Machine learning (ML) and deep learning (DL) have both produced overwhelming interest
and drawn unparalleled community interest recently. With a growing convergence of online …

Due to the continuous digitalization of our society, distributed and web-based applications
become omnipresent and making them more secure gains paramount relevance. Deep …

Three technical problems should be solved urgently in cyberspace security: the timeliness
and accuracy of network attack detection, the credibility assessment and prediction of the …

Machine learning (ML) and deep learning (DL) both drawn unparalleled community interest
recently. With a growing convergence of online activities and digital life, the way people …

IoT malware analysis is crucial for understanding the behavior and purpose of malware
samples. While deep learning methods have been applied to IoT malware analysis using …

Network intrusion detection systems (NIDSs) are one of the main tools used to defend
against cyber-attacks. Deep learning has shown remarkable success in network intrusion …

Reverse engineering of a stripped binary has a wide range of applications, yet it is
challenging mainly due to the lack of contextually useful information within. Once debugging …

A wide range of binary analysis applications, such as bug discovery, malware analysis and
code clone detection, require recovery of contextual meanings on a binary code. Recently …

Artificial Intelligence occupies a major part in the end-to-end technology we use every day.
In order to ensure and enhance security, Artificial Intelligence techniques are used in cyber …

The largest number of cybersecurity attacks is on web applications, in which Cross-Site
Scripting (XSS) is the most popular way. The code audit is the main method to avoid the …