Antivirus and malware protection programs are great, but they have a fatal flaw: they can only protect your PC from threats they know about. It's not a terrible problem, but it gives attackers a brief window of opportunity to harm your computer every time they tweak their code. If a PC hasn't nabbed the latest update to its protection suite, it's vulnerable -- but it doesn't have to be that way. Researchers are using deep learning algorithms that can spot new malicious code naturally, without database updates.
If an artificial neural network can be trained to recognize a face, why can't it be trained to recognize potentially malicious code? Well, according to Israeli startup Deep Instinct, it can. The company is building a deep-learning antivirus suite that can (reportedly) spot new malware with 20% higher accuracy than today's best protection software. The claims are unverified, but the company's approach isn't without support: researchers at both Microsoft and Invincea have published papers demonstrating the potential of deep learning malware detection systems. One experiment found 95% of new malware without updates. That's encouraging.
Like most deep learning initiatives, self-learning malware detection software is still in the early stages -- but if successful, it could be a game changer. Check out TechnologyReview at the source link below for the full story.
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