P‐DNN: Parallel DNN based IDS framework for the detection of IoT vulnerabilities

S BS, R Nagapadma - Security and Privacy, 2024 - Wiley Online Library
The rapid growth of the Internet of Things (IoT) in our daily life has recently received
attention from hackers in releasing novel attacks. This is because the existing traditional …

A Scrutiny of Privacy and Security Issues in Fog Computing Environment

R Alexander, KPM Kumar - 2022 3rd International Conference …, 2022 - ieeexplore.ieee.org
The current technological improvements of IoT devices result in a significant volume of data
being generated. Traditional cloud-based systems store all data in a geographically …

CVS-FLN: a novel IoT-IDS model based on metaheuristic feature selection and neural network classification model

R Geetha, A Jegatheesan, RK Dhanaraj… - Multimedia Tools and …, 2024 - Springer
Abstract The Internet of Things (IoT) is one of the technologies that will be used all over the
world in the future, and its security and privacy features are the primary concerns. However …

Hybrid wrapper feature selection method based on genetic algorithm and extreme learning machine for intrusion detection

EM Maseno, Z Wang - Journal of Big Data, 2024 - Springer
Intrusion detection systems play a critical role in the mitigation of cyber-attacks on the
Internet of Things (IoT) environment. Due to the integration of many devices within the IoT …

Different mechanisms of machine learning and optimization algorithms utilized in intrusion detection systems

MR Aziz, AS Alfoudi - AIP Conference Proceedings, 2023 - pubs.aip.org
Malicious software is an integral part of cybercrime defense. Due to the growing number of
malicious attacks and their target sources, detecting and preventing the attack becomes …

An adaptive nonlinear whale optimization multi-layer perceptron cyber intrusion detection framework

H El-Ghaish, H Miqrish, A Elmogy… - International Journal of …, 2024 - Springer
The increasing prevalence of cyber threats has created a critical need for robust defense
against such incidents. Many Cyber Intrusion Detection Systems (CIDSs), utilizing machine …

An intelligent deep feature based intrusion detection system for network applications

K Shailaja, B Srinivasulu, L Thirupathi… - Wireless Personal …, 2023 - Springer
The network's digital applications and functions are vulnerable to get attacks from malicious
events. Hence, an Intrusion Detection System (IDS) is the required process for the network …

Detecting DDoS attacks using machine learning algorithms and feature selection methods

M Almaiah, R Alrawashdeh… - … Journal of Data and …, 2024 - m.growingscience.com
A Distributed Denial of Service (DDoS) attack occurs when an attacker tries to disrupt a
network, service or website by flooding huge numbers of packets on the internet traffic …

An efficient intrusion detection systems in fog computing using forward selection and BiLSTM

FA Zwayed, M Anbar, S Manickam, Y Sanjalawe… - Bulletin of Electrical …, 2024 - beei.org
Intrusion detection systems (IDS) play a pivotal role in network security and anomaly
detection and are significantly impacted by the feature selection (FS) process. As a …

Intrusion detection system: a deep neural network-based concatenated approach

HS Sharma, KJ Singh - The Journal of Supercomputing, 2024 - Springer
In recent years, the field of information security has seen a substantial rise in the use of
approaches that include deep learning. The implementation of deep learning strategies into …