Foundations and applications of artificial Intelligence for zero-day and multi-step attack detection
Behind firewalls, more and more cybersecurity attacks are specifically targeted to the very
network where they are taking place. This review proposes a comprehensive framework for …
network where they are taking place. This review proposes a comprehensive framework for …
Deep learning techniques to detect cybersecurity attacks: a systematic mapping study
D Torre, F Mesadieu, A Chennamaneni - Empirical Software Engineering, 2023 - Springer
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 …
A machine learning approach for rdp-based lateral movement detection
T Bai, H Bian, A Abou Daya… - 2019 IEEE 44th …, 2019 - ieeexplore.ieee.org
Detecting cyber threats has been an on-going research endeavor. In this era, advanced
persistent threats (APTs) can incur significant cost for organizations and businesses. The …
persistent threats (APTs) can incur significant cost for organizations and businesses. The …
Rdp-based lateral movement detection using machine learning
Detecting cyber threats has been an on-going research endeavor. In this era, Advanced
Persistent Threats (APTs) can incur significant costs for organizations and businesses. The …
Persistent Threats (APTs) can incur significant costs for organizations and businesses. The …
Neural Network‐Based Voting System with High Capacity and Low Computation for Intrusion Detection in SIEM/IDS Systems
N Moukafih, G Orhanou… - Security and …, 2020 - Wiley Online Library
Integrating intelligence into intrusion detection tools has received much attention in the last
years. The goal is to improve the detection capability within SIEM and IDS systems in order …
years. The goal is to improve the detection capability within SIEM and IDS systems in order …
User behavior analysis for detecting compromised user Accounts: A review paper
The rise of online transactions has led to a corresponding increase in online criminal
activities. Account takeover attacks, in particular, are challenging to detect, and novel …
activities. Account takeover attacks, in particular, are challenging to detect, and novel …
Intrusion detection system based on hybrid classifier and user profile enhancement techniques
This paper presents a user intrusion detection system based on hybrid classifier and profile
enhancement techniques. The proposed approach is an anomaly-based intrusion detection …
enhancement techniques. The proposed approach is an anomaly-based intrusion detection …
[PDF][PDF] Decision tree for multiclass classification of firewall access
HNK AL-Behadili - … Journal of Intelligent Engineering and Systems, 2021 - researchgate.net
Internet usage is increasing rapidly worldwide, allowing numerous connected computer
objects or devices to run and communicate with mass digital information. As Internet usage …
objects or devices to run and communicate with mass digital information. As Internet usage …
[HTML][HTML] WebTraceSense—A Framework for the Visualization of User Log Interactions
The current surge in the deployment of web applications underscores the need to consider
users' individual preferences in order to enhance their experience. In response to this, an …
users' individual preferences in order to enhance their experience. In response to this, an …
Analysis of neural network training and cost functions impact on the accuracy of IDS and SIEM systems
S El Hajji, N Moukafih, G Orhanou - … , C2SI 2019, Rabat, Morocco, April 22 …, 2019 - Springer
Nowadays, companies are implementing security tools such as Intrusion Detection Systems
(IDS) and Security Information and Event Management systems (SIEM) to deal with …
(IDS) and Security Information and Event Management systems (SIEM) to deal with …