Federated Anomaly Detection with Isolation Forest for IoT Network Traffics
J Li, X Zhang, H Xiang… - 2023 IEEE 29th …, 2023 - ieeexplore.ieee.org
With the development of modern technology, the application of various types of devices in
life has become more extensive, especially with the emergence of the Internet of Things …
life has become more extensive, especially with the emergence of the Internet of Things …
IoTWarden: A Deep Reinforcement Learning Based Real-time Defense System to Mitigate Trigger-action IoT Attacks
MM Alam, I Jahan, W Wang - arXiv preprint arXiv:2401.08141, 2024 - arxiv.org
In trigger-action IoT platforms, IoT devices report event conditions to IoT hubs notifying their
cyber states and let the hubs invoke actions in other IoT devices based on functional …
cyber states and let the hubs invoke actions in other IoT devices based on functional …
DeL-IoT: A deep ensemble learning approach to uncover anomalies in IoT
Abstract Internet of Things (IoT) devices are inherently vulnerable due to insecure design,
implementation, and configuration. Aggressive behavior changes, due to increased …
implementation, and configuration. Aggressive behavior changes, due to increased …
ECMT Framework for Internet of Things: An Integrative Approach Employing In-Memory Attribute Examination and Sophisticated Neural Network Architectures in …
With the proliferation of connected devices in the Internet of Things (IoT), cybersecurity
threats have increased. Identifying malicious attacks in IoT requires advanced techniques …
threats have increased. Identifying malicious attacks in IoT requires advanced techniques …
Feco: Boosting intrusion detection capability in iot networks via contrastive learning
Over the last decade, Internet of Things (IoT) has permeated our daily life with a broad range
of applications. However, a lack of sufficient security features in IoT devices renders IoT …
of applications. However, a lack of sufficient security features in IoT devices renders IoT …
Inferring and investigating IoT-generated scanning campaigns targeting a large network telescope
The analysis of recent large-scale cyber attacks, which leveraged insecure Internet of Things
(IoT) devices to perform malicious activities on the Internet, highlighted the rise of IoT …
(IoT) devices to perform malicious activities on the Internet, highlighted the rise of IoT …
IoT Threat Detection Testbed Using Generative Adversarial Networks
The Internet of Things (IoT) paradigm provides persistent sensing and data collection
capabilities and is becoming increasingly prevalent across many market sectors. However …
capabilities and is becoming increasingly prevalent across many market sectors. However …
Software-Defined IoT with Machine Learning-Based Enhanced Security
A Husnain, C Nguyen, NT Le - 2023 28th Asia Pacific …, 2023 - ieeexplore.ieee.org
The widespread adoption of IoT devices has revolutionized multiple sectors, including
healthcare, military, agriculture, and smart cities. This surge in IoT-generated data raises …
healthcare, military, agriculture, and smart cities. This surge in IoT-generated data raises …
[PDF][PDF] Poster: Discovering Authentication Bypass Vulnerabilities in IoT Devices through Guided Concolic Execution
JW Huang, NJ Tsai, SM Cheng - ndss-symposium.org
The severity of attacks on IoT devices underscores the pressing need for efficient and
effective vulnerability discovery methods. Specifically, authentication-related vulnerabilities …
effective vulnerability discovery methods. Specifically, authentication-related vulnerabilities …
Detecting IoT Malware Using Federated Learning
QV Dang, TH Pham - International Conference on Data Science and …, 2023 - Springer
The surge in Internet of Things (IoT) device usage has concurrently seen a rise in cyber
threats aimed at these devices. Conventional centralized machine learning methods for …
threats aimed at these devices. Conventional centralized machine learning methods for …