In the last decade, the number of computer malware has grown rapidly. Currently,
cybercriminals typically use malicious software (malware) as a means of attacking industrial …

The effectiveness of deep-learning-based malicious traffic detection systems relies on high-
quality labeled traffic datasets. However, malicious traffic labeling approaches can easily …

Cobalt Strike is the most prevalent attack tool abused by cyber-criminals to achieve
command and control on victim hosts over HTTPS traffics. It appears in many ransomware …

Internet traffic classification plays a key role in network visibility, Quality of Services (QoS),
intrusion detection, Quality of Experience (QoE) and traffic-trend analyses. In order to …

The accurate identification of internet traffic is crucial for network management. However, the
use of encryption techniques and constant changes in network protocols make it difficult to …

The development of the Internet of Things (IoT) has led to the rapid growth of the types and
number of connected devices and has generated large amounts of complex and diverse …

Current security solutions face significant challenges in dealing with the ever-increasing
complexity and sophistication of cyber-attacks. This is particularly true for the solutions that …

The ability to use a single camera for indoor navigation of a real mobile robot can help
develop a complete navigation system, eliminating the need to use a traditional navigation …

Due to the exponential increase of internet applications and network users, network traffic
classification (NTC) is a crucial study subject. It successfully improves network service …

Using deep learning models to deal with the classification tasks in network traffic offers a
new approach to address the imbalanced Internet of Things malicious traffic classification …