Traffic classification is the first step in network anomaly detection and is essential to network
security. However, existing malicious traffic classification methods have several limitations; …

In the contemporary landscape, Distributed Denial of Service (DDoS) attacks have emerged
as an exceedingly pernicious threat, particularly in the context of network management …

Distributed Denial of Service (DDoS) and Address Resolution Protocol (ARP) attacks pose
significant threats to the security of Software-Defined Internet of Things (SD-IoT) networks …

Abstract Application-layer Distributed Denial of Service (App-DDoS) attacks continue to be a
pervasive problem in cybersecurity, despite the availability of various defensive frameworks …

The primary objective in building predictive analytics models is to achieve optimal accuracy
with real datasets. The limitations of existing models lie in their storage capacity, which …

The internet, a cornerstone of modern life, has profound implications across personal,
business, and society. However, its widespread use has posed challenges, especially …

Effective identification and categorization of network attacks are paramount for ensuring
robust security. However, contemporary techniques often struggle to accurately discern and …

Since its inception, the Internet has been rapidly evolving. With the advancement of science
and technology and the explosive growth of the population, the demand for the Internet has …

This paper presents the functional subspace variational autoencoder, a technique
addressing challenges in sensor data analysis in transportation systems, notably the …

Abstract Application-layer Distributed Denial of Service (App-DDoS) attacks continue to be a
pervasive problem in cybersecurity, despite the availability of various defensive frameworks …