Composition of hybrid deep learning model and feature optimization for intrusion detection system
Recently, with the massive growth of IoT devices, the attack surfaces have also intensified.
Thus, cybersecurity has become a critical component to protect organizational boundaries …
Thus, cybersecurity has become a critical component to protect organizational boundaries …
A performance overview of machine learning-based defense strategies for advanced persistent threats in industrial control systems
Cybersecurity incident response is a very crucial part of the cybersecurity management
system. Adversaries emerge and evolve with new cybersecurity tactics, techniques, and …
system. Adversaries emerge and evolve with new cybersecurity tactics, techniques, and …
[HTML][HTML] Dependable intrusion detection system using deep convolutional neural network: A novel framework and performance evaluation approach
Intrusion detection systems (IDS) play a critical role in safeguarding computer networks
against unauthorized access and malicious activities. However, traditional IDS approaches …
against unauthorized access and malicious activities. However, traditional IDS approaches …
[HTML][HTML] Snow depth estimation at country-scale with high spatial and temporal resolution
Monitoring snow depth is important for applications such as hydrology, energy planning,
ecology, and safety evaluation for outdoor winter activities. Most methods able to estimate …
ecology, and safety evaluation for outdoor winter activities. Most methods able to estimate …
Cyber-secure SDN: A CNN-based approach for efficient detection and mitigation of DDoS attacks
Abstract Software Defined Networking (SDN) has become popular due to its flexibility and
agility in network management, enabling rapid adaptation to changing business …
agility in network management, enabling rapid adaptation to changing business …
Deep learning model transposition for network intrusion detection systems
Companies seek to promote a swift digitalization of their business processes and new
disruptive features to gain an advantage over their competitors. This often results in a wider …
disruptive features to gain an advantage over their competitors. This often results in a wider …
IoT-based privacy-preserving anomaly detection model for smart agriculture
Internet of Things (IoT) technology has been incorporated into the majority of people's
everyday lives and places of employment due to the quick development in information …
everyday lives and places of employment due to the quick development in information …
Early-Season Crop Map** on an Agricultural Area in Italy Using X-Band Dual-Polarization SAR Satellite Data and Convolutional Neural Networks
G Fontanelli, A Lapini, L Santurri… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Early-season crop map** provides decision-makers with timely information on crop types
and conditions that are crucial for agricultural management. Current satellite-based map** …
and conditions that are crucial for agricultural management. Current satellite-based map** …
LST-GCN: Long Short-Term Memory embedded graph convolution network for traffic flow forecasting
X Han, S Gong - Electronics, 2022 - mdpi.com
Traffic flow prediction is an important part of the intelligent transportation system. Accurate
traffic flow prediction is of great significance for strengthening urban management and …
traffic flow prediction is of great significance for strengthening urban management and …
[HTML][HTML] Traffic Feature Selection and Distributed Denial of Service Attack Detection in Software-Defined Networks Based on Machine Learning
D Han, H Li, X Fu, S Zhou - Sensors, 2024 - mdpi.com
As 5G technology becomes more widespread, the significant improvement in network speed
and connection density has introduced more challenges to network security. In particular …
and connection density has introduced more challenges to network security. In particular …