Visible to the public Biblio

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2020-09-28
Lv, Chengcheng, Zhang, Long, Zeng, Fanping, Zhang, Jian.  2019.  Adaptive Random Testing for XSS Vulnerability. 2019 26th Asia-Pacific Software Engineering Conference (APSEC). :63–69.
XSS is one of the common vulnerabilities in web applications. Many black-box testing tools may collect a large number of payloads and traverse them to find a payload that can be successfully injected, but they are not very efficient. And previous research has paid less attention to how to improve the efficiency of black-box testing to detect XSS vulnerability. To improve the efficiency of testing, we develop an XSS testing tool. It collects 6128 payloads and uses a headless browser to detect XSS vulnerability. The tool can discover XSS vulnerability quickly with the ART(Adaptive Random Testing) method. We conduct an experiment using 3 extensively adopted open source vulnerable benchmarks and 2 actual websites to evaluate the ART method. The experimental results indicate that the ART method can effectively improve the fuzzing method by more than 27.1% in reducing the number of attempts before accomplishing a successful injection.
2018-02-14
Petrică, G., Axinte, S. D., Bacivarov, I. C., Firoiu, M., Mihai, I. C..  2017.  Studying cyber security threats to web platforms using attack tree diagrams. 2017 9th International Conference on Electronics, Computers and Artificial Intelligence (ECAI). :1–6.

Used by both information systems designers and security personnel, the Attack Tree method provides a graphical analysis of the ways in which an entity (a computer system or network, an entire organization, etc.) can be attacked and indicates the countermeasures that can be taken to prevent the attackers to reach their objective. In this paper, we built an Attack Tree focused on the goal “compromising the security of a Web platform”, considering the most common vulnerabilities of the WordPress platform identified by CVE (Common Vulnerabilities and Exposures), a global reference system for recording information regarding computer security threats. Finally, based on the likelihood of the attacks, we made a quantitative analysis of the probability that the security of the Web platform can be compromised.