Drastic advancement in computing technology and the dramatic increase in the usage of
explainable machine learning algorithms provide a promising platform for developing robust …

Momentous increase in the popularity of explainable machine learning models coupled with
the dramatic increase in the use of synthetic data facilitates us to develop a cost-efficient …

The dramatic increase in the computational facilities integrated with the explainable
machine learning algorithms allows us to do fast intrusion detection and prevention at …

Abstract Intrusion Detection Systems (IDS) play a pivotal role in safeguarding computer
networks from unauthorized access and malicious activities. With the increasing complexity …

In recent years, machine learning-based intrusion detection systems (IDSs) have proven to
be effective; especially, deep neural networks improve the detection rates of intrusion …

In today's digital world, the tremendous amount of data poses a significant challenge to
cyber security. The complexity of cyber-attacks makes it difficult to develop efficient tools to …

Recently proposed methods in intrusion detection are iterating on machine learning
methods as a potential solution. These novel methods are validated on one or more …

Ensuring fast and efficient Intrusion Detection and Prevention (IDP) at international borders
is crucial for maintaining security and safeguarding nations. In this study, we propose an …

Although the field of eXplainable Artificial Intelligence (XAI) has a significant interest these
days, its implementation within cyber security applications still needs further investigation to …

Abstract Machine Learning (ML)-based network intrusion detection systems bring many
benefits for enhancing the cybersecurity posture of an organisation. Many systems have …