Microsoft and Intel turn malware into images to help spot more threats
STAMINA has proven mostly effective so far, with just over 99 percent accuracy in classifying malware and a false positive rate slightly under 2.6 percent. However, it has its limits. It works well with small files, but it struggles with larger ones.
With enough refinement, though, this could be very useful. Most malware detection relies on extracting binary signatures or fingerprints, but the sheer number of signatures makes that impractical. This could help anti-malware tools effectively keep up and reduce the chances of security threats slipping past defenses.
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