Botnets are a frequent threat to information systems on the Internet, capable of launching
denial-of-service attacks, spreading spam and malware on a large scale. Detecting and …

Advanced Persistent Threat (APT) attacks are a form of malicious, intentionally and clearly
targeted attack. By using many sophisticated and complicated methods and technologies to …

Correlation coefficient and regression analysis are the most applied statistical approaches
accessible in numerous disciplines due to its applicability and relevance. The neutrosophic …

Abstract Advanced Persistent Threat (APT) is a dangerous network attack method that is
widely used by attackers nowadays. During the APT attack process, attackers often use …

Neutrosophic logic is a very powerful and effective concept. It has different application areas
due to its ability to capture the stochasticity in many complex real-life use cases. This paper …

In this article, the gained and lost dominance score (GLDS) method is extended into the 2-
tuple linguistic neutrosophic environment, which also combined the power aggregation …

The DGA botnet prevention is a burning topic in cybersecurity, with two problems: detection
and classification. The DGA botnet dataset plays an essential role in the research allowing …

Abstract Intrusion Detection System (IDS) can reduce the losses caused by intrusion
behaviors and protect users' information security. The effectiveness of IDS depends on the …

Stochastic and neutrosophic theory are effective tools for modeling real-world phenomena
and natural dynamical systems, where inputs are often affected by stochastic noises and …

The existing detection methods of algorithmically generated malicious domain names lack
theoretical modelling methods for domain name element composition. To address this …