Malware detection using genetic cascaded support vector machine classifier in Internet of Things

SK Gupta, B Pattnaik, V Agrawal… - 2022 Second …, 2022 - ieeexplore.ieee.org
The Internet of Things (IoT) is a network of computing devices that can transmit and obtain
data across a network without human intervention. In the last couple of decades, software …

HOMLC-Hyperparameter Optimization for Multi-Label Classification of Intrusion Detection Data for Internet of Things Network

A Sharma, S Rani, DK Sah, Z Khan, W Boulila - Sensors, 2023 - mdpi.com
The comparison of low-rank-based learning models for multi-label categorization of attacks
for intrusion detection datasets is presented in this work. In particular, we investigate the …

Machine-learning-based vulnerability detection and classification in internet of things device security

SB Hulayyil, S Li, L Xu - Electronics, 2023 - mdpi.com
Detecting cyber security vulnerabilities in the Internet of Things (IoT) devices before they are
exploited is increasingly challenging and is one of the key technologies to protect IoT …

[HTML][HTML] Secure edge computing vulnerabilities in smart cities sustainability using petri net and genetic algorithm-based reinforcement learning

LA Ajao, ST Apeh - Intelligent Systems with Applications, 2023 - Elsevier
Abstract The Industrial Internet of Things (IIoT) revolution has emerged as a promising
network that enhanced information dissemination about the city's resources. This city's …

SUKRY: suricata IDS with enhanced kNN algorithm on raspberry Pi for classifying IoT botnet attacks

I Syamsuddin, OM Barukab - electronics, 2022 - mdpi.com
The focus of this research is the application of the k-Nearest Neighbor algorithm in terms of
classifying botnet attacks in the IoT environment. The kNN algorithm has several advantages …

A big data analytics for DDOS attack detection using optimized ensemble framework in Internet of Things

I Ahmad, Z Wan, A Ahmad - Internet of Things, 2023 - Elsevier
Abstract Internet of Things (IoT) devices significantly threaten tech-dependant businesses
and communities. With the rapid integration of IoT devices into local networks, a system to …

[图书][B] Factors Influencing the Adoption of Machine Learning Algorithms to Detect Cyber Threats in the Banking Industry

H Gonaygunta - 2023 - search.proquest.com
Cyber attacks have evolved, making predicting and preventing their occurrence difficult. The
complexity of cyber threats has contributed to the development of technology-intensive …

An ensemble-based machine learning approach for cyber-attacks detection in wireless sensor networks

S Ismail, Z El Mrabet, H Reza - Applied Sciences, 2022 - mdpi.com
Wireless Sensor Networks (WSNs) are the key underlying technology of the Internet of
Things (IoT); however, these networks are energy constrained. Security has become a major …

A deep learning approach for classifying network connected IoT devices using communication traffic characteristics

RR Chowdhury, AC Idris, PE Abas - Journal of Network and Systems …, 2023 - Springer
Abstract The Internet of Things can be considered a technological revolution and has
successfully merged the physical world with the digital world. However, heterogeneous IoT …

Anomaly Detection Framework in Fog-to-Things Communication for Industrial Internet of Things.

T Alatawi, A Aljuhani - Computers, Materials & Continua, 2022 - search.ebscohost.com
The rapid development of the Internet of Things (IoT) in the industrial domain has led to the
new term the Industrial Internet of Things (IIoT). The IIoT includes several devices …