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An investigation into an attack against a cloud computing server reveals an unusual and innovative way for malware to communicate through Amazon’s firewalls
The botnet known as MyKings wields a wide range of automated methods to break into servers – all just to install cryptocurrency miners.
What defenders should know about the most prevalent and persistent malware families.
Challenges the world faces for the coming year, securing data, devices, and people in an increasingly complex environment.
On May 12th, 2017, organizations across the world were attacked by a new, fast-spreading piece of malware we now know as WannaCry. It is now considered one of the most widespread, and notoriously destructive malware attacks in history, halted only by a researcher getting a lucky break, registering a domain name embedded in the malware that unexpectedly acted as a kill switch. But even today, more than two years hence, WannaCry continues to affect thousands of computers worldwide.
Cybersecurity threats have been growing significantly in both volume and sophistication over the past decade. This poses great challenges to malware detection without considerable automation. In this paper, we have proposed a novel approach by extending our recently suggested artificial neural network (ANN)- based model with feature selection using the principal component analysis (PCA) technique for malware detection.