[HTML][HTML] A novel approach for detecting vulnerable IoT devices connected behind a home NAT
Y Meidan, V Sachidananda, H Peng, R Sagron… - Computers & …, 2020 - Elsevier
Telecommunication service providers (telcos) are exposed to cyber-attacks executed by
compromised IoT devices connected to their customers' networks. Such attacks might have …
compromised IoT devices connected to their customers' networks. Such attacks might have …
Toward the protection of IoT networks: Introducing the LATAM-DDoS-IoT dataset
JG Almaraz-Rivera, JA Perez-Diaz… - IEEE …, 2022 - ieeexplore.ieee.org
Anomaly detection is a well-known topic in cybersecurity. Its application to the Internet of
Things can lead to suitable protection techniques against problems such as denial of service …
Things can lead to suitable protection techniques against problems such as denial of service …
A deep learning approach for classifying network connected IoT devices using communication traffic characteristics
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 …
successfully merged the physical world with the digital world. However, heterogeneous IoT …
A machine learning model for classifying unsolicited IoT devices by observing network telescopes
The Internet of Things [IoT] promises to revolutionize the way we interact with our
surroundings. Smart cars, smart cities, smart homes are now being realized with the help of …
surroundings. Smart cars, smart cities, smart homes are now being realized with the help of …
Iot device identification using deep learning
The growing use of IoT devices in organizations has increased the number of attack vectors
available to attackers due to the less secure nature of the devices. The widely adopted bring …
available to attackers due to the less secure nature of the devices. The widely adopted bring …
The case for retraining of ML models for IoT device identification at the edge
Internet-of-Things (IoT) devices are known to be the source of many security problems, and
as such they would greatly benefit from automated management. This requires robustly …
as such they would greatly benefit from automated management. This requires robustly …
Smart defense against distributed Denial of service attack in IoT networks using supervised learning classifiers
From smart home to industrial automation to smart power grid, IoT-based solutions penetrate
into every working field. These devices expand the attack surface and turned out to be an …
into every working field. These devices expand the attack surface and turned out to be an …
Traffic data extraction and labeling for machine learning based attack detection in IoT networks
H Gebrye, Y Wang, F Li - International Journal of Machine Learning and …, 2023 - Springer
The fast expansion of the Internet of Things (IoT) networks raises the possibility of further
network threats. In today's world, network traffic analysis has become an increasingly critical …
network threats. In today's world, network traffic analysis has become an increasingly critical …
A machine learning based framework for IoT device identification and abnormal traffic detection
Network security is a key challenge for the deployment of Internet of Things (IoT). New
attacks have been developed to exploit the vulnerabilities of IoT devices. Moreover, IoT …
attacks have been developed to exploit the vulnerabilities of IoT devices. Moreover, IoT …
Machine learning ddos detection for consumer internet of things devices
An increasing number of Internet of Things (IoT) devices are connecting to the Internet, yet
many of these devices are fundamentally insecure, exposing the Internet to a variety of …
many of these devices are fundamentally insecure, exposing the Internet to a variety of …