A Review : Cyber Forensic using Support Vector Machine

Abstract

Cyber forensic is an essential field of study that deals with the investigation and analysis of digital evidence. With the increasing use of digital devices, cyber forensic has become more important in detecting and preventing cybercrimes. Support Vector Machine (SVM) is a powerful machine learning algorithm that has been widely used in cyber forensic for identifying and classifying digital evidence. This review article provides an overview of the use of SVM in cyber forensic. It begins by introducing cyber forensic and its importance in modern-day investigations. It then explains the basics of SVM and its applications in cyber forensic. The article also discusses the advantages and limitations of SVM in cyber forensic. The review further examines the various approaches used in SVM-based cyber forensic, including feature selection, feature extraction, and classification. It also discusses the challenges faced by cyber forensic investigators when using SVM and provides recommendations for improving the accuracy of SVM-based cyber forensic. the importance of SVM in cyber forensic and its potential to improve the accuracy and efficiency of digital evidence analysis. It encourages further research to explore the full potential of SVM and other machine learning algorithms in cyber forensic.