Machine learning in cybersecurity: a comprehensive survey

D Dasgupta, Z Akhtar, S Sen - The Journal of Defense …, 2022 - journals.sagepub.com
Today's world is highly network interconnected owing to the pervasiveness of small personal
devices (eg, smartphones) as well as large computing devices or services (eg, cloud …

Online diagnosis of performance variation in HPC systems using machine learning

O Tuncer, E Ates, Y Zhang, A Turk… - … on Parallel and …, 2018 - ieeexplore.ieee.org
As the size and complexity of high performance computing (HPC) systems grow in line with
advancements in hardware and software technology, HPC systems increasingly suffer from …

A FKPCA-GWO WDBiLSTM classifier for intrusion detection system in cloud environments

TV Geetha, AJ Deepa - Knowledge-Based Systems, 2022 - Elsevier
Due to the expansion of Internet traffic and threats in the cloud environment, intrusion
detection is becoming more challenging. Attackers may try to exploit various application …

Attacks and intrusion detection in cloud computing using neural networks and particle swarm optimization algorithms

AS Saljoughi, M Mehrvarz, H Mirvaziri - Emerging Science Journal, 2017 - ijournalse.org
Today, cloud computing has become popular among users in organizations and companies.
Security and efficiency are the two major issues facing cloud service providers and their …

Prodigy: Towards unsupervised anomaly detection in production hpc systems

B Aksar, E Sencan, B Schwaller, O Aaziz… - Proceedings of the …, 2023 - dl.acm.org
Performance variations caused by anomalies in modern High Performance Computing
(HPC) systems lead to decreased efficiency, impaired application performance, and …

[HTML][HTML] Unsupervised packet-based anomaly detection in virtual networks

D Spiekermann, J Keller - Computer Networks, 2021 - Elsevier
The enormous number of network packets transferred in modern networks together with the
high speed of transmissions hamper the implementation of successful IT security …

Albadross: Active learning based anomaly diagnosis for production hpc systems

B Aksar, E Sencan, B Schwaller, O Aaziz… - 2022 IEEE …, 2022 - ieeexplore.ieee.org
Diagnosing causes of performance variations in High-Performance Computing (HPC)
systems is a daunting chal-lenge due to the systems' scale and complexity. Variations in …

E2EWatch: an end-to-end anomaly diagnosis framework for production HPC systems

B Aksar, B Schwaller, O Aaziz, VJ Leung… - Euro-Par 2021: Parallel …, 2021 - Springer
Abstract In today's High-Performance Computing (HPC) systems, application performance
variations are among the most vital challenges as they adversely affect system efficiency …

A real-time machine learning application for browser extension security monitoring

TP Fowdur, S Hosenally - Information Security Journal: A Global …, 2024 - Taylor & Francis
One of the most common attacks in browser extensions is Cross-site scripting (XSS). To
address these challenges, several browsers have proposed a new mechanism where …

A data-driven preprocessing scheme on anomaly detection in big data applications

S Xu, Y Qian, RQ Hu - 2017 IEEE Conference on Computer …, 2017 - ieeexplore.ieee.org
Efficient anomaly detection mechanisms are becoming an urgent and critical topic in the
presence of big data applications. In this paper, we propose a data-driven preprocessing …