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Entropy based features distribution for anti-DDoS model in SDN
Raja Majid Ali Ujjan
, Zeeshan Pervez
*
,
Keshav Dahal
, Wajahat Ali Khan
, Asad Masood Khattak
, Bashir Hayat
*
Corresponding author for this work
School of Computing, Engineering and Physical Sciences
Research output
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Contribution to journal
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Article
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peer-review
33
Citations (Scopus)
95
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Dive into the research topics of 'Entropy based features distribution for anti-DDoS model in SDN'. Together they form a unique fingerprint.
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Keyphrases
Service Model
100%
Software-defined Networking
100%
Distributed Denial of Service (DDoS)
100%
Feature Distribution
100%
Entropy Features
100%
Detection Accuracy
22%
Network Services
22%
Service Detection
22%
Legitimate User
22%
Deep Neural Network Classifier
22%
Stacked Auto-encoder Neural Network
22%
Signature-based
11%
Network Traffic
11%
Traffic Pattern
11%
Service Data
11%
Service Users
11%
Controller
11%
False-positive Results
11%
Network Infrastructure
11%
User Traffic
11%
Convolutional Neural Network
11%
Shannon Entropy
11%
High Traffic
11%
Traffic Volume
11%
Traffic Flow
11%
Snort
11%
Stacked Autoencoder
11%
Deep Learning Model
11%
Network Security
11%
Conventional Network
11%
Entropy Calculation
11%
Generalized Entropy
11%
Network Security Tools
11%
Rényi Entropy
11%
Entropy-based
11%
Modern Network
11%
Traffic Overhead
11%
Distributed Features
11%
Malicious Traffic
11%
False Positive Alerts
11%
Computer Science
Software Defined Networking
100%
Service Model
100%
Distributed Denial of Service Attack
100%
Convolutional Neural Network
33%
Detection Accuracy
22%
Network Service
22%
False Positive
22%
Service Detection
22%
Network Security
22%
Legitimate User
22%
Service Traffic
22%
Collected Data
11%
Network Traffic
11%
Traffic Pattern
11%
Network Infrastructure
11%
Average Accuracy
11%
Deep Learning Model
11%
Data Services
11%
Targeted Network
11%