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http://dx.doi.org/10.5762/KAIS.2017.18.11.94

Technology Analysis on Automatic Detection and Defense of SW Vulnerabilities  

Oh, Sang-Hwan (Korea Internet & Security Agency)
Kim, Tae-Eun (Korea Internet & Security Agency)
Kim, HwanKuk (Korea Internet & Security Agency)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.18, no.11, 2017 , pp. 94-103 More about this Journal
Abstract
As automatic hacking tools and techniques have been improved, the number of new vulnerabilities has increased. The CVE registered from 2010 to 2015 numbered about 80,000, and it is expected that more vulnerabilities will be reported. In most cases, patching a vulnerability depends on the developers' capability, and most patching techniques are based on manual analysis, which requires nine months, on average. The techniques are composed of finding the vulnerability, conducting the analysis based on the source code, and writing new code for the patch. Zero-day is critical because the time gap between the first discovery and taking action is too long, as mentioned. To solve the problem, techniques for automatically detecting and analyzing software (SW) vulnerabilities have been proposed recently. Cyber Grand Challenge (CGC) held in 2016 was the first competition to create automatic defensive systems capable of reasoning over flaws in binary and formulating patches without experts' direct analysis. Darktrace and Cylance are similar projects for managing SW automatically with artificial intelligence and machine learning. Though many foreign commercial institutions and academies run their projects for automatic binary analysis, the domestic level of technology is much lower. This paper is to study developing automatic detection of SW vulnerabilities and defenses against them. We analyzed and compared relative works and tools as additional elements, and optimal techniques for automatic analysis are suggested.
Keywords
Automatic-Analysis; Concolic-Execution; Fuzzing; Patch-Generation; Security-Vulnerability; Symbolic-Execution;
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Times Cited By KSCI : 2  (Citation Analysis)
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