Machine Learning Leveraged to Spot Ransomware 

Everyone seemingly is complaining about the spread of ransomware, and now somebody is trying to do something about it using machine learning-based behavioral analytics techniques to track suspicious behavior on company networks.

As the scale of the ransomware threat grows, including ransom payments by hospitals and universities and growing fears that it will soon spread to other sectors, a Silicon Valley security intelligence firm has rolled out an approach for detecting ransomware via machine learning.

Exabeam, a specialist in user and "entity" behavior analytics based in San Mateo, Calif., unveiled its analytics approach to detecting ransomware attacks during a security conference this week.

See the full story at sister publication Datanami.

About the author: George Leopold

George Leopold has written about science and technology for more than 30 years, focusing on electronics and aerospace technology. He previously served as executive editor of Electronic Engineering Times. Leopold is the author of "Calculated Risk: The Supersonic Life and Times of Gus Grissom" (Purdue University Press, 2016).