"Microsoft and Intel Project Converts Malware Into Images Before Analyzing It"

Microsoft researchers are working with Intel Labs on a project, called STAMINA (Static Malware-as-Image Network Analysis). The project explores a new approach to detecting and classifying malware that involves the application of deep learning techniques. The method proposed by Microsoft and Intel converts malware samples into grayscale images, which are then scanned for textual and structural patterns associated with malware samples. The steps involved in STAMINA include preprocessing, transfer learning, validation, and classification. According to the research team, STAMINA has identified and classified malware samples at an accuracy rate of 99.07%. These results highlight the importance of exploring the use of machine learning techniques in malware classification. This article continues to discuss how STAMINA works, the concept of deep learning, the current limitations of the STAMINA project, and Microsoft's increased reliance on machine learning for detecting emerging threats. 

ZDNet reports "Microsoft and Intel Project Converts Malware Into Images Before Analyzing It"