MalSee: Using vision, hearing, and other features to detect malware Navy SBIR FY2015.1 Sol No.: Navy SBIR FY2015.1 Topic No.: N151-067 Topic Title: MalSee: Using vision, hearing, and other features to detect malware Proposal No.: N151-067-0409 Firm: Mayachitra, Inc. 5266 Hollister Avenue, Suite 229 Santa Barbara, California 93111 Contact: Kenneth Sullivan Phone: (805) 967-9828 Abstract: We propose MalSee to leverage recent research performed by principals at Mayachitra to recast the suspect software binaries as images and exploit computer vision techniques to automatically classify malware. This approach offers the following advantages: Robustness to variations, speed and scalability, route for further exploration. Benefits: Despite increasing efforts on computer security, malware continues to be a large problem for everyone from private individuals to national governments. The proposed system can quickly adapt to detection of new malware variants, and operates very quickly to scale to large numbers of tests. Return