While machine learning and artificial intelligence have long been applied in networking
research, the bulk of such works has focused on supervised learning. Recently, there has …

Scanning of ports on a computer occurs frequently on the Internet. An attacker performs port
scans of Internet protocol addresses to find vulnerable hosts to compromise. However, it is …

For the last decade it has become commonplace to evaluate machine learning techniques
for network based intrusion detection on the KDD Cup'99 data set. This data set has served …

Adversarial reconnaissance is a crucial step in sophisticated cyber-attacks as it enables
threat actors to find the weakest points of otherwise well-defended systems. To thwart …

Bayesian networks are very powerful tools for knowledge representation and reasoning
under uncertainty. This paper shows the applicability of naive Bayesian classifiers to two …

Cloud computing provides a paradigm to enable convenient and on-demand network
access to a shared pool of configurable computing resources. The security challenges …

Due to increasing amount of cyber attack, there is a growing demand for Network intrusion
detection systems (NIDSs) which are necessary for defending from potential attacks. Cyber …

The objective of this chapter is to provide a general overview of Network Scanning Activities
(NSAs). It describes who are their performers and targets, distinguishes them between …

Культурно-историческое наследие России нуждается в комплексной поддержке со
стороны государства и бизнеса. Множество значительных архитектурных комплексов …

Directed acyclic graph (DAG) is a popular representation of an application, which includes
application characteristics such as task dependencies, task execution time and inter …