Mitigating Malware Attacks using Machine Learning: A Review
Mahesh Arse, Kanhaiya Sharma, Shantanu Bindewari, Ashwin Tomar, Harshal Patil, Neha Jha · 2023
In this digital era, lots of technology is available to reduce human effort through industrial automation. Industrial automation protects digital data from unauthorized access while reducing human effort. Securing digital data from unauthorized access, corruption, or theft is becoming increasingly difficult. Attackers easily find helpful information and use it for other malicious activities that could harm the legitimate user. Due to the wide range of options available to steal users’ essential data, most hackers use malware by writing malicious computer programs. To prevent these attacks, efficient machine learning (ML)-based algorithms are required to identify malicious code in the files used by hackers. The authors reviewed existing literature for preventing various malware attacks using a machine learning approach in this study.