Abstract:
The Growth of Technology used on the Internet, Computers, Smartphones, and Tablets have been favorable to the emergence and spread of cyber threats, resulting in cyber-at...Show MoreMetadata
Abstract:
The Growth of Technology used on the Internet, Computers, Smartphones, and Tablets have been favorable to the emergence and spread of cyber threats, resulting in cyber-attacks around the world. The number of attacks has grown exponentially and has resulted in discovering various malware detection approaches. Multiple big data technologies and machine learning models are being used for the detection of malware. Currently, Malware detection solutions that adopt traditional Machine Learning techniques take time but have been shown to be successful at detecting unknown malware in real time. The feature engineering process can be absolutely eliminated by employing advanced Machine Learning Algorithms such as Deep learning. Various Malware Classification and Identification methods are discussed in this paper. To identify the sample as benign or malware, machine learning and deep learning-based solutions have been addressed.
Published in: 2021 International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA)
Date of Conference: 08-09 October 2021
Date Added to IEEE Xplore: 18 January 2022
ISBN Information: