Artificial immunity based distributed and fast anomaly detection for Industrial Internet of Things

B Li, Y Chang, H Huang, W Li, T Li, W Chen - Future Generation Computer …, 2023 - Elsevier
Recent years have witnessed an increased attack surface of the Industrial Internet of Things
(IIoT), as the deep convergence of the Internet of Things (IoT) and other information and …

Intrusion traffic detection and characterization using deep image learning

G Kaur, AH Lashkari, A Rahali - … , Intl Conf on Cloud and Big …, 2020 - ieeexplore.ieee.org
The security community has witnessed an unprecedented upsurge in cyber attacks in recent
years. These attacks have proved to be successful in achieving their catastrophic objectives …

Evaluation of machine learning algorithms for anomaly detection

N Elmrabit, F Zhou, F Li, H Zhou - … international conference on …, 2020 - ieeexplore.ieee.org
Malicious attack detection is one of the critical cyber-security challenges in the peer-to-peer
smart grid platforms due to the fact that attackers' behaviours change continuously over time …

A spectrogram image-based network anomaly detection system using deep convolutional neural network

AS Khan, Z Ahmad, J Abdullah, F Ahmad - IEEE access, 2021 - ieeexplore.ieee.org
The dynamics of computer networks have changed rapidly over the past few years due to a
tremendous increase in the volume of the connected devices and the corresponding …

IADF-CPS: Intelligent anomaly detection framework towards cyber physical systems

SM Nagarajan, GG Deverajan, AK Bashir… - Computer …, 2022 - Elsevier
Abstract Cyber–Physical Systems (CPSs) becoming one of the most complex, intelligent,
and sophisticated system. Ensuring security is an important aspect towards CPSs. However …

Anomaly-based intrusion detection using GAN for industrial control systems

KK Sabari, S Shrivastava - 2022 10th International …, 2022 - ieeexplore.ieee.org
In recent years, cyber-attacks on modern industrial control systems (ICS) have become more
common and it acts as a victim to various kind of attackers. The percentage of attacked ICS …

Anomaly detection in network traffic using unsupervised machine learning approach

A Vikram - 2020 5th International Conference on …, 2020 - ieeexplore.ieee.org
The advent of IoT technology and the increase in wireless networking devices has led to an
enormous increase in network attacks from different sources. To maintain networks as safe …

Anomaly-based intrusion detection using auto-encoder

YN Nguimbous, R Ksantini… - … Conference on Software …, 2019 - ieeexplore.ieee.org
Intrusion detection systems do not perform well when it comes to detecting new attacks.
Therefore improving their performance in that regard is an active research topic. In this …

Anomaly-based network intrusion detection system through feature selection and hybrid machine learning technique

A Pattawaro, C Polprasert - 2018 16th International Conference …, 2018 - ieeexplore.ieee.org
In this paper, we propose an anomaly-based network intrusion detection system based on a
combination of feature selection, K-Means clustering and XGBoost classification model. We …

Anomaly based novel intrusion detection system for network traffic reduction

K Vengatesan, A Kumar, R Naik… - … I-SMAC) I-SMAC (IoT in …, 2018 - ieeexplore.ieee.org
With the coming of anomaly based intrusion detection systems, numerous methodologies
and strategies have been produced to track novel assaults on the systems. High detection …