Tudor Dumitras, an assistant professor of electrical and computer engineering with appointments in UMIACS and the Maryland Cybersecurity Center (MC2), collaborated with researchers from UMD, Symantec Research Labs, and IBM Research to develop a new, faster method of detecting malware.
The team used known data to reconstruct and analyze 19 million downloader graphs from five million real hosts. Using this data, the researchers were able to identify several strong indicators of malware activity. They were then able to implement and evaluate a machine learning system for malware detection.
As a result, the researchers say, the system is able to detect malware—on average— approximately nine days earlier than existing anti-virus products.
To see a video overview of the cybersecurity work done by Dumitras, go here. Read more about the team's work here.
