Modern networks are crucial for seamless connectivity but face various threats, including
disruptive network attacks, which can result in significant financial and reputational risks. To …

Network attacks refer to malicious activities exploiting computer network vulnerabilities to
compromise security, disrupt operations, or gain unauthorized access to sensitive …

Abstract Machine Learning (ML) techniques are increasingly adopted to tackle ever-evolving
high-profile network attacks, including Distributed Denial of Service (DDoS), botnet, and …

Emerging and evolving cybersecurity threats pose significant risks to the private data and
assets of government, businesses, and individuals. The timely detection of unknown network …

Multi-stage network attack (MSA) is a serious threat to data security. The high-dimensionality
of the alert data along with the diverse features, leads to poor detection performance for …

The digitization of different components of industry and inter-connectivity among indigenous
networks have increased the risk of network attacks. Designing an intrusion detection …

Recently, machine learning techniques are gaining a lot of interest in security applications
as they exhibit fast processing with real-time predictions. One of the significant challenges in …

Precise real-time prediction of the number of future network attacks cannot only prompt
cloud infrastructures to fast respond to them and protect network security, but also prevents …

Featured Application This work has potential usages in cyber-attack detection in air-gapped
internal networks that lack sufficient labeled data samples to build detection models for …

Network attacks have been around since the beginning of the Internet and they are still
relevant due to the numerous attempts of independent hackers, cybercrime organizations …