Artificial intelligence based security requirements identification and testing

Abstract

The proposed systems and methods apply natural language processing to identify implicit security requirements flowing from input text narratively describing desired features for a software project. These systems and methods can identify hidden security requirements that may not be readily apparent from the features described in the input text. For example, a story may include a feature of a return URL (Uniform Resource Locator), which is the URL for the website to which a user will be redirected. A security vulnerability that would not be obvious from this feature is that a user might be directed to an attacker controlled site instead of the originally intended site. A security requirement that could counteract this vulnerability would be to include the feature of verifying all redirects go to Whitelisted Sites. The proposed systems and methods provide a framework for automated security requirements analysis capable of identifying unstated security requirements early on in a software development lifecycle using artificial intelligence techniques.