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 …

Comprehensive review of cybercrime detection techniques

WA Al-Khater, S Al-Maadeed, AA Ahmed… - IEEE …, 2020 - ieeexplore.ieee.org
Cybercrimes are cases of indictable offences and misdemeanors that involve computers or
communication tools as targets and commission instruments or are associated with the …

Securing the smart grid: A comprehensive compilation of intrusion detection and prevention systems

PI Radoglou-Grammatikis, PG Sarigiannidis - Ieee Access, 2019 - ieeexplore.ieee.org
The smart grid (SG) paradigm is the next technological leap of the conventional electrical
grid, contributing to the protection of the physical environment and providing multiple …

Sequential model based intrusion detection system for IoT servers using deep learning methods

M Zhong, Y Zhou, G Chen - Sensors, 2021 - mdpi.com
IoT plays an important role in daily life; commands and data transfer rapidly between the
servers and objects to provide services. However, cyber threats have become a critical …

A review of threat modelling approaches for APT-style attacks

M Tatam, B Shanmugam, S Azam, K Kannoorpatti - Heliyon, 2021 - cell.com
Threats are potential events, intentional or not, that compromise the confidentiality, integrity,
and/or availability of information systems. Defending against threats and attacks requires …

Exploring SME cybersecurity practices in developing countries

S Kabanda, M Tanner, C Kent - Journal of Organizational …, 2018 - Taylor & Francis
The continued use of information technology systems by small and medium enterprises
(SMEs) in developing countries has the potential to bring significant benefits but, at the same …

A lightweight perceptron-based intrusion detection system for fog computing

B Sudqi Khater, AWB Abdul Wahab, MYIB Idris… - applied sciences, 2019 - mdpi.com
Fog computing is a paradigm that extends cloud computing and services to the edge of the
network in order to address the inherent problems of the cloud, such as latency and lack of …

Swarm intelligence inspired intrusion detection systems—a systematic literature review

MH Nasir, SA Khan, MM Khan, M Fatima - Computer Networks, 2022 - Elsevier
Abstract An Intrusion Detection System (IDS) is one of the fundamental building blocks in
securing a network. A huge number of techniques have been proposed and implemented to …

Toward a reliable anomaly-based intrusion detection in real-world environments

EK Viegas, AO Santin, LS Oliveira - Computer Networks, 2017 - Elsevier
A popular approach for detecting network intrusion attempts is to monitor the network traffic
for anomalies. Extensive research effort has been invested in anomaly-based network …

The future of artificial intelligence in cybersecurity: A comprehensive survey

F Tao, MS Akhtar, Z Jiayuan - EAI Endorsed Transactions on …, 2021 - publications.eai.eu
AI in Cybersecurity Market scheme helps organizations in observance, detecting, reporting,
and countering cyber threats to keep up information confidentiality. The increasing …