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 …

Anomaly detection is critical given the raft of cyber attacks in the wireless communications
these days. It is thus a challenging task to determine network anomaly more accurately. In …

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

Anomaly detection in network traffic is one of the key techniques to ensure security in future
networks. Today, the importance of this topic is even higher, since the network traffic is …

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 …

Network traffic anomaly detection is an important technique of ensuring network security.
However, there are usually three problems with existing machine learning based anomaly …

In this paper, we propose an optimization approach by leveraging swarm intelligence and
ensemble methods to solve the non-deterministic feature selection problem. The proposed …

Convolutional neural networks (CNNs) are the specific architecture of feed‐forward artificial
neural networks. It is the de‐facto standard for various operations in machine learning and …

Abstract The Internet of Things (IoT) is a key enabler in closing the loop in Cyber-Physical
Systems, providing “smartness” and thus additional value to each monitored/controlled …

Security issues of large-scale local area network are becoming more prominent and the
anomaly detection for the network traffic is the key means to solve this problem. On the other …