I have been talking about artificial intelligence (AI) and machine learning (ML) in cyber security quite a bit lately. My latest two essays you can find as guest posts on TowardsDataScience and DarkReading.
Following is a summary of the latest AI and ML posts with quick summaries:
- Machine Learning and AI – What’s the Scoop for Security Monitoring? – A bit of a supervised-biased post on ML in cyber. It talks about the use of deep learning in cyber hunting and shortly outlines my core point in the ML/AI discussion about capturing expert knowledge rather than experimenting with different algorithms to find anomalies or attacks.
- Unsupervised Machine Learning in Cyber Security – This post balances out the previous one that was a bit too supervised ML heavy and discusses some of the challenges with unsupervised ML in security.
- AI and Machine Learning in Cyber Security – What Zen Teaches About Insights A really fun post where I talk a little bit about Zen and how it relates to artificial intelligence in cyber. It gives a bit of an overview of the ML/AI environment for cyber security and elaborates where those approaches work well and where they don’t. As an added bonus, it talks about Zen koans, which I have grown very fond of.
- AI in Cybersecurity: Where We Stand & Where We Need to Go This is a darkreading post that is a short and fairly concise version of my general AI/ML points of view.
I’d love to hear your comments – be that on twitter or as comments on the posts!
This is a Security Bloggers Network syndicated blog post authored by Raffael Marty. Read the original post at: Security Intelligence and Big Data | raffy.ch – blog