TC: Medium: Exploiting Multicore and Hardware Acceleration to Perform Efficient Behavior-Based Attack Detection and Repair

TC：中：利用多核和硬件加速执行高效的基于行为的攻击检测和修复

• 批准号: 1065112
• 负责人: David Brumley
• 金额: $ 114.02万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1065112&HistoricalAwards=false
• 关键词: TC; Medium; Exploiting; Multicore; Hardware

This research investigates techniques to efficiently detect the first exploit against an unknown vulnerability on a user system, and then safely heal the system against further attacks. The research uses dynamic analysis -- the ability to monitor code as it executes -- because it can be used to check safety and security properties of actual executions and make sure that each step of the execution is safe. However, existing dynamic analysis techniques are far too slow for end users, and currently do not help user systems self-heal. This research investigates techniques to overcome these limitations by developing efficient dynamic analysis techniques, as well as techniques for diagnosing the root cause of an exploited vulnerability, repairing any damage done, and defending the system against further attacks.

这项研究研究如何有效地检测针对用户系统上的未知漏洞的第一次利用，然后安全地修复系统以抵御进一步的攻击。这项研究使用了动态分析--在代码执行时监控代码的能力--因为它可以用来检查实际执行的安全性和安全性属性，并确保执行的每个步骤都是安全的。然而，现有的动态分析技术对最终用户来说太慢了，目前无法帮助用户系统自我修复。这项研究通过开发高效的动态分析技术，以及诊断漏洞的根本原因、修复造成的任何损害和保护系统免受进一步攻击的技术，来研究克服这些限制的技术。