Detecting cybersecurity attacks in internet of things using artificial intelligence methods: A systematic literature review

M Abdullahi, Y Baashar, H Alhussian, A Alwadain… - Electronics, 2022 - mdpi.com
In recent years, technology has advanced to the fourth industrial revolution (Industry 4.0),
where the Internet of things (IoTs), fog computing, computer security, and cyberattacks have …

Intrusion detection in internet of things systems: a review on design approaches leveraging multi-access edge computing, machine learning, and datasets

E Gyamfi, A Jurcut - Sensors, 2022 - mdpi.com
The explosive growth of the Internet of Things (IoT) applications has imposed a dramatic
increase of network data and placed a high computation complexity across various …

A systematic literature review for network intrusion detection system (IDS)

OH Abdulganiyu, T Ait Tchakoucht… - International journal of …, 2023 - Springer
With the recent increase in internet usage, the number of important, sensitive, confidential
individual and corporate data passing through internet has increasingly grown. With gaps in …

A comprehensive study of anomaly detection schemes in IoT networks using machine learning algorithms

A Diro, N Chilamkurti, VD Nguyen, W Heyne - Sensors, 2021 - mdpi.com
The Internet of Things (IoT) consists of a massive number of smart devices capable of data
collection, storage, processing, and communication. The adoption of the IoT has brought …

IoT security challenges: cloud and blockchain, postquantum cryptography, and evolutionary techniques

S Balogh, O Gallo, R Ploszek, P Špaček, P Zajac - Electronics, 2021 - mdpi.com
Internet of Things connects the physical and cybernetic world. As such, security issues of IoT
devices are especially damaging and need to be addressed. In this treatise, we overview …

[HTML][HTML] An unsupervised TinyML approach applied to the detection of urban noise anomalies under the smart cities environment

SS Hammad, D Iskandaryan, S Trilles - Internet of Things, 2023 - Elsevier
Abstract Artificial Intelligence of Things (AIoT) is an emerging area of interest, and this can
be used to obtain knowledge and take better decisions in the same Internet of Things (IoT) …

DANTD: A deep abnormal network traffic detection model for security of industrial internet of things using high-order features

G Shi, X Shen, F Xiao, Y He - IEEE Internet of Things Journal, 2023 - ieeexplore.ieee.org
With the development of blockchain, artificial intelligence, and data mining technology,
abnormal network traffic data has become easy to obtain. The traffic detection model detects …

A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security

S Shitharth, AM Alshareef, AO Khadidos, KH Alyoubi… - Scientific Reports, 2023 - nature.com
Ensuring the privacy and trustworthiness of smart city—Internet of Things (IoT) networks
have recently remained the central problem. Cyborg intelligence is one of the most popular …

Towards an explainable universal feature set for IoT intrusion detection

MM Alani, A Miri - Sensors, 2022 - mdpi.com
As IoT devices' adoption grows rapidly, security plays an important role in our daily lives. As
part of the effort to counter these security threats in recent years, many IoT intrusion …

A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models

OBJ Rabie, S Selvarajan, T Hasanin, AM Alshareef… - Scientific Reports, 2024 - nature.com
Abstract The Internet of Things (IoT) is extensively used in modern-day life, such as in smart
homes, intelligent transportation, etc. However, the present security measures cannot fully …