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Application layer DDoS attack detection using cluster with label based on sparse vector decomposition and rhythm matching

https://doi.org/10.1002/sec.1236
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-1-4614-9491-1_3openalex-snapshot
DDoS Attack Detection
inferredcites →https://doi.org/10.1016/j.asoc.2012.08.028openalex-snapshot
Detection of malicious and non-malicious website visitors using unsupervised neural network learning
inferredcites →https://doi.org/10.1016/j.comcom.2011.01.012openalex-snapshot
Distributed denial of service attack detection using an ensemble of neural classifier
inferredcites →https://doi.org/10.1016/j.comnet.2012.07.003openalex-snapshot
Flow level detection and filtering of low-rate DDoS
inferredcites →https://doi.org/10.1016/j.future.2013.08.002openalex-snapshot
Detection and defense of application-layer DDoS attacks in backbone web traffic
inferredcites →https://doi.org/10.1016/j.sysarc.2013.08.008openalex-snapshot
An in-depth analysis on traffic flooding attacks detection and system using data mining techniques
inferredcites →https://doi.org/10.1109/glocom.2011.6133798openalex-snapshot
Web DDoS Detection Schemes Based on Measuring User's Access Behavior with Large Deviation
inferredcites →https://doi.org/10.1109/icrtit.2011.5972281openalex-snapshot
Real time detection and classification of DDoS attacks using enhanced SVM with string kernels
inferredcites →https://doi.org/10.1109/msecp.2003.1219056openalex-snapshot
Inside the Slammer worm
inferredcites →https://doi.org/10.1109/tnet.2008.923716openalex-snapshot
A Large-Scale Hidden Semi-Markov Model for Anomaly Detection on User Browsing Behaviors
inferredcites →https://doi.org/10.1109/tnet.2008.925628openalex-snapshot
Monitoring the Application-Layer DDoS Attacks for Popular Websites
inferredcites →https://doi.org/10.1109/tpds.2011.262openalex-snapshot
Discriminating DDoS Attacks from Flash Crowds Using Flow Correlation Coefficient
inferredcites →https://doi.org/10.1109/tsmca.2006.889480openalex-snapshot
Covariance-Matrix Modeling and Detecting Various Flooding Attacks
inferredcites →https://doi.org/10.1145/511446.511485openalex-snapshot
Flash crowds and denial of service attacks
inferredcites →https://doi.org/10.1145/511483.511485openalex-snapshot
Flash crowds and denial of service attacks
inferredcites →https://doi.org/10.1145/966389.966390openalex-snapshot
Telling humans and computers apart automatically
inferredcites →https://doi.org/10.1155/2009/837601openalex-snapshot
Network Anomaly Detection Based on Wavelet Analysis

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/dac.4603openalex-snapshot
A survey and meta‐analysis of application‐layer distributed denial‐of‐service attack
inferred← citeshttps://doi.org/10.1002/ett.3187openalex-snapshot
ReCAP: A distributed CAPTCHA service at the edge of the network to handle server overload
inferred← citeshttps://doi.org/10.1007/978-3-030-15032-7_103openalex-snapshot
Implicit and Continuous Authentication of Smart Home Users
inferred← citeshttps://doi.org/10.1007/978-3-030-30577-2_82openalex-snapshot
Critical Investigation on Application Layer-DDoS Attacks: Taxonomy and Parameter Efficacy
inferred← citeshttps://doi.org/10.1007/978-3-030-78375-4_14openalex-snapshot
Defending Web Servers Against Flash Crowd Attacks
inferred← citeshttps://doi.org/10.1007/978-981-16-3097-2_1openalex-snapshot
Application Layer DDOS Attack Detection and Defense Methods
inferred← citeshttps://doi.org/10.1007/978-981-16-9705-0_28openalex-snapshot
A Hybrid Model for DDoS Attack Detection Using LSTM-RNN
inferred← citeshttps://doi.org/10.1007/978-981-19-8136-4_19openalex-snapshot
DDoS Attack Detection Using Artificial Neural Network on IoT Devices in a Simulated Environment
inferred← citeshttps://doi.org/10.1007/978-981-33-4893-6_56openalex-snapshot
Threat Detection on UDP Protocols Using Packet Rates in IoT
inferred← citeshttps://doi.org/10.1007/s10015-019-00527-zopenalex-snapshot
Use of access characteristics to distinguish legitimate user traffic from DDoS attack traffic
inferred← citeshttps://doi.org/10.1007/s10207-021-00571-6openalex-snapshot
Anomalous behavior detection-based approach for authenticating smart home system users
inferred← citeshttps://doi.org/10.1007/s11277-021-08556-3openalex-snapshot
Shield Techniques for Application Layer DDoS Attack in MANET: A Methodological Review
inferred← citeshttps://doi.org/10.1007/s13369-017-2414-5openalex-snapshot
DDoS Attack Detection and Mitigation Using SDN: Methods, Practices, and Solutions
inferred← citeshttps://doi.org/10.1016/j.comcom.2017.02.003openalex-snapshot
Detection of DDoS attacks and flash events using information theory metrics–An empirical investigation
inferred← citeshttps://doi.org/10.1016/j.comnet.2019.106906openalex-snapshot
On the performance of intelligent techniques for intensive and stealthy DDos detection
inferred← citeshttps://doi.org/10.1016/j.cosrev.2017.07.003openalex-snapshot
Characterizing DDoS attacks and flash events: Review, research gaps and future directions
inferred← citeshttps://doi.org/10.1016/j.jisa.2015.11.001openalex-snapshot
A comprehensive approach to discriminate DDoS attacks from flash events
inferred← citeshttps://doi.org/10.1016/j.jisa.2021.103090openalex-snapshot
HTTP request pattern based signatures for early application layer DDoS detection: A firewall agnostic approach
inferred← citeshttps://doi.org/10.1016/j.jnca.2018.03.030openalex-snapshot
User behavior analytics-based classification of application layer HTTP-GET flood attacks
inferred← citeshttps://doi.org/10.1016/j.procs.2018.10.337openalex-snapshot
Burst Header Packet Flood Detection in Optical Burst Switching Network Using Deep Learning Model
inferred← citeshttps://doi.org/10.1109/access.2021.3110586openalex-snapshot
Mathematical Approach as Qualitative Metrics of Distributed Denial of Service Attack Detection Mechanisms
inferred← citeshttps://doi.org/10.1109/access.2024.3361476openalex-snapshot
Improving Quality of Service and HTTPS DDoS Detection in MEC Environment With a Cyber Deception-Based Architecture
inferred← citeshttps://doi.org/10.1109/access.2026.3730464openalex-snapshot
Cross-Protocol DDoS Detection via HTTP/2 Stream Reconstruction: A Multiplexing-Aware Traffic Transformation Approach
inferred← citeshttps://doi.org/10.1109/cloudtech.2017.8284731openalex-snapshot
DDoS attack detection using machine learning techniques in cloud computing environments
inferred← citeshttps://doi.org/10.1109/comnet47917.2020.9306081openalex-snapshot
Securing Smart Homes using a Behavior Analysis based Authentication Approach
inferred← citeshttps://doi.org/10.1109/comst.2018.2863942openalex-snapshot
Security Data Collection and Data Analytics in the Internet: A Survey
inferred← citeshttps://doi.org/10.1109/comst.2018.2867288openalex-snapshot
Security and Privacy of Smart Cities: A Survey, Research Issues and Challenges
inferred← citeshttps://doi.org/10.1109/hpcc/smartcity/dss.2018.00224openalex-snapshot
Security and Privacy of Smart Cities: Issues and Challenge
inferred← citeshttps://doi.org/10.1109/icbds61829.2024.10837482openalex-snapshot
Implementation of QOS in SDN and Distributed Networks for mitigation of DDOS based attacks using Machine Learning
inferred← citeshttps://doi.org/10.1109/iccci56745.2023.10128499openalex-snapshot
BDDoS: Blocking Distributed Denial of Service Flooding Attacks With Dynamic Path Detectors
inferred← citeshttps://doi.org/10.1109/icnp.2019.8888105openalex-snapshot
Defending Web Servers Against Flash Crowd Attacks
inferred← citeshttps://doi.org/10.1109/infocomwkshps54753.2022.9798301openalex-snapshot
Identifying DDoS Attack using Split-Machine Learning System in 5G and Beyond Networks
inferred← citeshttps://doi.org/10.1109/innovations.2018.8605972openalex-snapshot
Defense Analysis Against Store and Forward Distributed Reflective Denial of Service Attacks
inferred← citeshttps://doi.org/10.1109/iri.2017.44openalex-snapshot
User Behavior Anomaly Detection for Application Layer DDoS Attacks
inferred← citeshttps://doi.org/10.1109/isci62787.2024.10668039openalex-snapshot
Enhancing Detection and Prediction of DDoS Attacks Through Regression Modeling
inferred← citeshttps://doi.org/10.1109/ispa-bdcloud-sustaincom-socialcom48970.2019.00133openalex-snapshot
IAP-Based Self-Learning Real-Time Application Layer DDoS Detection Method on Storm Platform
inferred← citeshttps://doi.org/10.1109/signass67826.2026.11479956openalex-snapshot
Simulation-Based Cybersecurity Assessment of DDoS Attack Impacts on Web Server Performance Using OMNeT++
inferred← citeshttps://doi.org/10.1109/smarttech54121.2022.00029openalex-snapshot
A User Behavior Analytics (UBA)- based solution using LSTM Neural Network to mitigate DDoS Attack in Fog and Cloud Environment
inferred← citeshttps://doi.org/10.1155/2018/1263123openalex-snapshot
Detection System of HTTP DDoS Attacks in a Cloud Environment Based on Information Theoretic Entropy and Random Forest
inferred← citeshttps://doi.org/10.1155/2019/1283472openalex-snapshot
Review of Recent Detection Methods for HTTP DDoS Attack
inferred← citeshttps://doi.org/10.1155/2020/8840058openalex-snapshot
An Efficient and Effective Approach for Flooding Attack Detection in Optical Burst Switching Networks
inferred← citeshttps://doi.org/10.1166/jctn.2020.9317openalex-snapshot
An Enhanced Way of Distributed Denial of Service Attack Detection by Applying Machine Learning Algorithms in Cloud Computing
inferred← citeshttps://doi.org/10.1504/ijiei.2017.10003432openalex-snapshot
Impact analysis of application layer DDoS attacks on web services: a simulation study
inferred← citeshttps://doi.org/10.21833/ijaas.2022.02.012openalex-snapshot
Deep learning model for distributed denial of service (DDoS) detection
inferred← citeshttps://doi.org/10.30534/ijatcse/2019/86842019openalex-snapshot
Enhanced Detection Algorithms to Detect HTTP DDoS
inferred← citeshttps://doi.org/10.3390/proceedings2020063051openalex-snapshot
A Machine Learning Approach for DDoS (Distributed Denial of Service) Attack Detection Using Multiple Linear Regression
inferred← citeshttps://doi.org/10.3390/s20143820openalex-snapshot
Recent Analysis of Forged Request Headers Constituted by HTTP DDoS
inferred← citeshttps://doi.org/10.4018/978-1-7998-5348-0.ch015openalex-snapshot
Performance Evaluation of Web Server's Request Queue against AL-DDoS Attacks in NS-2
inferred← citeshttps://doi.org/10.4018/ijcwt.2021100102openalex-snapshot
Improving Discriminating Accuracy Rate of DDoS Attacks and Flash Events
inferred← citeshttps://doi.org/10.4018/ijisp.2017100103openalex-snapshot
Performance Evaluation of Web Server's Request Queue against AL-DDoS Attacks in NS-2
inferred← citeshttps://doi.org/10.5120/ijca2019918900openalex-snapshot
DDoS Attack Detection using Predictive Models
inferred← citeshttps://doi.org/10.5815/ijisa.2018.04.04openalex-snapshot
Fuzzy-based User Behavior Characterization to Detect HTTP-GET Flood Attacks
inferred← citeshttps://doi.org/10.5815/ijwmt.2019.01.06openalex-snapshot
DDoS Attack Detection Using C5.0 Machine Learning Algorithm
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