Deep learning techniques to detect cybersecurity attacks: a systematic map** study
Context Recent years have seen a lot of attention into Deep Learning (DL) techniques used
to detect cybersecurity attacks. DL techniques can swiftly analyze massive datasets, and …
to detect cybersecurity attacks. DL techniques can swiftly analyze massive datasets, and …
Modeling and executing cyber security exercise scenarios in cyber ranges
MM Yamin, B Katt - Computers & Security, 2022 - Elsevier
The skill shortage in global cybersecurity is a well-known problem; to overcome this issue,
cyber ranges have been developed. These ranges provide a platform for conducting …
cyber ranges have been developed. These ranges provide a platform for conducting …
Use of cyber attack and defense agents in cyber ranges: A case study
MM Yamin, B Katt - Computers & Security, 2022 - Elsevier
With the ever-changing cybersecurity landscape, the need for a continuous training for new
cybersecurity skill sets is a requirement. Such continuous training programs can be …
cybersecurity skill sets is a requirement. Such continuous training programs can be …
Living-off-the-land command detection using active learning
In recent years, enterprises have been targeted by advanced adversaries who leverage
creative ways to infiltrate their systems and move laterally to gain access to critical data. One …
creative ways to infiltrate their systems and move laterally to gain access to critical data. One …
Analysis and correlation of visual evidence in campaigns of malicious office documents
F Casino, N Totosis, T Apostolopoulos… - … Threats: Research and …, 2023 - dl.acm.org
Many malware campaigns use Microsoft (MS) Office documents as droppers to download
and execute their malicious payload. Such campaigns often use these documents because …
and execute their malicious payload. Such campaigns often use these documents because …
Command-line Risk Classification using Transformer-based Neural Architectures
To protect large-scale computing environments necessary to meet increasing computing
demand, cloud providers have implemented security measures to monitor Operations and …
demand, cloud providers have implemented security measures to monitor Operations and …
Resilient Machine Learning Methods for Cyber-Attack Detection
T Ongun - 2023 - search.proquest.com
The cyber threat landscape has evolved tremendously in recent years, with new threat
variants emerging daily, and large-scale coordinated campaigns becoming more prevalent …
variants emerging daily, and large-scale coordinated campaigns becoming more prevalent …
LOLBin detection through unsupervised learning: An approach based on explicit featurization of the command line and parent-child relationships
U Nisslmueller - 2022 - essay.utwente.nl
Over the last couple of years, LOLBins have become a staple in the arsenal of APTs and
other organized threat actors. Compared to the usual modus operandi of performing one or …
other organized threat actors. Compared to the usual modus operandi of performing one or …
Head based tracking
For tracking multiple targets in a scene, the most common approach is to represent the target
in a bounding box and track the whole box as a single entity. However, in the case of …
in a bounding box and track the whole box as a single entity. However, in the case of …
Modelling and analyzing attack-defense scenarios for cyber-ranges
MM Yamin - 2022 - ntnuopen.ntnu.no
Rome was not built in a day, but it was burnt to the ground in only six. Wood naturally
catches fire, and without adequate engineering, fireproof houses and training for firefighters …
catches fire, and without adequate engineering, fireproof houses and training for firefighters …