This survey paper describes a literature review of deep learning (DL) methods for cyber
security applications. A short tutorial-style description of each DL method is provided …

Deep learning has become a predominant method for solving data analysis problems in
virtually all fields of science and engineering. The increasing complexity and the large …

The system log generated in a computer system refers to large-scale data that are collected
simultaneously and used as the basic data for determining errors, intrusion and abnormal …

The KDD CUP 1999 intrusion detection dataset was introduced at the third international
knowledge discovery and data mining tools competition, and it has been widely used for …

Cybersecurity is a very emerging field that protects systems, networks, and data from digital
attacks. With the increase in the scale of the Internet and the evolution of cyber attacks …

Recently, the development of blockchain technology has given us an opportunity to improve
the security and trustworthiness of multimedia. With the applications of blockchain …

Since SVM is sensitive to noises and outliers of system call sequence data. A new fuzzy
support vector machine algorithm based on SVDD is presented in this paper. In our …

Abstract Research into Intrusion and Anomaly Detectors at the Host level typically pays
much attention to extracting attributes from system call traces. These include window-based …

Nowadays web applications influence people deeply and become popular targets of
attackers. The payload anomaly detection is an effective method to keep the security of web …

The rise of malware attacks presents a significant cyber-security challenge, with advanced
techniques and offline command-and-control (C2) servers causing disruptions and financial …