Detecting Cyber Security Vulnerabilities through Reactive Programming

Abstract

We propose a software architectural model, which uses reactive programming for collecting and filtering live tweets and interpreting their potential correlation to software vulnerabilities and exploits. We aim to investigate if we could discover the existence of exploits for disclosed vulnerabilities in Twitter data streams. Reactive programming is used for performing filtering and querying of tweet to find potential exploits. The result of processing Twitter data streams with reactive programming could be broadcasted, by pointing towards potential exploits, which might create a cyber-attack. They can also be entered as a new entry into existing overt or open source intelligence repositories.