An Automated Vulnerability Detection and Remediation Method for Software Security

Jeesoo Jurn, Taeeun Kim and Hwankuk Kim
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Jeesoo Jurn: Korea Internet & Security Agency, 9, Jinheung-gil, Naju-si, Jeollanam-do 58324, Korea
Taeeun Kim: Korea Internet & Security Agency, 9, Jinheung-gil, Naju-si, Jeollanam-do 58324, Korea
Hwankuk Kim: Korea Internet & Security Agency, 9, Jinheung-gil, Naju-si, Jeollanam-do 58324, Korea

Sustainability, 2018, vol. 10, issue 5, 1-12

Abstract: As hacking techniques become more sophisticated, vulnerabilities have been gradually increasing. Between 2010 and 2015, around 80,000 vulnerabilities were newly registered in the CVE (Common Vulnerability Enumeration), and the number of vulnerabilities has continued to rise. While the number of vulnerabilities is increasing rapidly, the response to them relies on manual analysis, resulting in a slow response speed. It is necessary to develop techniques that can detect and patch vulnerabilities automatically. This paper introduces a trend of techniques and tools related to automated vulnerability detection and remediation. We propose an automated vulnerability detection method based on binary complexity analysis to prevent a zero-day attack. We also introduce an automatic patch generation method through PLT/GOT table modification to respond to zero-day vulnerabilities.

Keywords: security; vulnerability; automation; fuzzing; symbolic execution (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
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