Web application vulnerability prediction using hybrid program analysis and machine learning

Web application vulnerability prediction using hybrid program analysis and machine learning

Due to limited time and resources, web software engineers need support in identifying vulnerable code. A practical approach to predicting vulnerable code would enable them to prioritize security auditing efforts. In this paper, we propose using a set of hybrid (staticþdynamic) code attributes that c...

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Bibliographic Details
Main Authors: SHAR, Lwin Khin, BRIAND, Lionel, TAN, Hee Beng Kuan
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2014
Subjects:
Vulnerability prediction
security measures
input validation and sanitization
program analysis
empirical study
Information Security
Programming Languages and Compilers
Online Access:https://ink.library.smu.edu.sg/sis_research/4895
https://ink.library.smu.edu.sg/context/sis_research/article/5898/viewcontent/Web_Application___PV.pdf
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Institution: Singapore Management University
Language: English

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https://ink.library.smu.edu.sg/sis_research/4895
https://ink.library.smu.edu.sg/context/sis_research/article/5898/viewcontent/Web_Application___PV.pdf

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