首页    期刊浏览 2024年11月27日 星期三
登录注册

文章基本信息

  • 标题:Perceiving Kernel-Level Rootkits Using Data Structure Invariants
  • 本地全文:下载
  • 作者:G.Vijayalakshmi ; A.Anusha Priya
  • 期刊名称:International Journal of Innovative Research in Computer and Communication Engineering
  • 印刷版ISSN:2320-9798
  • 电子版ISSN:2320-9801
  • 出版年度:2015
  • 卷号:3
  • 期号:7
  • DOI:10.15680/ijircce.2015.0307148
  • 出版社:S&S Publications
  • 摘要:Rootkits affect system security by modifying kernel data structures to achieve a variety of maliciousgoals. While early rootkits modified control data structures, such as the system call table and values of functionpointers, recent work has demonstrated root kits that maliciously modify non control data. Most prior techniques forroot kit detection have focused solely on detecting control data modifications and, therefore, fail to detect such rootkits. This paper presents a novel technique to detect rootkits that modify both control and non control data. The mainidea is to externally observe the execution of the kernel during an inference phase and hypothesize invariants on kerneldata structures. A root kit detection phase uses these invariants as specifications of data structure integrity. During thisphase, violation of invariants indicates an infection. We have implemented Gibraltar, a prototype tool that infers kerneldata structure invariants and uses them to detect root kits. Experiments show that Gibraltar can effectively detectpreviously known rootkits, including those that modify non-control data structures.
  • 关键词:Kernel-level rootkits; non control data attacks; invariant inference; static and dynamic program;analysis.
国家哲学社会科学文献中心版权所有