Earticle

초록

영어

Web application security is an important problem in today’s Internet. A major cause of this is that many developers are not equipped with the right skills to develop secure code. Because of limited time and resources, web engineers need help in recognizing vulnerable components. A useful approach to predict vulnerable code would allow them to prioritize security-auditing efforts. In this work, we compare the performance of different classification techniques in predicting vulnerable PHP files and propose an application of these classification rules. We performed empirical case studies on three large open source web-projects. Software metrics are investigated whether they are discriminative and predictive of vulnerable code, and can guide actions for improvement of code and development team and can prioritize validation and verification efforts. The results indicate that the metrics are discriminative and predictive of vulnerabilities.

목차

Abstract
 1. Introduction
 2. Software Metrics
 3. Approach
 4. Experimental Evaluation
  4.1. Data Set
  4.2. Classifiers
  4.3. Evaluation Metrics
  4.4. Results
 5. Application
 6. Threats to Validity
 7. Related Work
  7.1. Fault Prediction
  7.2. Vulnerability prediction
  7.3. Equations
 8. Conclusion
 References

키워드

저자

• Mamdouh Alenezi [ College of Computer & Information Sciences, Prince Sultan University Riyadh, Saudi Arabia ]
• Ibrahim Abunadi [ College of Computer & Information Sciences, Prince Sultan University Riyadh, Saudi Arabia ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Security and Its Applications

• 간기

  격월간

• pISSN

  1738-9976

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605