Predicting common web application vulnerabilities from input validation and sanitization code patterns
Software defect prediction studies have shown that defect predictors built from static code attributes are useful and effective. On the other hand, to mitigate the threats posed by common web application vulnerabilities, many vulnerability detection approaches have been proposed. However, finding al...
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sg-ntu-dr.10356-975112020-03-07T13:24:47Z Predicting common web application vulnerabilities from input validation and sanitization code patterns Shar, Lwin Khin Tan, Hee Beng Kuan School of Electrical and Electronic Engineering International Conference on Automated Software Engineering (27th : 2012 : Essen, Germany) DRNTU::Engineering::Electrical and electronic engineering Software defect prediction studies have shown that defect predictors built from static code attributes are useful and effective. On the other hand, to mitigate the threats posed by common web application vulnerabilities, many vulnerability detection approaches have been proposed. However, finding alternative solutions to address these risks remains an important research problem. As web applications generally adopt input validation and sanitization routines to prevent web security risks, in this paper, we propose a set of static code attributes that represent the characteristics of these routines for predicting the two most common web application vulnerabilities—SQL injection and cross site scripting. In our experiments, vulnerability predictors built from the proposed attributes detected more than 80% of the vulnerabilities in the test subjects at low false alarm rates. 2013-07-18T02:51:02Z 2019-12-06T19:43:27Z 2013-07-18T02:51:02Z 2019-12-06T19:43:27Z 2012 2012 Conference Paper Shar, L. K., & Tan, H. B. K. (2012). Predicting common web application vulnerabilities from input validation and sanitization code patterns. Proceedings of the 27th IEEE/ACM International Conference on Automated Software Engineering - ASE 2012. https://hdl.handle.net/10356/97511 http://hdl.handle.net/10220/11832 10.1145/2351676.2351733 en © 2012 ACM. |
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DRNTU::Engineering::Electrical and electronic engineering Shar, Lwin Khin Tan, Hee Beng Kuan Predicting common web application vulnerabilities from input validation and sanitization code patterns |
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Software defect prediction studies have shown that defect predictors built from static code attributes are useful and effective. On the other hand, to mitigate the threats posed by common web application vulnerabilities, many vulnerability detection approaches have been proposed. However, finding alternative solutions to address these risks remains an important research problem. As web applications generally adopt input validation and sanitization routines to prevent web security risks, in this paper, we propose a set of static code attributes that represent the characteristics of these routines for predicting the two most common web application vulnerabilities—SQL injection and cross site scripting. In our experiments, vulnerability predictors built from the proposed attributes detected more than 80% of the vulnerabilities in the test subjects at low false alarm rates. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Shar, Lwin Khin Tan, Hee Beng Kuan |
format |
Conference or Workshop Item |
author |
Shar, Lwin Khin Tan, Hee Beng Kuan |
author_sort |
Shar, Lwin Khin |
title |
Predicting common web application vulnerabilities from input validation and sanitization code patterns |
title_short |
Predicting common web application vulnerabilities from input validation and sanitization code patterns |
title_full |
Predicting common web application vulnerabilities from input validation and sanitization code patterns |
title_fullStr |
Predicting common web application vulnerabilities from input validation and sanitization code patterns |
title_full_unstemmed |
Predicting common web application vulnerabilities from input validation and sanitization code patterns |
title_sort |
predicting common web application vulnerabilities from input validation and sanitization code patterns |
publishDate |
2013 |
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https://hdl.handle.net/10356/97511 http://hdl.handle.net/10220/11832 |
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1681035908206297088 |