Cyber-security challenges in aviation industry: A review of current and future trends
The integration of Information and Communication Technology (ICT) tools into mechanical
devices in routine use within the aviation industry has heightened cyber-security concerns …
devices in routine use within the aviation industry has heightened cyber-security concerns …
Machine learning-driven intrusion detection for Contiki-NG-based IoT networks exposed to NSL-KDD dataset
Wide adoption of Internet of Things (IoT) devices and applications encounters security
vulnerabilities as roadblocks. The heterogeneous nature of IoT systems prevents common …
vulnerabilities as roadblocks. The heterogeneous nature of IoT systems prevents common …
Deep neural network based anomaly detection in Internet of Things network traffic tracking for the applications of future smart cities
An anomaly exposure system's foremost objective is to categorize the behavior of the system
into normal and untruthful actions. To estimate the possible incidents, the administrators of …
into normal and untruthful actions. To estimate the possible incidents, the administrators of …
Biometric authentication-based intrusion detection using artificial intelligence internet of things in smart city
Nowadays, there is a growing demand for information security and security rules all across
the world. Intrusion detection (ID) is a critical technique for detecting dangers in a network …
the world. Intrusion detection (ID) is a critical technique for detecting dangers in a network …
From 3D point clouds to HBIM: application of artificial intelligence in cultural heritage
VA Cotella - Automation in Construction, 2023 - Elsevier
Interest in semantic segmentation of 3D point clouds using ML and DL has grown due to
their key role in scene insight across a wide range of computer vision, robotics and remote …
their key role in scene insight across a wide range of computer vision, robotics and remote …
CNN-CNN: Dual Convolutional Neural Network Approach for Feature Selection and Attack Detection on Internet of Things Networks
The Internet of Things (IoT) has brought significant advancements that have connected our
world more closely than ever before. However, the growing number of connected devices …
world more closely than ever before. However, the growing number of connected devices …
Ransomware detection using deep learning based unsupervised feature extraction and a cost sensitive Pareto Ensemble classifier
Ransomware attacks pose a serious threat to Internet resources due to their far-reaching
effects. It's Zero-day variants are even more hazardous, as less is known about them. In this …
effects. It's Zero-day variants are even more hazardous, as less is known about them. In this …
A New V‐Net Convolutional Neural Network Based on Four‐Dimensional Hyperchaotic System for Medical Image Encryption
In the transmission of medical images, if the image is not processed, it is very likely to leak
data and personal privacy, resulting in unpredictable consequences. Traditional encryption …
data and personal privacy, resulting in unpredictable consequences. Traditional encryption …
BDEdge: blockchain and deep-learning for secure edge-envisioned green CAVs
Green Connected and Autonomous Vehicles (CAVs) are the future of next-generation
Intelligent Transportation Systems (ITS) that will help humans to improve road safety and …
Intelligent Transportation Systems (ITS) that will help humans to improve road safety and …
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 …