Predicting Network Traffic Anomalies in Denial-of-Service Attacks-A Nonlinear Approach
The amount of data moving across the network at any given time is referred to as network
traffic. It is the data units that are encapsulated in packets and sent over a network. Denial-of …
traffic. It is the data units that are encapsulated in packets and sent over a network. Denial-of …
[HTML][HTML] A novel method for improved network traffic prediction using enhanced deep reinforcement learning algorithm
Network data traffic is increasing with expanded networks for various applications, with text,
image, audio, and video for inevitable needs. Network traffic pattern identification and …
image, audio, and video for inevitable needs. Network traffic pattern identification and …
Network Traffic Classification Using Deep Autonomous Learning Approach
NG Bhuvaneswari Amma - Security, Privacy and Data Analytics: Select …, 2022 - Springer
Nowadays computer network traffic is increasing exponentially making the Internet
vulnerable to huge number of security threats. Distributed Denial of Service (DDoS) attacks …
vulnerable to huge number of security threats. Distributed Denial of Service (DDoS) attacks …
Enhancing Denial-of-Service (DoS) Attack Defense Mechanisms through Machine Learning-Based Analysis of Network Traffic Data
N Yimporntana, S Kosolsombat - 2023 8th International …, 2023 - ieeexplore.ieee.org
The purpose of this research project is to study the classification of normal and malicious
network traffic (Denial-of Service; DoS) with a total of 5 machine learning models: Decision …
network traffic (Denial-of Service; DoS) with a total of 5 machine learning models: Decision …
A hybrid neural network architecture for early detection of DDOS attacks using deep learning models
With the increasing technologies in the digital era, the task of identification of Distributed
Denial of Service (DDoS) attacks is a significantly challenging problem due to the …
Denial of Service (DDoS) attacks is a significantly challenging problem due to the …
Generalized classification of DNS over HTTPS traffic with deep learning
LFG Casanova, PC Lin - 2021 Asia-Pacific Signal and …, 2021 - ieeexplore.ieee.org
Network anomaly detection has been a challenge for both industry and academia. The
alarming situation of network attacks is a worrisome problem for many Internet services …
alarming situation of network attacks is a worrisome problem for many Internet services …
Classification of DDoS traffic for Industrial Internet of Services using Deep learning approaches
The Industrial Internet of Services (IIoS) combines traditional industrial systems with digital
technologies, offering numerous advantages like improved efficiency, productivity, and …
technologies, offering numerous advantages like improved efficiency, productivity, and …
[PDF][PDF] Detecting and Mitigating DDOS Attacks in SDNs Using Deep Neural Network.
Distributed denial of service (DDoS) attack is the most common attack that obstructs a
network and makes it unavailable for a legitimate user. We proposed a deep neural network …
network and makes it unavailable for a legitimate user. We proposed a deep neural network …
Network Security: Approach Based on Network Traffic Prediction
S Thakare, A Pund, MA Pund - … on Computer Networks, Big Data and IoT …, 2020 - Springer
Considering the network security aspect, one of the best way of preventing network
infrastructure against anomalous activities is to monitor its traffic for suspicious activities. The …
infrastructure against anomalous activities is to monitor its traffic for suspicious activities. The …
[HTML][HTML] Traffic prediction in SDN for explainable QoS using deep learning approach
G Wassie, J Ding, Y Wondie - Scientific Reports, 2023 - nature.com
The radical increase of multimedia applications such as voice over Internet protocol (VOIP),
image processing, and video-based applications require better quality of service (QoS) …
image processing, and video-based applications require better quality of service (QoS) …