Review of intrusion detection systems based on deep learning techniques: coherent taxonomy, challenges, motivations, recommendations, substantial analysis and …
This study reviews and analyses the research landscape for intrusion detection systems
(IDSs) based on deep learning (DL) techniques into a coherent taxonomy and identifies the …
(IDSs) based on deep learning (DL) techniques into a coherent taxonomy and identifies the …
Deep learning approaches for anomaly-based intrusion detection systems: A survey, taxonomy, and open issues
A Aldweesh, A Derhab, AZ Emam - Knowledge-Based Systems, 2020 - Elsevier
The massive growth of data that are transmitted through a variety of devices and
communication protocols have raised serious security concerns, which have increased the …
communication protocols have raised serious security concerns, which have increased the …
Machine learning and deep learning methods for intrusion detection systems: recent developments and challenges
G Kocher, G Kumar - Soft Computing, 2021 - Springer
Deep learning (DL) is gaining significant prevalence in every field of study due to its
domination in training large data sets. However, several applications are utilizing machine …
domination in training large data sets. However, several applications are utilizing machine …
Deep learning-based intrusion detection systems: a systematic review
Nowadays, the ever-increasing complication and severity of security attacks on computer
networks have inspired security researchers to incorporate different machine learning …
networks have inspired security researchers to incorporate different machine learning …
A comprehensive survey of databases and deep learning methods for cybersecurity and intrusion detection systems
This survey presents a comprehensive overview of machine learning methods for
cybersecurity intrusion detection systems, with a specific focus on recent approaches based …
cybersecurity intrusion detection systems, with a specific focus on recent approaches based …
A systematic and comprehensive survey of recent advances in intrusion detection systems using machine learning: Deep learning, datasets, and attack taxonomy
Recently, intrusion detection systems (IDS) have become an essential part of most
organisations' security architecture due to the rise in frequency and severity of network …
organisations' security architecture due to the rise in frequency and severity of network …
Towards secure intrusion detection systems using deep learning techniques: Comprehensive analysis and review
Providing a high-performance Intrusion Detection System (IDS) can be very effective in
controlling malicious behaviors and cyber-attacks. Regarding the ever-growing negative …
controlling malicious behaviors and cyber-attacks. Regarding the ever-growing negative …
Comparative analysis of intrusion detection systems and machine learning based model analysis through decision tree
Cyber-attacks pose increasing challenges in precisely detecting intrusions, risking data
confidentiality, integrity, and availability. This review paper presents recent IDS taxonomy, a …
confidentiality, integrity, and availability. This review paper presents recent IDS taxonomy, a …
[图书][B] Network intrusion detection using deep learning: a feature learning approach
K Kim, ME Aminanto, HC Tanuwidjaja - 2018 - books.google.com
This book presents recent advances in intrusion detection systems (IDSs) using state-of-the-
art deep learning methods. It also provides a systematic overview of classical machine …
art deep learning methods. It also provides a systematic overview of classical machine …
A Survey of Deep Learning Technologies for Intrusion Detection in Internet of Things
The Internet of Things (IoT) is transforming how we live and work, and its applications are
widespread, spanning smart homes, industrial monitoring, smart cities, healthcare …
widespread, spanning smart homes, industrial monitoring, smart cities, healthcare …