CSR-AES-RCS: Scalable and Efficient Dynamic Information Flow Tracking in Multithreaded Programs

CSR-AES-RCS：多线程程序中可扩展且高效的动态信息流跟踪

• 批准号: 0719791
• 负责人: Rajiv Gupta
• 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: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2007-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0719791&HistoricalAwards=false
• 关键词: CSR; AES; RCS; Scalable; Efficient

This project is aimed at developing scalable as well as highly efficient techniques for performing Dynamic Information Flow Tracking (DIFT) in multithreaded programs.The approach being developed is based upon dynamic instrumention of binaries to perform information flow tracking so that the application source code is not required and applications involving dynamically generated code can be handled. For achieving scalability, a novel strategy based upon the integration of checkpointing logging with fine-grained tracing is being used. Initially the program is executed with logging turned on. When DIFT needs to be performed, the execution of relevant execution intervals is replayed and fine-grained tracing is selectively performed.For achieving further efficiency, idle cores on a multicore processor are being used.Dynamically, a monitoring thread is generated by analyzing the application binary and the monitoring thread and the application execute concurrently on different cores.By achieving scalability and efficiency, the developed techniques can be applied to realistic programs such as server programs. The DIFT techniques are being evaluated in context of following applications: (debugging) bug location and avoidance; (security) software attack detection and location of vulnerability; and (data validation) maintaining lineage of scientific data.

该项目旨在开发可扩展的和高效的技术，用于在多线程程序中执行动态信息流动跟踪（DIFT）。开发的方法是基于二进制文件的动态仪器来执行信息流量流跟踪，以便不需要应用程序源代码和涉及涉及的应用程序代码的应用程序源代码。为了实现可伸缩性，正在使用基于将检查点记录与细颗粒跟踪集成的新型策略。最初，该程序是在登录时执行的。当需要执行DIFT时，重新测试相关执行间隔并选择性地进行细粒度的跟踪。为了实现进一步的效率，正在使用多层处理器上的空闲核心，从而使用了监视线程，从而通过分析应用程序和应用程序的范围来实现型号，并效率地进行了范围。诸如服务器程序之类的程序。通过以下应用程序评估DIFT技术：（调试）错误位置和避免； （安全）软件攻击检测和漏洞的位置； （数据验证）维持科学数据的谱系。