As our professional, social, and financial existences become increasingly digitized and as
our government, healthcare, and military infrastructures rely more on computer technologies …

Today, the Internet security community largely emphasizes cyberspace monitoring for the
purpose of generating cyber intelligence. In this paper, we present a survey on darknet. The …

The implementation of electronics in modern vehicles has resulted in an increase in attacks
targeting in-vehicle networks; thus, attack detection models have caught the attention of the …

As cyberattacks become more intelligent, it is challenging to detect advanced attacks in a
variety of fields including industry, national defense, and healthcare. Traditional intrusion …

The problem of network intrusion detection poses innumerable challenges to the research
community, industry, and commercial sectors. Moreover, the persistent attacks occurring on …

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

As the number of cyber attacks have increased, detecting the intrusion in networks become
a very tough job. For network intrusion detection system (NIDS), many data mining and …

In recent years, machine learning (ML) has become an important part to yield security and
privacy in various applications. ML is used to address serious issues such as real-time …

Security and privacy of a system is compromised, when an intrusion happens. Intrusion
Detection System (IDS) plays vital role in network security as it detects various types of …

Intrusion Detection Systems (IDS) are aimed at analyzing and detecting security problems.
IDS based on anomaly detection and, in particular, on statistical analysis, inspect each traffic …