Behaviour Based Malware Detection using Machine Learning

Abstract

Abstract: Considering all the researches done, it appears that over last decade, malware has been growing exponentially and also has been causing significant financial losses to different organizations. Thus, it becomes important to detect if a file contains any malware or not. The malwares can cause a lot of damage to the system such as slowing downthe system and also stealing sensitive information from the system. malware is a executable program specifically to destroy a genuine user's computer by spreading harmful virusin different ways .In the current times, one of the most important assets of the people is their data and information which needs to be protected. Hence, in order to protect the data and information, there is a need for software which couldperform this task and help in ensuring the integrity of our system. Our method for malware detection uses different machine learning algorithms such as decision tree, random forest etc. The algorithm which has the maximum accuracy gets selected which provides a great detection ratio for the system. Furthermore, the performance of the system is detected by calculating the false positive and false negative rates using the confusion matrix.