On the Effectiveness of Software Diversity: A Systematic Study on Real-World Vulnerabilities

Many systems have been introduced to detect software intrusions by comparing the outputs and behavior of diverse replicas when they are processing the same, potentially malicious, input. When these replicas are constructed using off-the-shelf software products, it is assumed that they are diverse an...

全面介紹

Saved in:
書目詳細資料
Main Authors: HAN, Jin, GAO, Debin, DENG, Robert H.
格式: text
語言:English
出版: Institutional Knowledge at Singapore Management University 2009
主題:
在線閱讀:https://ink.library.smu.edu.sg/sis_research/327
https://ink.library.smu.edu.sg/context/sis_research/article/1326/viewcontent/Han2009_Chapter_OnTheEffectivenessOfSoftware_pv.pdf
標簽: 添加標簽
沒有標簽, 成為第一個標記此記錄!
機構: Singapore Management University
語言: English
實物特徵
總結:Many systems have been introduced to detect software intrusions by comparing the outputs and behavior of diverse replicas when they are processing the same, potentially malicious, input. When these replicas are constructed using off-the-shelf software products, it is assumed that they are diverse and not compromised simultaneously under the same attack. In this paper, we analyze vulnerabilities published in 2007 to evaluate the extent to which this assumption is valid. We focus on vulnerabilities in application software, and show that the majority of these software products --- including those providing the same service (and therefore multiple software substitutes can be used in a replicated system to detect intrusions) and those that run on multiple operating systems (and therefore the same software can be used in a replicated system with different operating systems to detect intrusions) --- either do not have the same vulnerability or cannot be compromised with the same exploit. We also find evidence that indicates the use of diversity in increasing attack tolerance for other software. These results show that systems utilizing off-the-shelf software products to introduce diversity are effective in detecting intrusions.