Labeled data sets are necessary to train and evaluate anomaly-based network intrusion
detection systems. This work provides a focused literature survey of data sets for network …

Significant cybersecurity and threat intelligence analysts agree that online criminal activity is
increasing exponentially. To offer an overview of the techniques and indicators to perform …

Software-Defined Network (SDN) has been developed to reduce network complexity
through control and manage the whole network from a centralized location. Today, SDN is …

Flow-based data sets are necessary for evaluating network-based intrusion detection
systems (NIDS). In this work, we propose a novel methodology for generating realistic flow …

Network Intrusion Detection Systems (NIDS) play an important role as tools for identifying
potential network threats. In the context of ever-increasing traffic volume on computer …

Signature-based Network Intrusion Detection Systems (NIDS) have become state-of-the-art
in modern network security solutions. However, most systems are not designed for modern …

Port scanning attack is a common cyber-attack where an attacker directs packets with
diverse port numbers to scan accessible services aiming to discover open/weak ports in a …

Anomalous traffic detection is a vital task in advanced Internet supervision and maintenance.
To detect anomalies accurately, various data representations, such as vectors, matrices, and …

Fuzzy Rule Interpolation (FRI) offers a convenient way for delivering rule based decisions on
continuous universes avoiding the burden of binary decisions. In contrast with the classical …

We propose a framework for anomaly detection in communication network logs along with
automated extraction of human-readable annotations that explain the decision logic …