CorrAUC: a malicious bot-IoT traffic detection method in IoT network using machine-learning techniques
Identification of anomaly and malicious traffic in the Internet-of-Things (IoT) network is
essential for the IoT security to keep eyes and block unwanted traffic flows in the IoT …
essential for the IoT security to keep eyes and block unwanted traffic flows in the IoT …
A Productive Feature Selection Criterion for Bot-IoT Recognition based on Random Forest Algorithm
R Pavaiyarkarasi, T Manimegalai… - 2022 IEEE 11th …, 2022 - ieeexplore.ieee.org
For IoT security to function properly, it is necessary to identify anomalies and suspicious
activities in the Internet of things (IoT) network in order to keep an eye on things and stop …
activities in the Internet of things (IoT) network in order to keep an eye on things and stop …
Selection of effective machine learning algorithm and Bot-IoT attacks traffic identification for internet of things in smart city
Identifying cyber attacks traffic is very important for the Internet of things (IoT) security in
smart city. Recently, the research community in the field of IoT Security endeavor hard to …
smart city. Recently, the research community in the field of IoT Security endeavor hard to …
IoT malicious traffic identification using wrapper-based feature selection mechanisms
Abstract Machine Learning (ML) plays very significant role in the Internet of Things (IoT)
cybersecurity for malicious and intrusion traffic identification. In other words, ML algorithms …
cybersecurity for malicious and intrusion traffic identification. In other words, ML algorithms …
Effective multitask deep learning for iot malware detection and identification using behavioral traffic analysis
Despite the benefits of the Internet of Things (IoT), the growing influx of IoT-specific malware
coordinating large-scale cyberattacks via infected IoT devices has created a substantial …
coordinating large-scale cyberattacks via infected IoT devices has created a substantial …
[PDF][PDF] Attack and anomaly detection in IoT networks using supervised machine learning approaches.
H Tyagi, R Kumar - Revue d'Intelligence Artificielle, 2021 - researchgate.net
Accepted: 9 February 2021 IoT is characterized by communication between things (devices)
that constantly share data, analyze, and make decisions while connected to the internet …
that constantly share data, analyze, and make decisions while connected to the internet …
A lightweight deep learning framework for botnet detecting at the IoT edge
Nowadays, a large number of Internet-of-Things (IoT) devices are exposed on the Internet.
Due to the serious security flaws and users' misuse, they are vulnerable to various attacks …
Due to the serious security flaws and users' misuse, they are vulnerable to various attacks …
A two-level flow-based anomalous activity detection system for IoT networks
I Ullah, QH Mahmoud - Electronics, 2020 - mdpi.com
The significant increase of the Internet of Things (IoT) devices in smart homes and other
smart infrastructure, and the recent attacks on these IoT devices, are motivating factors to …
smart infrastructure, and the recent attacks on these IoT devices, are motivating factors to …
An automatic and efficient malware traffic classification method for secure Internet of Things
Malware traffic classification (MTC) plays an important role in cyber security and network
resource management for the secure Internet of Things (IoT). Many deep learning (DL) …
resource management for the secure Internet of Things (IoT). Many deep learning (DL) …
Network flow based IoT botnet attack detection using deep learning
S Sriram, R Vinayakumar, M Alazab… - IEEE INFOCOM 2020 …, 2020 - ieeexplore.ieee.org
Governments around the globe are promoting smart city applications to enhance the quality
of daily-life activities in urban areas. Smart cities include internet-enabled devices that are …
of daily-life activities in urban areas. Smart cities include internet-enabled devices that are …