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Characteristic Classification and Correlation Analysis of Source-Level Vulnerabilities in the Linux Kernel

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Computational Intelligence and Security (CIS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3802))

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Abstract

Although studies regarding the classification and analysis of source-level vulnerabilities in operating systems are not direct and practical solutions to the exploits with which computer systems are attacked, it is important that these studies supply the elementary technology for the development of effective security mechanisms. Linux systems are widely used on the Internet and in intra-net environments. However, researches regarding the fundamental vulnerabilities in the Linux kernel have not been satisfactorily conducted. In this paper, characteristic classification and correlation analysis of source-level vulnerabilities in the Linux kernel, open to the public and listed on the SecurityFocus site for the 6 years from 1999 to 2004, are presented. This study will enable Linux kernel maintenance groups to understand the wide array of vulnerabilities, to analyze the characteristics of the attack abusing vulnerabilities, and to prioritize their development effort according to the impact of these vulnerabilities on the Linux systems.

This research was supported by the MIC(Ministry of Information and Communication), Korea, under the ITRC(Information Technology Research Center) support program supervised by the IITA(Institute of Information Technology Assessment).

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© 2005 Springer-Verlag Berlin Heidelberg

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Ko, K., Jang, I., Kang, Yh., Lee, J., Eom, Y.I. (2005). Characteristic Classification and Correlation Analysis of Source-Level Vulnerabilities in the Linux Kernel. In: Hao, Y., et al. Computational Intelligence and Security. CIS 2005. Lecture Notes in Computer Science(), vol 3802. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596981_172

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  • DOI: https://doi.org/10.1007/11596981_172

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30819-5

  • Online ISBN: 978-3-540-31598-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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