过去一年中添加的文章，按日期排序
A dual-stage deep learning model based on a sparse autoencoder and layered deep classifier for intrusion detection with imbalanced data
O Al-Harbi, A Hamed - … Journal of Sensor Networks, 2024 - inderscienceonline.com
22 天前 - … network (CNN) and bidirectional long short-term memory (Bi-… include machine
learning, deep neural networks, natural … To evaluate the performance of our proposed model, we …
learning, deep neural networks, natural … To evaluate the performance of our proposed model, we …
An Enhanced Hybrid Deep Learning Model to Enhance Network Intrusion Detection Capabilities for Cybersecurity
A Das, N Shobha, M Natesh… - Journal of Machine and …, 2024 - impressions.manipal.edu
24 天前 - … neural networks (CNNs), Multilayer Perceptron (MLP), and long short-term memories
(… A discussion of the outcomes achieved follows an assessment of the proposed DL model …
(… A discussion of the outcomes achieved follows an assessment of the proposed DL model …
[PDF][PDF] Intrusion Detection for In-Vehicle CAN Communication Using Deep Neural Networks
F Sundfeldt, B Widstam - 2024 - lup.lub.lu.se
30 天前 - … Convolutional Neural Network) och LSTM (Long Short-Term Memory)… deep learning
models are evaluated, Convolutional Neural Network (CNN) and Long Short-Term Memory …
models are evaluated, Convolutional Neural Network (CNN) and Long Short-Term Memory …
Securing the IoT Cyber Environment: Enhancing Intrusion Anomaly Detection with Vision Transformers
33 天前 - … cutting-edge DL approach of long short-term memory (LSTM) and vision … intrusion
detection model using improved ViT to solve the issue of memory in recurrent neural networks …
detection model using improved ViT to solve the issue of memory in recurrent neural networks …
Deep learning method for efficient cloud IDS utilizing combined behavior and flow-based features
G TV, D AJ - Applied Intelligence, 2024 - Springer
33 天前 - … Then, bidirectional long short-term memory (… deep learning approach for Intrusion
Detection Systems (IDSs), leveraging a framework based on Recurrent Neural Networks (…
Detection Systems (IDSs), leveraging a framework based on Recurrent Neural Networks (…
[HTML][HTML] Inertial Sensors-Based Assessment of Human Breathing Pattern: A Systematic Literature Review
33 天前 - … These encompass a diverse range of techniques, including Modified Long Short-Term
Memory Recurrent Neural Network [63], K-means clustering [48], Correlation-based …
Memory Recurrent Neural Network [63], K-means clustering [48], Correlation-based …
Developing robust machine learning models to defend against adversarial attacks in the field of cybersecurity
TA Khaleel - 2024 International Congress on Human-Computer …, 2024 - ieeexplore.ieee.org
34 天前 - … preprocessing, and evaluating the robustness of … networks (GANs), random forest
ensembles, and a variety of scenario-specific hybrid approaches. Assess their effectiveness in …
ensembles, and a variety of scenario-specific hybrid approaches. Assess their effectiveness in …
[PDF][PDF] Towards Image-Based Network Traffic Pattern Detection for DDoS Attacks in Cloud Computing Environments: A Comparative Study.
A Abdullah, MA Bouke - CLOSER, 2024 - scitepress.org
41 天前 - … Neural Networks (CNN), Long Short-Term Memory (LSTM… evaluate various models
based on deep neural networks (… study to evaluate the effectiveness of intrusion detection …
based on deep neural networks (… study to evaluate the effectiveness of intrusion detection …
Efficient RNN Models for IOT Intrusion Detection System
R Jablaoui, N Liouane - 2024 International Conference on …, 2024 - ieeexplore.ieee.org
42 天前 - … and various network attacks as a protective measure from … Recurrent Neural
Network (RNN) models long short-term … networks with long short-term memory. 2021 Systems of …
Network (RNN) models long short-term … networks with long short-term memory. 2021 Systems of …
Cyber Digital Twin with Deep Learning Model for Enterprise Products Management
Z Wang - Wireless Personal Communications, 2024 - Springer
49 天前 - … mechanisms with long short-term memory anomaly detection (DL-… This research
offers an intrusion detection approach for … Deep neural networks include several hidden layers, …
offers an intrusion detection approach for … Deep neural networks include several hidden layers, …