[HTML][HTML] A systematic literature review of methods and datasets for anomaly-based network intrusion detection

Z Yang, X Liu, T Li, D Wu, J Wang, Y Zhao, H Han - Computers & Security, 2022‏ - Elsevier
As network techniques rapidly evolve, attacks are becoming increasingly sophisticated and
threatening. Network intrusion detection has been widely accepted as an effective method to …

[PDF][PDF] The significance of machine learning and deep learning techniques in cybersecurity: A comprehensive review

MM Mijwil, IE Salem, MM Ismaeel - Iraqi Journal For Computer Science and …, 2023‏ - iasj.net
People in the modern era spend most of their lives in virtual environments that offer a range
of public and private services and social platforms. Therefore, these environments need to …

Ai-driven cybersecurity: an overview, security intelligence modeling and research directions

IH Sarker, MH Furhad, R Nowrozy - SN Computer Science, 2021‏ - Springer
Artificial intelligence (AI) is one of the key technologies of the Fourth Industrial Revolution (or
Industry 4.0), which can be used for the protection of Internet-connected systems from cyber …

Cybersecurity data science: an overview from machine learning perspective

IH Sarker, ASM Kayes, S Badsha, H Alqahtani… - Journal of Big …, 2020‏ - Springer
In a computing context, cybersecurity is undergoing massive shifts in technology and its
operations in recent days, and data science is driving the change. Extracting security …

A survey on intrusion detection system: feature selection, model, performance measures, application perspective, challenges, and future research directions

A Thakkar, R Lohiya - Artificial Intelligence Review, 2022‏ - Springer
With the increase in the usage of the Internet, a large amount of information is exchanged
between different communicating devices. The data should be communicated securely …

Intrusion detection system using machine learning for vehicular ad hoc networks based on ToN-IoT dataset

AR Gad, AA Nashat, TM Barkat - IEEE Access, 2021‏ - ieeexplore.ieee.org
Vehicular ad hoc networks (VANETs) are a subsystem of the proposed intelligent
transportation system (ITS) that enables vehicles to communicate over the wireless …

Deep learning approach for intelligent intrusion detection system

R Vinayakumar, M Alazab, KP Soman… - Ieee …, 2019‏ - ieeexplore.ieee.org
Machine learning techniques are being widely used to develop an intrusion detection
system (IDS) for detecting and classifying cyberattacks at the network-level and the host …

Future intelligent and secure vehicular network toward 6G: Machine-learning approaches

F Tang, Y Kawamoto, N Kato, J Liu - Proceedings of the IEEE, 2019‏ - ieeexplore.ieee.org
As a powerful tool, the vehicular network has been built to connect human communication
and transportation around the world for many years to come. However, with the rapid growth …

A survey of network-based intrusion detection data sets

M Ring, S Wunderlich, D Scheuring, D Landes… - Computers & …, 2019‏ - Elsevier
Labeled data sets are necessary to train and evaluate anomaly-based network intrusion
detection systems. This work provides a focused literature survey of data sets for network …

Selection of effective machine learning algorithm and Bot-IoT attacks traffic identification for internet of things in smart city

M Shafiq, Z Tian, Y Sun, X Du, M Guizani - Future Generation Computer …, 2020‏ - Elsevier
Identifying cyber attacks traffic is very important for the Internet of things (IoT) security in
smart city. Recently, the research community in the field of IoT Security endeavor hard to …