A review and analysis of the bot-iot dataset
JM Peterson, JL Leevy… - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
Machine learning is rapidly changing the cybersecu-rity landscape. The use of predictive
models to detect malicious activity and identify inscrutable attack patterns is providing levels …
models to detect malicious activity and identify inscrutable attack patterns is providing levels …
[HTML][HTML] A systematic literature review of recent lightweight detection approaches leveraging machine and deep learning mechanisms in Internet of Things networks
GAL Mukhaini, M Anbar, S Manickam… - Journal of King Saud …, 2023 - Elsevier
Abstract The Internet of Things (IoT) connects daily use devices to the Internet, such as
home appliances, health care equipment, sensors, and industrial devices. Concurrently …
home appliances, health care equipment, sensors, and industrial devices. Concurrently …
Intrusion detection framework for the internet of things using a dense random neural network
The Internet of Things (IoT) devices, networks, and applications have become an integral
part of modern societies. Despite their social, economic, and industrial benefits, these …
part of modern societies. Despite their social, economic, and industrial benefits, these …
Memory-efficient deep learning for botnet attack detection in IoT networks
Cyber attackers exploit a network of compromised computing devices, known as a botnet, to
attack Internet-of-Things (IoT) networks. Recent research works have recommended the use …
attack Internet-of-Things (IoT) networks. Recent research works have recommended the use …
Associated random neural networks for collective classification of nodes in botnet attacks
Botnet attacks are a major threat to networked systems because of their ability to turn the
network nodes that they compromise into additional attackers, leading to the spread of high …
network nodes that they compromise into additional attackers, leading to the spread of high …
[PDF][PDF] Enhancing iot security with deep stack encoder using various optimizers for botnet attack prediction
A Kalidindi, MB Arrama - … Journal of Advanced Computer Science and …, 2023 - academia.edu
The Internet of Things (IoT) connects different sensors, devices, applications, databases,
services, and people, bringing improvements to various aspects of our lives, such as cities …
services, and people, bringing improvements to various aspects of our lives, such as cities …
[PDF][PDF] Selection of efficient machine learning algorithm on Bot-IoT dataset for intrusion detection in internet of things networks
I Kerrakchou, A Abou El Hassan, S Chadli… - Indones. J. Electr. Eng …, 2023 - academia.edu
With the growth of internet of things (IoT) systems, they have become the target of malicious
third parties. In order to counter this issue, realistic investigation and protection …
third parties. In order to counter this issue, realistic investigation and protection …
Towards Developing a Robust Intrusion Detection Model Using Hadoop–Spark and Data Augmentation for IoT Networks
RA Manzano Sanchez, M Zaman, N Goel, K Naik… - Sensors, 2022 - mdpi.com
In recent years, anomaly detection and machine learning for intrusion detection systems
have been used to detect anomalies on Internet of Things networks. These systems rely on …
have been used to detect anomalies on Internet of Things networks. These systems rely on …
Intrusion Detection System for IoT Using Logical Analysis of Data and Information Gain Ratio
S Chauhan, S Gangopadhyay, AK Gangopadhyay - Cryptography, 2022 - mdpi.com
The rapidly increasing use of the internet has led to an increase in new devices and
technologies; however, attack and security violations have grown exponentially as well. In …
technologies; however, attack and security violations have grown exponentially as well. In …
Towards feasibility of Deep-Learning based Intrusion Detection System for IoT Embedded Devices
In this work we seek to determine the feasibility of implementing deep learning-based
intrusion detection on higher-capacity embedded devices, by evaluating the performance …
intrusion detection on higher-capacity embedded devices, by evaluating the performance …