Machine learning can sniff out tell-tale signs of shady URLs so you don’t get phished.
The problem: The internet is riddled with websites set up for the sole purpose of stealing a user’s information or installing malware on a victim’s machine. Antivirus companies blacklist them as fast as they can, but with new sites launched every day, it’s a Sisyphean effort to keep up.
AI to the rescue: A new system called URLNet uses neural networks that look at character-level and word-level combinations in—you guessed it—the site’s URL to detect a site’s risk. URLs contain clues to whether a site is malicious, like length and misspelled domain names.
Results: The researchers trained URLNet on two data sets, one containing a million legit and malicious URLs and one with five million. In each case, URLNet beat other current systems at detecting suspicious sites.
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“I have suddenly switched my views on whether these things are going to be more intelligent than us.”
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Deep learning pioneer Geoffrey Hinton has quit Google
Hinton will be speaking at EmTech Digital on Wednesday.
We are hurtling toward a glitchy, spammy, scammy, AI-powered internet
Large language models are full of security vulnerabilities, yet they’re being embedded into tech products on a vast scale.
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