Ransomware detection using machine learning

Ransomware is a kind of malware that installs covertly on a victim's computer
or smartphone, executes a cryptovirology attack and demands a ransom
payment to restore it. Ransomwares have been the most serious threat
in 2016, and this situation continues to worsen. Because of high reward for
Ransomwares, more and more Ransomware families appear, and it makes
us more dicult to detect them. There are dierent signatures or behaviors
among dierent families (i.e. Locky, Cerber, Cryptowall to name a few)
or versions (i.e. CryptXXX2.0, CryptXXX3.0) of Ransomwares. It will be
wonderful if there is a way that can detect potential Ransomware threats.
This paper is based on machine learning technique to detect Ransomwares.
The rst part introduces how to label the data with dierent behaviors and
what features that have chosen. Afterward, present the model for detecting
various Ransomware and prevent them from encrypting victim's data.
Experimental evaluation demonstrates that this model can detect the latest
Ransomware.

MSC CS 2017-2019 INT Md. Meraj Uddin