Towards a hybrid framework for detecting input manipulation vulnerabilities

• Main Authors: DING, Sun, TAN, Hee Beng Kuan, SHAR, Lwin Khin, PADMANABHUNI, Bindu Madhavi
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2013
• Subjects: Vulnerability detection; framework; formal verification; prediction; data mining; input validation; specification; verification; input manipulation vulnerabilities; Information Security; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/4837; https://ink.library.smu.edu.sg/context/sis_research/article/5840/viewcontent/Towards_a_hybrid_framework_for_detecting_input_manipulation_2013_av.pdf
• Institution: Singapore Management University

Input manipulation vulnerabilities such as SQL Injection, Cross-site scripting, Buffer Overflow vulnerabilities are highly prevalent and pose critical security risks. As a result, many methods have been proposed to apply static analysis, dynamic analysis or a combination of them, to detect such secu...