Multi Classifier models using machine learning algorithms techniques for Malware Detection Assignment, Ireland

Malware is a program that has been purposefully developed to engage in a variety of malicious behaviors, ranging from data theft to cyber espionage. Malware or malicious software is used by cybercriminals with the intention of causing financial or reputational damage. They could be used to infiltrate systems and gain access to confidential information.

Nowadays they are becoming more common and harder to identify. This research uses machine learning algorithms for the detection and classification of the most common malware.  This report will try to focus on the machine learning methods which will detect malware functioning in any computer or software.

Different machine learning technologies have been extremely successful in the detection of malware functioning. Machine learning is a data analytics process that monitors visualization and other advanced processes in the targeted computer to acquire and integrate large-scale knowledge into the system automatically.

It depends on several models which work based on algorithms mainly used for machine learning. Some of the well-known machine learning techniques used by data analysts and scientists are regression, clustering, an ensemble of methods, neural nets and deep learning, dimensionality reduction, and classification. The four types of algorithms used in machine learning are unsupervised, supervised, reinforcement, and semi-supervised.

The report will highlight the main points in the form of a literature review which will point out current research that has been conducted on malware detection through machine learning methodologies.