DDoS Attack Detection Using Heuristics Clustering Algorithm and Naïve Bayes Classification

ISSN Print: 2153-1234
ISSN Online: 2153-1242
www.scirp.org/journal/jis
E-mail: jis@scirp.org

"DDoS Attack Detection Using Heuristics Clustering Algorithm and Naïve Bayes Classification"
written by Sharmila Bista, Roshan Chitrakar,
published by Journal of Information Security, Vol.9 No.1, 2018

has been cited by the following article(s):

[1]	Predictive machine learning-based integrated approach for DDoS detection and prevention
	Multimedia Tools and …, 2022

[2]	A detailed survey of denial of service for IoT and multimedia systems: Past, present and futuristic development
	Multimedia Tools and Applications, 2022

[3]	A Hybrid Modified Grasshopper Optimization Algorithm and Genetic Algorithm to Detect and Prevent DDoS Attacks
	2021

[4]	Identification of distributed denial of services anomalies by using combination of entropy and sequential probabilities ratio test methods
	Haddad, R Atan… - Sensors, 2021

[5]	F-STONE: A Fast Real-Time DDOS Attack Detection Method Using an Improved Historical Memory Management.
	2020

[6]	F-STONE: A Fast Real-Time DDOS Attack Detection Method Using an Improved Historical Memory Management
	2020

[7]	A review on statistical approaches for anomaly detection in DDoS attacks
	2020

[8]	Distributed Denial of Service Attacks: Real-world Detection and Mitigation
	2020

[9]	Fuzzy LSSVC-WKNN Combination Algorithm in Fault Diagnosis.
	Electrotehnica, Electronica …, 2020

[10]	Twin Security Model—A Machine Learning-Based Approach for DDoS Attack Detection in SDN
	2019

[11]	Performance Evaluation of Machine Learning Algorithms for Hypertext Transfer Protocol Distributed Denial of Service Intrusion Detection
	2019

[1]	A detailed survey of denial of service for IoT and multimedia systems: Past, present and futuristic development Multimedia Tools and Applications, 2022 DOI:10.1007/s11042-021-11859-z

[2]	An Efficient DDoS Attack Detecting System using Levenberg-Marquardt Based Deep Artificial Neural Network Approach for IOT International Journal of Innovative Technology and Exploring Engineering, 2021 DOI:10.35940/ijitee.C8356.0110321

[3]	A review on statistical approaches for anomaly detection in DDoS attacks Information Security Journal: A Global Perspective, 2020 DOI:10.1080/19393555.2020.1717019

[4]	Intelligent Computing, Information and Control Systems Advances in Intelligent Systems and Computing, 2020 DOI:10.1007/978-3-030-30465-2_73

[5]	Performance Evaluation of Machine Learning Algorithms for Hypertext Transfer Protocol Distributed Denial of Service Intrusion Detection 2019 15th International Conference on Electronics, Computer and Computation (ICECCO), 2019 DOI:10.1109/ICECCO48375.2019.9043262