Machine Learning Techniques for Malware Detection with Challenges and Future Directions

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Mohammed A Alqhatani


In the recent times Cybersecurity is the hot research topic because of its sensitivity. Especially at the times of digital world where everything is now transformed into digital medium. All the critical transactions are being carried out online with internet applications. Malware is an important issue which has the capability of stealing the privacy and funds from an ordinary person who is doing sensitive transactions through his mobile device. Researchers in the current time are striving to develop efficient techniques to detect these kinds of attacks. Not only individuals are getting offended even the governments are getting effected by these kinds of attacks and losing big amount of funds. In this work various Artificial intelligent and machine learning techniques are discussed which were implements for the detection of malware. Traditional machine learning techniques like Decision tree, K-Nearest Neighbor and Support vector machine and further to advanced machine learning techniques like Artificial neural network and convolution neural network are discussed. Among the discussed techniques, the work got the highest accuracy is 99% followed by 98.422%, 97.3% and 96% where the authors have implemented package-level API calls as feature, followed by advanced classification technique. Also, dataset details are discussed and listed which were used for the experimentation of malware detection, among the many dataset DREBIN had the most significant number of samples with 123453 Benign samples and 5560 Malware samples. Finally, open challenges are listed, and the future directions are highlighted which would encourage a new researcher to adopt this field of research and solve these open challenges with the help of future direction details provided in this paper. The paper is concluded with the limitation and conclusion section

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How to Cite
Alqhatani, M. A. (2022). Machine Learning Techniques for Malware Detection with Challenges and Future Directions. International Journal of Communication Networks and Information Security (IJCNIS), 13(2). (Original work published August 26, 2021)
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Author Biography

Mohammed A Alqhatani, Imam Abdulrahman Bin Faisal University

Mohammed A. Alqahtani he was a Teaching Assistant with the Imam Abdulrahman Bin Faisal University , Dammam, Kingdom of Saudi Arabia from 2004 to 2009. In the same university he worked as a Cisco instructor from 2005 to 2009, As a lecturer from 2009 to 2015, As an assistant professor since 2016. Currently he is the Chairman of the Computer Information System department at the same university. Recently he was assigned as Vice Dean of Communications and Information Technology as well. His research interest includes the Software Engineering, Programming, Mobile Transactions, Usability and Data Analysis.[Imam Abdulrahman Bin Faisal University]<>