A Method of Combining Multiple Experts for the Recognition of Unconstrained Handwritten Numerals
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Combining Pattern Classifiers: Methods and Algorithms
Combining Pattern Classifiers: Methods and Algorithms
Traffic classification on the fly
ACM SIGCOMM Computer Communication Review
ACM SIGCOMM Computer Communication Review
GA-Based Internet Traffic Classification Technique for QoS Provisioning
IIH-MSP '06 Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia
On Inferring Application Protocol Behaviors in Encrypted Network Traffic
The Journal of Machine Learning Research
Early application identification
CoNEXT '06 Proceedings of the 2006 ACM CoNEXT conference
Traffic classification using en-semble learning and co-training
AIC'08 Proceedings of the 8th conference on Applied informatics and communications
Internet traffic classification demystified: myths, caveats, and the best practices
CoNEXT '08 Proceedings of the 2008 ACM CoNEXT Conference
Information fusion for computer security: State of the art and open issues
Information Fusion
TIE: A Community-Oriented Traffic Classification Platform
TMA '09 Proceedings of the First International Workshop on Traffic Monitoring and Analysis
Early traffic classification using support vector machines
Proceedings of the 5th International Latin American Networking Conference
Machine learning based encrypted traffic classification: identifying SSH and skype
CISDA'09 Proceedings of the Second IEEE international conference on Computational intelligence for security and defense applications
Early recognition of encrypted applications
PAM'07 Proceedings of the 8th international conference on Passive and active network measurement
Better network traffic identification through the independent combination of techniques
Journal of Network and Computer Applications
K-dimensional trees for continuous traffic classification
TMA'10 Proceedings of the Second international conference on Traffic Monitoring and Analysis
A survey of techniques for internet traffic classification using machine learning
IEEE Communications Surveys & Tutorials
A Survey on Internet Traffic Identification
IEEE Communications Surveys & Tutorials
Information combination operators for data fusion: a comparative review with classification
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Bayesian Neural Networks for Internet Traffic Classification
IEEE Transactions on Neural Networks
Using a behaviour knowledge space approach for detecting unknown IP traffic flows
MCS'11 Proceedings of the 10th international conference on Multiple classifier systems
Reviewing traffic classification
DataTraffic Monitoring and Analysis
| Hi-index | 0.00 |
In thiswork we present and evaluate different automated combination techniques for traffic classification. We consider six intelligent combination algorithms applied to both traditional and more recent traffic classification techniques using either packet content or statistical properties of flows. Preliminary results show that, when selecting complementary classifiers, some combination algorithms allow a further improvement - in terms of classification accuracy - over already well-performing standalone classification techniques. Moreover, our experiments show that the positive impact of combination is particularly significant when there are early-classification constraints, that is, when the classification of a flow must be obtained in its early stage (e.g. first 1-4 packets) in order to perform network operations online.