A key notion in numerous data mining and machine learning (ML) algorithms says that the
training data and testing data are essentially in the similar feature space and also have the …

In recent decades, the internet has grown and changed the world tremendously, and this, in
turn, has brought about many cyberattacks. Cybersecurity represents one of the most …

Cloud computing is perhaps the most enticing innovation in the present figuring situation. It
gives an expense-effective arrangement by diminishing the enormous forthright expense of …

Monitoring network traffic and trying to detect malicious activities are two of the high
significance tasks carried out by Computer Security Incident Response Teams (CSIRTs) …

Botnet detection is a critical step in stopping the spread of botnets and preventing malicious
activities. However, reliable detection is still a challenging task, due to a wide variety of …

Machine Learning (ML) methods have been widely used in Intrusion Detection Systems
(IDS). In particular, many botnet detection methods are based on ML. However, due to the …

The proliferation of Botnet attacks on IoT devices indicates that IoT network traffics is more
vulnerable than other IT-based device network traffic. Mitigating this threat has led to new …

Due to the low recognition accuracy and slow convergence speed of the traditional
basketball shooting trajectory recognition methods, this paper proposes a basketball …

Abstract The use of Transfer Learning algorithms for enhancing the performance of machine
learning algorithms has gained attention over the last decade. In this paper we introduce an …

Cybercrime costs large amounts of money and resources every year. This is because it is
usually carried out using different methods and at different scales. The use of botnets is one …