Machine learning is becoming more important to cybersecurity every day. As I’ve written before , it’s a powerful weapon against the large-scale automation favored by today’s threat actors, but the dynamic between attackers and defenders is evolving.
Nowadays, machine learning is mostly used by security software to ingest massive quantities of data and identify threats, but that will all soon change as increasingly sophisticated cybercriminals tap into their own machine learning tools to counter this. The early stages of this malicious machine learning will likely take the form of bad guys directly targeting the good guys’ algorithms directly to sabotage, mislead and reverse-engineer them.
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