CAREER: Privacy Preserving Security Analytics: When Security Meets Privacy

越来越多的企业和组织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。然而，这种经济高效且可靠的安全解决方案目前要求其服务租户不断外包其大规模和不同的数据集。该项目通过严格的隐私保障来解决此类安全分析外包服务中的隐私风险。该项目旨在创建隐私保护数据分析的新范例，以私下对结构化和非结构化数据(例如，网络流量、监控视频、系统日志和电子邮件)执行实时异常检测。主要目标是在这种隐私保护安全分析的新背景下，从根本上推进差异隐私和安全多方计算。为此，我们提出了新颖的差分隐私机制和安全多方计算协议，通过理论研究探索了可证明的隐私保障，并将隐私保护技术部署在可扩展的实时系统中。在解决了在确保高实用性和高效率的同时缓解各种数据和应用程序中的隐私风险的基本挑战之后，预期的研究成果可以被许多其他在线监测和分析应用程序所利用。该项目还整合了隐私、安全和数据分析交叉口的研究和教育。它开发了一项全面的教育和推广计划，包括网络安全劳动力培训、教育材料开发和分发、K-12推广以及向更广泛社区传播研究。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.