State of the Art: Automated Black-Box Web Application Vulnerability Testing

By Jason Bau, Elie Bursztein, Divij Gupta, John C. Mitchell. IEEE Symposium on Security and Privacy, 2010

368 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems

View Paper: https://www.semanticscholar.org/paper/b51273c1af3d9740c9631775e16a31a153d90aea

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Sorelle A. Friedler
2. Carlos Eduardo Scheidegger
3. Suresh Venkatasubramanian
4. Qing-Long Han
5. Jun Zhang
6. Philip Adler
7. Brandon Smith
8. Gabriel Rybeck

In Information Systems

1. Qing-Long Han
2. Suresh Venkatasubramanian
3. Carlos Eduardo Scheidegger
4. Sorelle A. Friedler
5. Jun Zhang
6. Yang Xiang

Citations in the corpus

• Auditing Black-box Models by Obscuring Features (2016, background): “addressed separately from machine learning in the domain of auditing black-box web applications for security vulnerabilities [2] or in validating known (non black-box) models [11].”
• Detecting and Preventing Cyber Insider Threats: A Survey (2018, background): “, port scanning [14], network vulnerability scanning [15], Web application vulnerability scanning [16], database vulnerability scanning [17] and etc.”