Automated Secure Computing for Next-Generation Systems

6An Automatic Artificial Intelligence System for Malware Detection

Ahmad Moawad¹*, Ahmed Ismail Ebada², A.A. El-Harby¹ and Aya M. Al-Zoghby¹

¹Department of Computer Science, Faculty of Computers and Artificial Intelligence, Damietta, Egypt

²Department of Information Systems, Faculty of Computers and Artificial Intelligence, Damietta, Egypt

Abstract

One of the major issues in computer system security is detecting malware threats before they spread. The continuous development of malware makes it challenging to detect malware with traditional anti-malware software, which relies on the signature database. As new malware samples increase daily, standard malware detection tools become less effective; thus, the AI method is required to detect and prevent malware spread. Machine learning and deep learning methods have promising results and can handle malware by identifying patterns in malware samples and detecting similar malware. The analysis process is essential for identifying the malware and its outcome with patterns or features that are used in the detection process. Malware analyses are static, dynamic, hybrid, and memory-based; all of them have pros and cons. Applying the outcome from the analysis process by employing machine learning and deep learning provides good and accurate results, is quick, is less costly, is independent from the reverse engineers, and offers promising detection solutions to safeguard individuals and governments. This chapter covers the following: malware ...