Deep Learning for Ransomware Detection
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 difficult to detect them. There are different signatures or behaviors among different 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. In this paper, we will use deep learning method to detect Ransomwares. At first, we will introduce how we label the data with different behaviors and what features we choose. Afterwards, we will present our model for detecting various Ransomwares and prevent them from encrypting victim's data. Experimental evaluation demonstrates that our deep learning model can detect the latest Ransomwares in high speed network timely.