A machine learning approach for ddos (distributed denial of service) attack detection using multiple linear regression
S Sambangi, L Gondi - Proceedings, 2020 - mdpi.com
The problem of identifying Distributed Denial of Service (DDos) attacks is fundamentally a
classification problem in machine learning. In relevance to Cloud Computing, the task of …
classification problem in machine learning. In relevance to Cloud Computing, the task of …
Correlation-aware neural networks for DDOS attack detection in IoT systems
We present a comprehensive study on applying machine learning to detect distributed
Denial of service (DDoS) attacks using large-scale Internet of Things (IoT) systems. While …
Denial of service (DDoS) attacks using large-scale Internet of Things (IoT) systems. While …
A survey on types of machine learning techniques in intrusion prevention systems
The computation technology is evolving. The data transmitted and generated using them are
growing exponentially. The traffic on these networks requires surveillance. Effective network …
growing exponentially. The traffic on these networks requires surveillance. Effective network …
Supervised learning‐based DDoS attacks detection: Tuning hyperparameters
M Kim - ETRI Journal, 2019 - Wiley Online Library
Two supervised learning algorithms, a basic neural network and a long short‐term memory
recurrent neural network, are applied to traffic including DDoS attacks. The joint effects of …
recurrent neural network, are applied to traffic including DDoS attacks. The joint effects of …
Review of detection DDOS attack detection using naive bayes classifier for network forensics
Abstract Distributed Denial of Service (DDoS) is a type of attack using the volume, intensity,
and more costs mitigation to increase in this era. Attackers used many zombie computers to …
and more costs mitigation to increase in this era. Attackers used many zombie computers to …
Detection of DoS attacks using machine learning techniques
As the growth of IoT has been further reinforced by the advances, when used with other
technologies like embedded systems, hardware and software enhancements, networking …
technologies like embedded systems, hardware and software enhancements, networking …
The design of SDN based detection for distributed denial of service (DDoS) attack
MM Oo, S Kamolphiwong… - 2017 21st International …, 2017 - ieeexplore.ieee.org
Software Defined Networking (SDN) is the network architecture where the network control is
decoupled and separated from forwarding mechanism. It is more popular in enterprise …
decoupled and separated from forwarding mechanism. It is more popular in enterprise …
Neural networks for DDOS attack detection using an enhanced urban IoT dataset
We investigate the application of artificial intelligence to cybersecurity, to contribute to the
safe and secure growth of the internet of things (IoT). Specifically, we train and evaluate …
safe and secure growth of the internet of things (IoT). Specifically, we train and evaluate …
Large-scale urban iot activity data for ddos attack emulation
As IoT deployments grow in scale for applications such as smart cities, they face increasing
cyber-security threats. In particular, as evidenced by the famous Mirai incident and other …
cyber-security threats. In particular, as evidenced by the famous Mirai incident and other …
Evaluating the performance of various SVM kernel functions based on basic features extracted from KDDCUP'99 dataset by random forest method for detecting DDoS …
The main goal of Denial of Service (DoS) attack is to restrict authorized users from gaining
access to available services and resources or to prevent from processing the benign events …
access to available services and resources or to prevent from processing the benign events …