[HTML][HTML] Recent advancements and challenges of AIoT application in smart agriculture: a review
As the most popular technologies of the 21st century, artificial intelligence (AI) and the
internet of things (IoT) are the most effective paradigms that have played a vital role in …
internet of things (IoT) are the most effective paradigms that have played a vital role in …
[HTML][HTML] Reviewing and integrating aec practices into industry 6.0: Strategies for smart and sustainable future-built environments
A Almusaed, I Yitmen, A Almssad - Sustainability, 2023 - mdpi.com
This article explores the possible ramifications of incorporating ideas from AEC Industry 6.0
into the design and construction of intelligent, environmentally friendly, and long-lasting …
into the design and construction of intelligent, environmentally friendly, and long-lasting …
Intrusion detection in the automotive domain: A comprehensive review
The automotive domain has realized amazing advancements in communication,
connectivity, and automation—and at a breakneck pace. Such advancements come with …
connectivity, and automation—and at a breakneck pace. Such advancements come with …
Stochastic gradient descent classifier-based lightweight intrusion detection systems using the efficient feature subsets of datasets
J Azimjonov, T Kim - Expert Systems with Applications, 2024 - Elsevier
Abstract The Internet of Things (IoT) has become an essential part of our daily lives.
However, with the increasing use of IoT, the number of botnet attacks targeting resource …
However, with the increasing use of IoT, the number of botnet attacks targeting resource …
TSGS: Two-stage security game solution based on deep reinforcement learning for Internet of Things
X Feng, H Xia, S Xu, L Xu, R Zhang - Expert Systems with Applications, 2023 - Elsevier
The lack of effective defense resource allocation strategies and reliable multi-agent
collaboration mechanisms lead to the low stability of Deep Reinforcement Learning (DRL) …
collaboration mechanisms lead to the low stability of Deep Reinforcement Learning (DRL) …
[HTML][HTML] can-train-and-test: A Curated CAN Dataset for Automotive Intrusion Detection
When it comes to in-vehicle networks (IVNs), the controller area network (CAN) bus
dominates the market; automobiles manufactured and sold worldwide depend on the CAN …
dominates the market; automobiles manufactured and sold worldwide depend on the CAN …
HDA-IDS: A Hybrid DoS Attacks Intrusion Detection System for IoT by using semi-supervised CL-GAN
In recent years, the application of the internet of things (IoT) in areas such as intelligent
transportation, smart cities, and the industrial internet has become increasingly widespread …
transportation, smart cities, and the industrial internet has become increasingly widespread …
A novel hybrid quantum-classical framework for an in-vehicle controller area network intrusion detection
In-vehicle controller area network (CAN) is susceptible to various cyberattacks due to its
broadcast-based communication nature. An attacker can inject false messages to a vehicle's …
broadcast-based communication nature. An attacker can inject false messages to a vehicle's …
[HTML][HTML] A review of security attacks and intrusion detection in the vehicular networks
With the proliferation of Vehicular Ad Hoc Networks (VANETs), ensuring the security and
integrity of communication within these networks has become a paramount concern. This …
integrity of communication within these networks has become a paramount concern. This …
DivaCAN: Detecting in-vehicle intrusion attacks on a controller area network using ensemble learning
The controller area network (CAN) protocol is a critical communication mechanism in
vehicular systems. However, the widespread adoption of this protocol has introduced …
vehicular systems. However, the widespread adoption of this protocol has introduced …