Due to the monumental growth of Internet applications in the last decade, the need for
security of information network has increased manifolds. As a primary defense of network …

Anomaly detection in a network is one of the prime concerns for network security. In this
work, a novel Channel Boosted and Residual learning based deep Convolutional Neural …

Currently, expert systems and applied machine learning algorithms are widely used to
automate network intrusion detection. In critical infrastructure applications of communication …

Deep Learning has been very successful in many application domains. However, its
usefulness in the context of network intrusion detection has not been systematically …

Network Intrusion detection is a rapidly growing field of information security due to its
importance for modern IT infrastructure. Many supervised and unsupervised learning …

The prevalence of internet usage leads to diverse internet traffic, which may contain
information about various types of internet attacks. In recent years, many researchers have …

Network anomaly detection systems (NADSs) play a significant role in every network
defense system as they detect and prevent malicious activities. Therefore, this paper offers …

Abstract Internet-of-Things (IoT) connects various physical objects through the Internet and it
has a wide application, such as in transportation, military, healthcare, agriculture, and many …

The growing development of IoT (Internet of Things) devices creates a large attack surface
for cybercriminals to conduct potentially more destructive cyberattacks; as a result, the …

Network anomaly detection plays a crucial role as it provides an effective mechanism to
block or stop cyberattacks. With the recent advancement of Artificial Intelligence (AI), there …