C4.5: programs for machine learning
C4.5: programs for machine learning
Empirically derived analytic models of wide-area TCP connections
IEEE/ACM Transactions on Networking (TON)
Wide area traffic: the failure of Poisson modeling
IEEE/ACM Transactions on Networking (TON)
Machine Learning
Machine Learning - Special issue on learning with probabilistic representations
Machine Learning
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Analyzing peer-to-peer traffic across large networks
Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment
Machine Learning
Measurement, modeling, and analysis of a peer-to-peer file-sharing workload
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
An analysis of Internet chat systems
Proceedings of the 3rd ACM SIGCOMM conference on Internet measurement
Accurate, scalable in-network identification of p2p traffic using application signatures
Proceedings of the 13th international conference on World Wide Web
The CoralReef Software Suite as a Tool for System and Network Administrators
LISA '01 Proceedings of the 15th USENIX conference on System administration
Internet traffic classification using bayesian analysis techniques
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
BLINC: multilevel traffic classification in the dark
Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
ACAS: automated construction of application signatures
Proceedings of the 2005 ACM SIGCOMM workshop on Mining network data
Automated Traffic Classification and Application Identification using Machine Learning
LCN '05 Proceedings of the The IEEE Conference on Local Computer Networks 30th Anniversary
Traffic classification on the fly
ACM SIGCOMM Computer Communication Review
Traffic classification using clustering algorithms
Proceedings of the 2006 SIGCOMM workshop on Mining network data
ACM SIGCOMM Computer Communication Review
Traffic classification through simple statistical fingerprinting
ACM SIGCOMM Computer Communication Review
A markovian signature-based approach to IP traffic classification
Proceedings of the 3rd annual ACM workshop on Mining network data
Towards Automatic Traffic Classification
ICNS '07 Proceedings of the Third International Conference on Networking and Services
Offline/realtime traffic classification using semi-supervised learning
Performance Evaluation
Network Traffic Classification Using K-means Clustering
IMSCCS '07 Proceedings of the Second International Multi-Symposiums on Computer and Computational Sciences
Early application identification
CoNEXT '06 Proceedings of the 2006 ACM CoNEXT conference
Early recognition of encrypted applications
PAM'07 Proceedings of the 8th international conference on Passive and active network measurement
Estimating continuous distributions in Bayesian classifiers
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Inferring users' online activities through traffic analysis
Proceedings of the fourth ACM conference on Wireless network security
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Online classification of network traffic is very challenging and still an issue to be solved due to the increase of new applications and traffic encryption. In this paper, we propose a hybrid mechanism for online classification of network traffic, in which we apply a signature-based method at the first level, and then we take advantage of a learning algorithm to classify the remaining unknown traffic using statistical features. Our evaluation with over 250 thousand flows collected over three consecutive hours on a large-scale ISP network shows promising results in detecting encrypted and tunneled applications compared to other existing methods.