A Study of Malware Datasets and Techniques to Detect the Malware using Deep Learning Approach
V. S. Jeyalakshmi, J. Jayapriya, N. Krishnan · 2022 6th International Conference on Trends in Electronics and Informatics (ICOEI) · 2022
Cyber analytics play a vital role in solving the various domain problems in our day-to-day life. In this, Malware and web based attacks are most common types. Business organizations have their own apps to run their business. Malware captures the business information and corrupt the system. Malwares are developed based on financial gain. Security issues are now a big challenge with the ever increasing risk of malware attacks. Recently researchers are highly motivated to detect the malwares in the cyber field. Similarly some international highly trained programmer's community are also interested to detect the malwares for profit yielding purpose. The proposed study is based on the different malware datasets, deep learning techniques and its applications involved in malware analysis. The study infers the comprehensive comparison between different neural networks using Deep learning algorithm such as CNN, LSTM, RNN, GRU, GAN, Transfer learning, etc for Static malware analysis with different datasets.