An intrusion detection system (IDS) is an important protection instrument for detecting
complex network attacks. Various machine learning (ML) or deep learning (DL) algorithms …

Attacks on networks are currently the most pressing issue confronting modern society.
Network risks affect all networks, from small to large. An intrusion detection system must be …

Handling redundant and irrelevant features in high-dimension datasets has caused a long-
term challenge for network anomaly detection. Eliminating such features with spectral …

The connectivity of devices through the internet plays a remarkable role in our daily lives.
Many network-based applications are utilized in different domains, eg, health care, smart …

This research paper presents MLDroid—a web-based framework—which helps to detect
malware from Android devices. Due to increase in the popularity of Android devices …

Intrusion detection system (IDS) provides an important basis for the network defense. Due to
the development of the cloud computing and social network, massive amounts of data are …

Abstract The Internet of Things (IoT) has evolved in the last few years to become one of the
hottest topics in the area of computer science research. This drastic increase in IoT …

The prosperity of technology worldwide has made the concerns of security tend to increase
rapidly. The enormous usage of Internetworking has raised the need of protecting systems …

A lot of research is being done on the development of effective Network Intrusion Detection
Systems. Anomaly based Network Intrusion Detection Systems are preferred over Signature …

A common problem shared by current IDS is the high false positives and low detection rate.
An unsupervised machine learning using k-means was used to propose a model for …