Results 81 to 90 of about 4,077 (204)

A Survey for Deep Reinforcement Learning Based Network Intrusion Detection

Applied AI Letters, Volume 7, Issue 2, June 2026.
This paper surveys deep reinforcement learning (DRL) for network intrusion detection, evaluating model efficiency, minority attack detection, and dataset imbalance. Findings show DRL achieves state‐of‐the‐art results on public datasets, sometimes surpassing traditional deep learning.
Wanrong Yang, Alberto Acuto, Yihang Zhou, Dominik Wojtczak   +3 more
wiley   +1 more source

Semi-Supervised Encrypted Malicious Traffic Detection Based on Multimodal Traffic Characteristics

Sensors
The exponential growth of encrypted network traffic poses significant challenges for detecting malicious activities online. The scale of emerging malicious traffic is significantly smaller than that of normal traffic, and the imbalanced data distribution poses challenges for detection. However, most existing methods rely on single-category features for
Ming Liu, Qichao Yang, Wenqing Wang, Shengli Liu   +3 more
openaire   +3 more sources

Event‐Triggered Saturating Control for Synchronization of Lur'e Type Complex Dynamic Networks

International Journal of Robust and Nonlinear Control, Volume 36, Issue 4, Page 2184-2198, 10 March 2026.
ABSTRACT This article addresses the problem of synchronizing discrete‐time Lur'e type complex dynamic networks (CDNs) via dynamic event‐triggered control. In particular, it is considered that the control signal of each node is subject to input saturation. Using the Lyapunov Stability Theory, properties of slope‐restricted nonlinearities, and the linear
C. Lisbôa, J. V. Flores, L. G. Moreira, J. M. Gomes da Silva Jr.   +3 more
wiley   +1 more source

Survey of research on encrypted traffic classification based on machine learning

Tongxin xuebao
Encrypted traffic classification was an important component of network management and security protection. However, the complexity and variability of the current network traffic environment rendered traditional classification methods largely ineffective.
FU Yu, LIU Taotao, WANG Kun, YU Yihan
doaj  

MLDAS: Machine Learning Dynamic Algorithm Selection for Software‐Defined Networking Security

Concurrency and Computation: Practice and Experience, Volume 38, Issue 5, March 2026.
ABSTRACT Network security is a critical concern in the digital landscape of today, with users demanding secure browsing experiences and protection of their personal data. This study explores the dynamic integration of Machine Learning (ML) algorithms with Software‐Defined Networking (SDN) controllers to enhance network security through adaptive ...
Pablo Benlloch, Oscar Romero, Antonio Leon, Jaime Lloret   +3 more
wiley   +1 more source

High‐Resolution Neural Network‐Based Teaching Skill Development for Teachers in Edge Computing Environment

Engineering Reports, Volume 8, Issue 3, March 2026.
Where user devices include cell phones, tablets, laptops, and so on, which communicate with edge computing servers and use computational as well as storage resources provided by edge computing. Network connectivity is the core component of edge computing, which allows communication between mobile devices and edge computing nodes.
Genlian Zhang
wiley   +1 more source

Digital Twin Integration in Project Life Cycle Management—A Review

Engineering Reports, Volume 8, Issue 3, March 2026.
This study explores the integration of digital twin (DT) technology within project life cycle management (PLM), focusing on its transformative impact on industries like aerospace, automotive, healthcare, and construction. By creating real‐time virtual models synchronized with physical assets, DTs enable predictive maintenance, operational optimization,
Md. Injamamul Haque Protyai, Rajowone Shariar, Hrittik Mural   +2 more
wiley   +1 more source

Application of Embodied Intelligence in Intelligent Warehousing and Logistics Scenarios

Engineering Reports, Volume 8, Issue 3, March 2026.
Embodied intelligence (EI) enhances digital platform efficiency in intelligent logistics, reducing transportation costs, improving throughput by 37.5%, and lowering energy consumption. EI‐driven improvements lead to discriminatory pricing strategies, while lightweight encryption ensures minimal performance overhead, maintaining real‐time operations ...
Jun Zhang, Chuan Zhang, Mingtao Zhang
wiley   +1 more source

CLSTM-MT (a Combination of 2-Conv CNN and BiLSTM Under the Mean Teacher Collaborative Learning Framework): Encryption Traffic Classification Based on CLSTM (a Combination of 2-Conv CNN and BiLSTM) and Mean Teacher Collaborative Learning

Applied Sciences
The identification and classification of network traffic are crucial for maintaining network security, optimizing network management, and ensuring reliable service quality.
Xiaozong Qiu, Guohua Yan, Lihua Yin
doaj   +1 more source

Analysis of Encrypted Malicious Traffic

, 2019
In recent years there has been a dramatic increase in the number of malware attacks that use encrypted HTTP traffic for self-propagation and communication. Due to the volume of legitimate encrypted data, encrypted malicious traffic resembles benign traffic.
openaire   +2 more sources