ProvIoT: Detecting Stealthy Attacks in IoT through Federated Edge-Cloud Security
Abstract Internet of Things (IoT) devices have increased drastically in complexity and
prevalence within the last decade. Alongside the proliferation of IoT devices and …
prevalence within the last decade. Alongside the proliferation of IoT devices and …
Detecting Anomalies in IoT Devices: A Machine Learning-Based Solution
R Al Attar, M Alohaly - 2024 - preprints.org
The growing shift toward Internet of Things (IoT)-based solutions expands the attack surface
of systems by connecting an extensive network of heterogeneous devices and technologies …
of systems by connecting an extensive network of heterogeneous devices and technologies …
DÏoT: A federated self-learning anomaly detection system for IoT
IoT devices are increasingly deployed in daily life. Many of these devices are, however,
vulnerable due to insecure design, implementation, and configuration. As a result, many …
vulnerable due to insecure design, implementation, and configuration. As a result, many …
CMD: Co-analyzed IoT Malware Detection and Forensics via Network and Hardware Domains
With the widespread use of Internet of Things (IoT) devices, malware detection has become
a hot spot for both academic and industrial communities. Existing approaches can be …
a hot spot for both academic and industrial communities. Existing approaches can be …
Securing emerging IoT systems through systematic analysis and design
Q Wang - 2020 - ideals.illinois.edu
Abstract The Internet of Things (IoT) is growing very rapidly. A variety of IoT systems have
been developed and employed in many domains such as smart home, smart city and …
been developed and employed in many domains such as smart home, smart city and …
A near real-time scheme for collecting and analyzing iot malware artifacts at scale
The chronic proliferation of Internet of Things (IoT) botnet malware activities coupled with an
unprecedented rise in security vulnerabilities convene a new world of opportunities for …
unprecedented rise in security vulnerabilities convene a new world of opportunities for …
IoT Malicious Traffic Detection Based on Federated Learning
Y Shen, Y Zhang, Y Li, W Ding, M Hu, Y Li… - … Conference on Digital …, 2023 - Springer
Nowadays, a large number of IoT devices are manufactured and used in daily life. However,
the lack of uniform protocols and standards for IoT devices brings many security risks …
the lack of uniform protocols and standards for IoT devices brings many security risks …
Federated-learning-based anomaly detection for IoT security attacks
V Mothukuri, P Khare, RM Parizi… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
The Internet of Things (IoT) is made up of billions of physical devices connected to the
Internet via networks that perform tasks independently with less human intervention. Such …
Internet via networks that perform tasks independently with less human intervention. Such …
Understanding and detecting remote infection on linux-based iot devices
The rocketed population, poor security, and 24/7 online properties make Linux-based
Internet of Things (IoT) devices ideal targets for attackers. However, due to the budget …
Internet of Things (IoT) devices ideal targets for attackers. However, due to the budget …
Privacy-Aware Anomaly Detection in IoT Environments using FedGroup: A Group-Based Federated Learning Approach
The popularity of Internet of Things (IoT) devices in smart homes has raised significant
concerns regarding data security and privacy. Traditional machine learning (ML) methods …
concerns regarding data security and privacy. Traditional machine learning (ML) methods …