10.1109/sp54263.2024.00053
• 发表时间: 2023-07
• 期刊: ArXiv
• 作者: Xinyu Zhang;Hanbin Hong;Yuan Hong;Peng Huang;Binghui Wang;Zhongjie Ba;Kui Ren

UniAP: Protecting Speech Privacy With Non-Targeted Universal Adversarial Perturbations

• DOI: 10.1109/tdsc.2023.3242292
• 发表时间: 2024-01
• 期刊: IEEE Transactions on Dependable and Secure Computing
• 影响因子: 7.3
• 作者: Peng Cheng;Yuexin Wu;Yuan Hong;Zhongjie Ba;Feng Lin;Liwang Lu;Kui Ren

L-SRR: Local Differential Privacy for Location-Based Services with Staircase Randomized Response

• DOI: 10.1145/3548606.3560636
• 发表时间: 2022-09
• 期刊: Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security
• 作者: Han Wang;Hanbin Hong;Li Xiong;Zhan Qin;Yuan Hong