Intrusion detection systems (IDS) play a critical role in safeguarding computer networks
against unauthorized access and malicious activities. However, traditional IDS approaches …

This paper provides a comprehensive survey of the state-of-the-art use of Artificial
Intelligence (AI) and Machine Learning (ML) in the field of cybersecurity. The paper …

Anomaly detection plays an essential role in network security and traffic classification. Many
studies have focused on anomaly detection to improve network security, including machine …

Various machine learning algorithms have been applied to network intrusion classification
problems, including both binary and multi-class classifications. Despite the existence of …

Real-time deep learning faces the challenge of balancing accuracy and time, especially in
cybersecurity where intrusion detection is crucial. Traditional deep learning techniques have …

Network forensics aids in the identification of distinct network-based attacks through packet-
level analysis of collected network traffic. It also unveils the attacker's intentions and …

In the wake of the expanding digital realm, the imperative for robust cybersecurity measures
has burgeoned significantly. This extensive investigation digs into the complicated realm of …

The growing reliance on cloud services necessitates a heightened focus on security
measures to protect the integrity and privacy of crucial business data. Privacy preservation …

In the rapidly evolving landscape of computing and networking, the concepts of cloud
networks have gained significant prominence. Although the cloud network offers on-demand …

In computer network security, the escalating use of computer networks and the
corresponding increase in cyberattacks have propelled Intrusion Detection Systems (IDSs) …