An automated vulnerability detection and remediation method for software security

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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.

Figures

  • Table 1. Automated Vulnerability Detection Tool Comparison.
  • Table 2. Binary Hardening technique comparison.
  • Figure 1. Automated Vulnerability Detection and Remediation Architecture. Figure 1. Automated Vulnerability Detection and Remediation Architecture.
  • Table 3. List of Vulnerable Functions by Vulnerability Type.
  • Table 4. Halstead Complexity Metrics.
  • Table 5. Functions for Vulnerability Scoring.
  • Figure 2. ELF file structure modification. Figure 2. ELF file structure modification.
  • Figure 3. Secure_libs_loader operation process.

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CITATION STYLE

APA

Jurn, J., Kim, T., & Kim, H. (2018). An automated vulnerability detection and remediation method for software security. Sustainability (Switzerland), 10(5). https://doi.org/10.3390/su10051652

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