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On the performance of intelligent techniques for intensive and stealthy DDos detection

https://doi.org/10.1016/j.comnet.2019.106906

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What this work says

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

inferredcites →https://doi.org/10.1002/9780470061626.shm055openalex-snapshot

Artificial Neural Networks

inferredcites →https://doi.org/10.1002/sec.1236openalex-snapshot

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

inferredcites →https://doi.org/10.1007/3-540-44673-7_8openalex-snapshot

Pattern Recognition and Neural Networks

inferredcites →https://doi.org/10.1007/bf00994018openalex-snapshot

Support-Vector Networks

inferredcites →https://doi.org/10.1007/s13748-016-0094-0openalex-snapshot

Learning from imbalanced data: open challenges and future directions

inferredcites →https://doi.org/10.1016/b978-0-12-411474-6.00018-9openalex-snapshot

Real-time Network Intrusion Detection Using Hadoop-Based Bayesian Classifier

inferredcites →https://doi.org/10.1016/c2012-0-07222-5openalex-snapshot

Emerging Trends in ICT Security

inferredcites →https://doi.org/10.1016/j.asoc.2007.02.016openalex-snapshot

Compiling network traffic into rules using soft computing methods for the detection of flooding attacks

inferredcites →https://doi.org/10.1016/j.asoc.2009.06.019openalex-snapshot

The use of computational intelligence in intrusion detection systems: A review

inferredcites →https://doi.org/10.1016/j.comcom.2008.09.018openalex-snapshot

Traffic flooding attack detection with SNMP MIB using SVM

inferredcites →https://doi.org/10.1016/j.comcom.2010.04.007openalex-snapshot

Clustering botnet communication traffic based on n-gram feature selection

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.comcom.2012.04.008openalex-snapshot

Analyzing well-known countermeasures against distributed denial of service attacks

inferredcites →https://doi.org/10.1016/j.comcom.2015.06.012openalex-snapshot

Detecting DDoS attacks against data center with correlation analysis

inferredcites →https://doi.org/10.1016/j.comcom.2017.03.010openalex-snapshot

DDoS attacks in cloud computing: Issues, taxonomy, and future directions

inferredcites →https://doi.org/10.1016/j.compeleceng.2016.01.012openalex-snapshot

Botnet detection via mining of traffic flow characteristics

inferredcites →https://doi.org/10.1016/j.cose.2008.08.003openalex-snapshot

Anomaly-based network intrusion detection: Techniques, systems and challenges

inferredcites →https://doi.org/10.1016/j.cose.2013.04.007openalex-snapshot

Botnet detection based on traffic behavior analysis and flow intervals

inferredcites →https://doi.org/10.1016/j.eswa.2010.08.137openalex-snapshot

Real-time anomaly detection systems for Denial-of-Service attacks by weighted k-nearest-neighbor classifiers

inferredcites →https://doi.org/10.1016/j.ins.2014.03.066openalex-snapshot

Big Data Analytics framework for Peer-to-Peer Botnet detection using Random Forests

inferredcites →https://doi.org/10.1016/j.jnca.2015.11.016openalex-snapshot

A survey of network anomaly detection techniques

inferredcites →https://doi.org/10.1016/j.jnca.2016.01.001openalex-snapshot

Distributed denial of service (DDoS) resilience in cloud: Review and conceptual cloud DDoS mitigation framework

inferredcites →https://doi.org/10.1016/j.neucom.2015.04.101openalex-snapshot

Detection of known and unknown DDoS attacks using Artificial Neural Networks

inferredcites →https://doi.org/10.1016/s0031-3203(96)00142-2openalex-snapshot

The use of the area under the ROC curve in the evaluation of machine learning algorithms

inferredcites →https://doi.org/10.1017/cbo9780511812651openalex-snapshot

Pattern Recognition and Neural Networks

inferredcites →https://doi.org/10.1023/a:1009744630224openalex-snapshot

Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Survey

inferredcites →https://doi.org/10.1093/comjnl/bxt031openalex-snapshot

Detecting Distributed Denial of Service Attacks: Methods, Tools and Future Directions

inferredcites →https://doi.org/10.1109/asiajcis.2014.23openalex-snapshot

Detection of DDoS Backscatter Based on Traffic Features of Darknet TCP Packets

inferredcites →https://doi.org/10.1109/cics14697.2009openalex-snapshot

2009 IEEE Symposium on Computational Intelligence in Cyber Security

inferredcites →https://doi.org/10.1109/cicybs.2014.7013367openalex-snapshot

Supervised learning to detect DDoS attacks

inferredcites →https://doi.org/10.1109/cis.2007.117openalex-snapshot

A Biometric Verification System Addressing Privacy Concerns

inferredcites →https://doi.org/10.1109/cnsr.2009.21openalex-snapshot

BotCop: An Online Botnet Traffic Classifier

inferredcites →https://doi.org/10.1109/compsac.2008.213openalex-snapshot

A Naive Bayes Approach for Detecting Coordinated Attacks

inferredcites →https://doi.org/10.1109/comsnets.2011.5716474openalex-snapshot

A system approach to network modeling for DDoS detection using a Na

inferredcites →https://doi.org/10.1109/comst.2015.2487361openalex-snapshot

Software-Defined Networking (SDN) and Distributed Denial of Service (DDoS) Attacks in Cloud Computing Environments: A Survey, Some Research Issues, and Challenges

inferredcites →https://doi.org/10.1109/comst.2015.2494502openalex-snapshot

A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection

inferredcites →https://doi.org/10.1109/crisis.2008.4757464openalex-snapshot

Efficient detection of DDoS attacks with important attributes

inferredcites →https://doi.org/10.1109/globecom18177.2014openalex-snapshot

2014 IEEE Global Communications Conference

inferredcites →https://doi.org/10.1109/glocom.2017.8254023openalex-snapshot

FADM: DDoS Flooding Attack Detection and Mitigation System in Software-Defined Networking

inferredcites →https://doi.org/10.1109/hpcc-css-icess.2015.38openalex-snapshot

A Neural-Network Based DDoS Detection System Using Hadoop and HBase

inferredcites →https://doi.org/10.1109/icacci.2017.8126031openalex-snapshot

Detection of distributed denial of service attacks using machine learning algorithms in software defined networks

inferredcites →https://doi.org/10.1109/icasi.2016.7539833openalex-snapshot

Detection DDoS attacks based on neural-network using Apache Spark

inferredcites →https://doi.org/10.1109/iccasm.2010.5622759openalex-snapshot

Detecting DDoS attacks using conditional entropy

inferredcites →https://doi.org/10.1109/iccias.2006.294075openalex-snapshot

2006 International Conference on Computational Intelligence and Security

inferredcites →https://doi.org/10.1109/iccubea.2015.60openalex-snapshot

Detection of DoS/DDoS Attack against HTTP Servers Using Naive Bayesian

inferredcites →https://doi.org/10.1109/iccubea34886.2015openalex-snapshot

2015 International Conference on Computing Communication Control and Automation

inferredcites →https://doi.org/10.1109/icnp.1993.340908openalex-snapshot

1993 International Conference on Network Protocols

inferredcites →https://doi.org/10.1109/icnp.2002.1181418openalex-snapshot

Attacking DDoS at the source

inferredcites →https://doi.org/10.1109/icns.2007.5openalex-snapshot

A Detection and Offense Mechanism to Defend Against Application Layer DDoS Attacks

inferredcites →https://doi.org/10.1109/icoac.2014.7229711openalex-snapshot

DDoS detection and analysis in SDN-based environment using support vector machine classifier

inferredcites →https://doi.org/10.1109/ijcnn.2016.7727577openalex-snapshot

A neural network model for detecting DDoS attacks using darknet traffic features

inferredcites →https://doi.org/10.1109/incos.2009.34openalex-snapshot

DDoS Attack Detection Using IP Address Feature Interaction

inferredcites →https://doi.org/10.1109/incos16242.2009openalex-snapshot

2009 International Conference on Intelligent Networking and Collaborative Systems

inferredcites →https://doi.org/10.1109/isac.2010.5670479openalex-snapshot

DDoS attack detection based on neural network

inferredcites →https://doi.org/10.1109/jsac.2018.2815442openalex-snapshot

Privacy-Preserving DDoS Attack Detection Using Cross-Domain Traffic in Software Defined Networks

inferredcites →https://doi.org/10.1109/ms.2011.67openalex-snapshot

Usenix Security Symposium

inferredcites →https://doi.org/10.1109/noms.2016.7502971openalex-snapshot

A classification approach for adaptive mitigation of SYN flood attacks: Preventing performance loss due to SYN flood attacks

inferredcites →https://doi.org/10.1109/nss.2010.70openalex-snapshot

Adaptive Clustering with Feature Ranking for DDoS Attacks Detection

inferredcites →https://doi.org/10.1109/surv.2013.031413.00127openalex-snapshot

A Survey of Defense Mechanisms Against Distributed Denial of Service (DDoS) Flooding Attacks

inferredcites →https://doi.org/10.1109/surv.2013.052213.00046openalex-snapshot

Network Anomaly Detection: Methods, Systems and Tools

inferredcites →https://doi.org/10.1109/telfor.2016.7818791openalex-snapshot

Artificial neuron network implementation in detection and classification of DDoS traffic

inferredcites →https://doi.org/10.1109/tnn.2010.2063350openalex-snapshot

2011 International Joint Conference on Neural Networks

inferredcites →https://doi.org/10.1109/tsp.2016.7760838openalex-snapshot

Frequency based DDoS attack detection approach using naive Bayes classification

inferredcites →https://doi.org/10.1145/1216370.1216373openalex-snapshot

Survey of network-based defense mechanisms countering the DoS and DDoS problems

inferredcites →https://doi.org/10.1145/1626195.1626252openalex-snapshot

Application of artificial neural network in detection of DOS attacks

inferredcites →https://doi.org/10.1145/2345396.2345500openalex-snapshot

Layered approach for intrusion detection using naïve Bayes classifier

inferredcites →https://doi.org/10.1145/2393216.2393249openalex-snapshot

A DDoS attack detection mechanism based on protocol specific traffic features

inferredcites →https://doi.org/10.1145/3058060.3058074openalex-snapshot

FL-GUARD

inferredcites →https://doi.org/10.1145/997150.997156openalex-snapshot

A taxonomy of DDoS attack and DDoS defense mechanisms

inferredcites →https://doi.org/10.1186/s13638-016-0623-3openalex-snapshot

Ensemble-based multi-filter feature selection method for DDoS detection in cloud computing

inferredcites →https://doi.org/10.1201/9781315373515openalex-snapshot

Data Clustering

inferredcites →https://doi.org/10.1201/9781482281767-9openalex-snapshot

Artificial Neural Networks

inferredcites →https://doi.org/10.1201/b15288-3openalex-snapshot

Naïve Bayes Classifier

inferredcites →https://doi.org/10.1504/ijahuc.2011.038998openalex-snapshot

DDoS detection and traceback with decision tree and grey relational analysis

inferredcites →https://doi.org/10.17487/rfc3954openalex-snapshot

Cisco Systems NetFlow Services Export Version 9

inferredcites →https://doi.org/10.3390/e18100350openalex-snapshot

Entropy-Based Application Layer DDoS Attack Detection Using Artificial Neural Networks

inferredcites →https://doi.org/10.4230/lipics.esem.2026.21openalex-snapshot

Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation

inferredcites →https://doi.org/10.5121/ijnsa.2010.2202openalex-snapshot

Combining Naive Bayes and Decision Tree for Adaptive Intrusion Detection

inferredcites →https://doi.org/10.5281/zenodo.1072907openalex-snapshot

Proactive Detection Of Ddos Attacks Utilizing K-Nn Classifier In An Anti-Ddos Framework

inferredcites →https://doi.org/10.5281/zenodo.1099003openalex-snapshot

Predicting Application Layer Ddos Attacks Using Machine Learning Algorithms

inferredcites →https://doi.org/10.6633/ijns.201203.14(2).01openalex-snapshot

ANN Based Scheme to Predict Number of Zombies in a DDoS Attack

What points at this work

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

inferred← citeshttps://doi.org/10.1007/978-3-032-16469-8_24openalex-snapshot

Detection and Mitigation of DDoS Attacks on SDN Controller in IoT Network Using Gini Impurity

inferred← citeshttps://doi.org/10.1007/978-981-99-4071-4_49openalex-snapshot

Machine Learning-Based Detection for Distributed Denial of Service Attack in IoT

inferred← citeshttps://doi.org/10.1007/s11227-020-03323-wopenalex-snapshot

The DDoS attacks detection through machine learning and statistical methods in SDN

inferred← citeshttps://doi.org/10.1007/s42979-024-02938-7openalex-snapshot

An Enhanced DDoS Attack Detection in Software-Defined-Networks using Ensemble Learning

inferred← citeshttps://doi.org/10.1016/j.comnet.2020.107792openalex-snapshot

Detection of reduction-of-quality DDoS attacks using Fuzzy Logic and machine learning algorithms

inferred← citeshttps://doi.org/10.1016/j.eswa.2020.114520openalex-snapshot

Detection of DDoS attacks with feed forward based deep neural network model

inferred← citeshttps://doi.org/10.1080/01969722.2023.2175140openalex-snapshot

An Efficient DDoS Attack Detection Using Chaos Henry Gas Solubility Optimization Weight Initialization Based Rectified Linear Unit

inferred← citeshttps://doi.org/10.1109/tnet.2024.3408675openalex-snapshot

Correlation-Aware Neural Networks for DDoS Attack Detection in IoT Systems

inferred← citeshttps://doi.org/10.14569/ijacsa.2021.0120517openalex-snapshot

Predicting DOS-DDOS Attacks: Review and Evaluation Study of Feature Selection Methods based on Wrapper Process

inferred← citeshttps://doi.org/10.21015/vtse.v8i1.580openalex-snapshot

A Survey of DDoS Attack Detection Strategies in Cloud

inferred← citeshttps://doi.org/10.30865/mib.v5i3.2979openalex-snapshot

Analisa dan Implementasi Sistem Keamanan Router Mikrotik dari Serangan Winbox Exploitation, Brute-Force, DoS

inferred← citeshttps://doi.org/10.31436/iiumej.v23i1.1789openalex-snapshot

BOTNET DETECTION USING INDEPENDENT COMPONENT ANALYSIS

inferred← citeshttps://doi.org/10.36227/techrxiv.19642977openalex-snapshot

A Futuristic Survey on Learning Techniques for Internet of Things (IoT) Security : Developments, Applications, and Challenges

inferred← citeshttps://doi.org/10.36227/techrxiv.19642977.v1openalex-snapshot

A Futuristic Survey on Learning Techniques for Internet of Things (IoT) Security : Developments, Applications, and Challenges

inferred← citeshttps://doi.org/10.37034/jsisfotek.v2i4.32openalex-snapshot

Peningkatan Keamanan Router Mikrotik Terhadap Serangan Denial of Service (DoS)

inferred← citeshttps://doi.org/10.37034/jsisfotek.v2i4.81openalex-snapshot

Peningkatan Keamanan Router Mikrotik Terhadap Serangan Denial of Service (DoS)

inferred← citeshttps://doi.org/10.48550/arxiv.2007.13233openalex-snapshot

Cyber Threat Intelligence for Secure Smart City

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