[HTML][HTML] Evolving cybersecurity frontiers: A comprehensive survey on concept drift and feature dynamics aware machine and deep learning in intrusion detection …

MA Shyaa, NF Ibrahim, Z Zainol, R Abdullah… - … Applications of Artificial …, 2024‏ - Elsevier
Abstract Intrusion Detection Systems (IDS) have become pivotal in safeguarding information
systems against evolving threats. Concurrently, Concept Drift presents a significant …

Securing the internet of robotic things: a comprehensive review on machine learning-based intrusion detection

M Nkoom, SG Hounsinou… - Journal of Cyber Security …, 2024‏ - Taylor & Francis
ABSTRACT The Internet of Robotic Things (IoRT) emerges from integrating robotics into the
Internet of things (IoT). The dynamic nature of the IoRT environment poses unique security …

Enhanced intrusion detection with data stream classification and concept drift guided by the incremental learning genetic programming combiner

MA Shyaa, Z Zainol, R Abdullah, M Anbar, L Alzubaidi… - Sensors, 2023‏ - mdpi.com
Concept drift (CD) in data streaming scenarios such as networking intrusion detection
systems (IDS) refers to the change in the statistical distribution of the data over time. There …

A two stage lightweight approach for intrusion detection in Internet of Things

Z Li, W Yao - Expert Systems with Applications, 2024‏ - Elsevier
The prevalence of the Internet of Things (IoT) in people's life has led to a significant rise in
the amounts of breaches against different IoT devices. Given that IoT devices are typically …

Learning near-optimal intrusion responses against dynamic attackers

K Hammar, R Stadler - IEEE Transactions on Network and …, 2023‏ - ieeexplore.ieee.org
We study automated intrusion response and formulate the interaction between an attacker
and a defender as an optimal stop** game where attack and defense strategies evolve …

A micro reinforcement learning architecture for intrusion detection systems

B Darabi, M Bag-Mohammadi, M Karami - Pattern Recognition Letters, 2024‏ - Elsevier
This paper proposes an Intrusion Detection System (IDS) that utilizes Deep Reinforcement
Learning (DRL) in a fine-grained manner to enhance the performance of binary and …

Novel Intrusion Detection Strategies With Optimal Hyper Parameters for Industrial Internet of Things Based On Stochastic Games and Double Deep Q-Networks

S Yu, X Wang, Y Shen, G Wu, S Yu… - IEEE Internet of Things …, 2024‏ - ieeexplore.ieee.org
The Industrial Internet of Things (IIoT) has experienced rapid growth in recent years, with an
increasing number of interconnected devices, thereby expanding the attack surface …

Towards a reliable and lightweight onboard fault detection in autonomous unmanned aerial vehicles

SS Katta, EK Viegas - 2023 IEEE International Conference on …, 2023‏ - ieeexplore.ieee.org
This paper proposes a new model for onboard physical fault detection on autonomous
unmanned aerial vehicles (UAV) through machine learning (ML) techniques. The proposal …

Towards a reliable hierarchical android malware detection through image-based cnn

J Geremias, EK Viegas, AO Santin… - 2023 IEEE 20th …, 2023‏ - ieeexplore.ieee.org
The number of Android malicious applications keeps growing as time passes, even paving
their way to official app markets. In recent years, a promising malware detection approach …

Network-based intrusion detection through image-based cnn and transfer learning

P Horchulhack, EK Viegas, AO Santin… - 2024 International …, 2024‏ - ieeexplore.ieee.org
Machine learning (ML) techniques for network intrusion detection is still limited in production
environments despite promising results reported in the literature. Network traffic behavior …