Cybersecurity has recently gained considerable interest in today's security issues because
of the popularity of the Internet-of-Things (IoT), the considerable growth of mobile networks …

Due to the popularity of Internet of Things devices, the exponential progress of computer
networks, and a plethora of associated applications, cybersecurity has recently attracted …

Anomaly-based detection is a novel form of an intrusion detection system, which has
become the focus of many researchers for cybersecurity systems. Data manages most …

In recent years, advanced threat and zero day attacks are increasing significantly, but the
traditional network intrusion detection system based on feature filtering or based on a well …

Intrusion detection systems (IDS) play a vital role in protecting information systems from
intruders. Anomaly-based IDS has established its effectiveness in identifying new and …

As machine learning and cybersecurity continue to explode in the context of the digital
ecosystem, the complexity of cybersecurity data combined with complicated and evasive …

Anomaly detection from Big Cybersecurity Datasets is very important; however, this is a very
challenging and computationally expensive task. Feature selection (FS) is an approach to …

Ubiquitous system returns to making pervasive computing in daily lives, the objects of smart
environment becomes intelligent and interconnect without anyone being conscious of the …

Intrusion detection system (IDS) acts as an essential part to detect malicious activity in the
cyber domain. Earlier works on IDS are mainly based on statistical, machine learning (ML) …

In the era of big data, outlier detection has become an important task for many applications,
such as the network intrusion detection system. Data streams are a unique type of big data …