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Machine Learning Based Classifier for Service Function Chains
- Source :
- COMPUTING AND INFORMATICS; Vol. 39 No. 3 (2020): Computing and Informatics; 410-438
- Publication Year :
- 2020
- Publisher :
- Central Library of the Slovak Academy of Sciences, 2020.
-
Abstract
- Using service function chains, Internet Service Providers can customize the use of service functions that process the network flows belonging to their customers. Each network flow is injected into a service chain according to the flow features. Since most of the malicious applications try not to get the proper analysis by imitating some valid and famous applications, classification based on simple flow features may waste processing power by using inappropriate service chains for evasive flows. In this paper, we have explored an application-aware classification approach using machine learning methods. Using CatBoost as a machine learning method, a model is created and used for traffic classification. We have provided some statistical reports on how this approach is compared with simple flow feature-based approaches in malicious environments and how feature selection can impact classification correctness. Choosing the most suitable number of features at the right time can beat traditional approaches in classification quality and provide better results in the service function chaining environment.
- Subjects :
- 68M10
Correctness
business.industry
Computer science
General Engineering
Feature selection
Machine learning
computer.software_genre
Flow network
Internet service provider
machine learning
Traffic classification
Chaining
Service function chaining
Artificial intelligence
catboost
business
computer
Classifier (UML)
classifier
Waste processing
Subjects
Details
- ISSN :
- 25858807 and 13359150
- Volume :
- 39
- Database :
- OpenAIRE
- Journal :
- Computing and Informatics
- Accession number :
- edsair.doi.dedup.....fdd4646ffc9a61273b55af886fbe69cb