MF-Adaboost: LDoS attack detection based on multi-features and improved Adaboost

D Tang, L Tang, R Dai, J Chen, X Li… - Future Generation …, 2020 - Elsevier
A low-rate denial of service (LDoS) attack is a precise network attack that aims at reducing
the quality of the network service. Many networks do not have an effective mechanism for …

MF-CNN: A new approach for LDoS attack detection based on multi-feature fusion and CNN

D Tang, L Tang, W Shi, S Zhan, Q Yang - Mobile Networks and …, 2021 - Springer
Low-rate denial-of-service (LDoS) attack reduce the performance of network services by
periodically sending short-term and high-pulse packets. The behavior of LDoS attack is …

DDoS attacks detection using machine learning algorithms

Q Li, L Meng, Y Zhang, J Yan - … 2018, Shanghai, China, September 20–21 …, 2019 - Springer
A distributed denial-of-service (DDoS) attack is a malicious attempt to disrupt normal traffic of
a targeted server, service or network by overwhelming the target or its surrounding …

A DDoS attack detection method based on hybrid heterogeneous multiclassifier ensemble learning

B Jia, X Huang, R Liu, Y Ma - Journal of Electrical and …, 2017 - Wiley Online Library
The explosive growth of network traffic and its multitype on Internet have brought new and
severe challenges to DDoS attack detection. To get the higher True Negative Rate (TNR) …

Smart detection: an online approach for DoS/DDoS attack detection using machine learning

FS Lima Filho, FAF Silveira… - Security and …, 2019 - Wiley Online Library
Users and Internet service providers (ISPs) are constantly affected by denial‐of‐service
(DoS) attacks. This cyber threat continues to grow even with the development of new …

EIoT-DDoS: embedded classification approach for IoT traffic-based DDoS attacks

P Shukla, CR Krishna, NV Patil - Cluster Computing, 2024 - Springer
Abstract The Internet of Things (IoT) has shown incredible adaptability in recent years and
has become an integral part of human life. The proliferation of IoT technology has made IoT …

Effective and efficient DDoS attack detection using deep learning algorithm, multi-layer perceptron

S Ahmed, ZA Khan, SM Mohsin, S Latif, S Aslam… - Future Internet, 2023 - mdpi.com
Distributed denial of service (DDoS) attacks pose an increasing threat to businesses and
government agencies. They harm internet businesses, limit access to information and …

Detecting DDoS attacks using machine learning techniques and contemporary intrusion detection dataset

N Bindra, M Sood - Automatic Control and Computer Sciences, 2019 - Springer
Recent trends have revealed that DDoS attacks contribute to the majority of overall network
attacks. Networks face challenges in distinguishing between legitimate and malicious flows …

DDoS attack detection using MLP and Random Forest Algorithms

AA Najar, S Manohar Naik - International Journal of Information …, 2022 - Springer
Abstract Distributed Denial of Service (DDoS) attacks continue to be the most dangerous
over the Internet. With the rapid advancement of information and communication technology …

Network traffic behavioral analytics for detection of DDoS attacks

AD Lopez, AP Mohan, S Nair - SMU data science review, 2019 - scholar.smu.edu
As more organizations and businesses in different sectors are moving to a digital
transformation, there is a steady increase in malware, facing data theft or service …