Abstract:
Demands upon the cybersecurity teams to improve defensive techniques have increased year after year. Machine learning is an application that learns from experience and improves predictive accuracy over time though the use of Artificial Intelligence. Joining Cybersecurity and Machine Learning, together you can get a strong defence against current and future increasing threats in the cyberinfrastructure.
Increased pressure on the cybersecurity professional is, to get ahead of this hostile behaviour. There is a growing need to create a form of automated detection systems using machine learning targeting these cyber-attacks. The system, would be able to learn, diagnose and defend the cyberinfrastructure. The creation of a machine learning technique for cybersecurity is also open to its own adversarial attacks.
Spam, Malware and Phishing, all have use cases of machine learning techniques, which have potential in combating threats in an offensive and defensive ever growing data environment. Intrusion detection systems can also benefit from utilising machine learning techniques .
This paper is to discuss if machine learning can aide the cyber security professional in this combative environment.
Resources :
- CSU Library, Google Scholar and other methods to research papers, journals, and other academic sources.
- Online blog to track project progress and milestones
- Weekly progress report
Alignment of this project with my course specialisation :
Currently I am studying a Master of Information Systems Security. This project aligns with the main subject (Professional Systems Security) and electives of the course (Hacking Countermeasures), (Server Administration Windows/Linux). All of which are avenues of a cybersecurity defence which Machine learning could be used in.