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 …

The increase of connected devices and the constantly evolving methods and techniques by
attackers pose a challenge for network intrusion detection systems from conception to …

Sound, robust methods identify the most suitable, parsimonious set of tests to use with
respect to prioritized, sequential anomaly detection in a collected batch of sample data …

Malware researchers rely on the observation of malicious code in execution to collect
datasets for a wide array of experiments, including generation of detection models, study of …

Botnets represent one of the most aggressive threats against cyber security. Different
techniques using different feature sets have been proposed for botnet traffic analysis and …

This paper presents a framework for evaluating the transport layer feature space of malware
heartbeat traffic. We utilize these features in a prototype detection system to distinguish …

Researchers working on anomaly-based network intrusion detection immediately face a first,
somewhat surprising problem: The lack of good, recent datasets that could be employed for …

As the current cyber threat landscape is becoming more depressing, sophisticated intrusion
detection systems must evolve to protect network infrastructures efficiently. Building such a …

Botnets represent one of the most significant threats against cyber security. They employ
different techniques, topologies and communication protocols in different stages of their …

Botnets represent a destructive cyber security threat that aim to hide their malicious activities
within legitimate Internet traffic. Part of what makes botnets so affective is that they often …