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Investigating Two Different Approaches for Encrypted Traffic Classification

Riyad Alshammari, A. Nur Zincir-Heywood
2008 2008 Sixth Annual Conference on Privacy, Security and Trust  
The basic objective of this work is to compare the utility of an expert driven system and a data driven system for classifying encrypted network traffic, specifically SSH traffic from traffic log files  ...  Results show that the data driven system approach outperforms the expert driven system approach in terms of high detection and low false positive rates.  ...  Our thanks to John Sherwood, David Green and Dalhousie UCIS team for providing us the anonymozied Dalhousie traffic traces.  ... 
doi:10.1109/pst.2008.15 dblp:conf/pst/AlshammariZ08 fatcat:y3decntalnc57fkki7fnbtpegm

A Survey on Tor Encrypted Traffic Monitoring

Mohamad Amar Irsyad Mohd Aminuddin, Zarul Fitri, Manmeet Kaur, Darshan Singh
2018 International Journal of Advanced Computer Science and Applications  
This paper presents survey on existing approaches for classification of Tor and other encrypted traffic. There is preliminary discussion on machine learning approaches and Tor network.  ...  Therefore, numerous of research has been performed on encrypted traffic analyzing and classification using machine learning techniques.  ...  With the emerging traffic encryption and anonymity services such as Tor, machine learning technique for encrypted traffic classification should be considered as the prominent approaches on identifying  ... 
doi:10.14569/ijacsa.2018.090815 fatcat:wmjcrz4jojhzxmjv3a52sf4toe


A.Jenefa .
2015 International Journal of Research in Engineering and Technology  
for classifying the VoIP traffic flow with high accurate classification.  ...  Without investigate the packet payloads, our proposed Fine-Grained classifier effectively classifies the Peer-to-Peer encrypted traffic in the real time network.  ...  Fig 1 : 1 Different Learning approach demands an aforementioned knowledge to classify the Peer-to-Peer traffic flows.  ... 
doi:10.15623/ijret.2015.0403051 fatcat:flkf32jhw5ejdipxvu6lizwxke

Generalization of signatures for SSH encrypted traffic identification

Riyad Alshammari, Nur Zincir-Heywood
2009 2009 IEEE Symposium on Computational Intelligence in Cyber Security  
The objective of this work is to discover generalized signatures for identifying encrypted traffic where SSH is taken as an example application.  ...  We identified 13 signatures and 14 flow attributes for SSH traffic classification where IP addresses, source/destination ports and payload information are not employed.  ...  Our thanks to John Sherwood, David Green and Dalhosuie UCIS team for providing us the anonymozied Dalhousie traffic traces.  ... 
doi:10.1109/cicybs.2009.4925105 dblp:conf/cics/AlshammariZ09 fatcat:6phfovkryffmjguttpljq7eepu

Machine learning based encrypted traffic classification: Identifying SSH and Skype

Riyad Alshammari, A. Nur Zincir-Heywood
2009 2009 IEEE Symposium on Computational Intelligence for Security and Defense Applications  
The objective of this work is to assess the robustness of machine learning based traffic classification for classifying encrypted traffic where SSH and Skype are taken as good representatives of encrypted  ...  Results indicate the C4.5 based approach performs much better than other algorithms on the identification of both SSH and Skype traffic on totally different networks.  ...  Our thanks to John Sherwood, David Green and Dalhosuie UCIS team for providing us the anonymozied Dalhousie traffic traces.  ... 
doi:10.1109/cisda.2009.5356534 dblp:conf/cisda/AlshammariZ09 fatcat:oi7ch3u67vg7zj4jmxgsesofq4

A survey of methods for encrypted traffic classification and analysis

Petr Velan, Milan Čermák, Pavel Čeleda, Martin Drašar
2015 International Journal of Network Management  
In this paper, we survey existing approaches for classification and analysis of encrypted traffic. First, we describe the most widespread encryption protocols used throughout the Internet.  ...  To the best of our knowledge, this is the first work which comprehensively summarizes available approaches for encrypted traffic classification and analysis.  ...  In this paper we presented an overview of current approaches for the classification and analysis of encrypted traffic.  ... 
doi:10.1002/nem.1901 fatcat:k4ntvq6lyraq5elxrt2xzxz324

A multi-level framework to identify HTTPS services

Wazen M. Shbair, Thibault Cholez, Jerome Francois, Isabelle Chrisment
2016 NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium  
There is an essential need for new methods to investigate, with a proper level of identification, the increasing number of HTTPS traffic that may hold security breaches.  ...  The development of TLS-based encrypted traffic comes with new challenges related to the management and security analysis of encrypted traffic.  ...  To our knowledge, it is the first time such an approach has been applied to encrypted traffic classification problem.  ... 
doi:10.1109/noms.2016.7502818 dblp:conf/noms/ShbairCFC16 fatcat:po3jusgzpnff5fovjivgzokujq

Speaker recognition from encrypted VoIP communications

L.A. Khan, M.S. Baig, Amr M. Youssef
2010 Digital Investigation. The International Journal of Digital Forensics and Incident Response  
Most of the voice over IP (VoIP) traffic is encrypted prior to its transmission over the Internet.  ...  In this paper, we propose techniques for speaker identification and verification from encrypted VoIP conversations.  ...  Fig. 2 - 2 Overview of the proposed approach for speaker identification from encrypted VoIP communications.  ... 
doi:10.1016/j.diin.2009.10.001 fatcat:5qspukop4ff55lafnycnklolfa

Encrypted Network Traffic Classification Using Deep and Parallel Network-In-Network Models

Zhiyong Bu, Bin Zhou, Pengyu Cheng, Kecheng Zhang, Zhenhua Ling
2020 IEEE Access  
Although these two approaches can achieve high accuracy of traffic classification in some scenarios, they suffer from the popularity of encrypted data in current communication networks.  ...  Therefore, the machine learning approach to traffic classification, especially to encrypted traffic classification, has attracted more and more research attentions recently.  ... 
doi:10.1109/access.2020.3010637 fatcat:7lsexgsymvbythgpku2cl2xo7a

Detecting Encrypted Traffic: A Machine Learning Approach [chapter]

Seunghun Cha, Hyoungshick Kim
2017 Lecture Notes in Computer Science  
Detecting encrypted traffic is increasingly important for deep packet inspection (DPI) to improve the performance of intrusion detection systems.  ...  We propose a machine learning approach with several randomness tests to achieve high accuracy detection of encrypted traffic while requiring low overhead incurred by the detection procedure.  ...  Therefore, two different procedures could generally be used according to whether the inspected packets are encrypted or not.  ... 
doi:10.1007/978-3-319-56549-1_5 fatcat:dmces5xcmbd4tdgobb4bj6hife

Classifying SSH encrypted traffic with minimum packet header features using genetic programming

Riyad Alshammari, Peter I. Lichodzijewski, Malcolm Heywood, A. Nur Zincir-Heywood
2009 Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference - GECCO '09  
The classification of Encrypted Traffic, namely Secure Shell (SSH), on the fly from network TCP traffic represents a particularly challenging application domain for machine learning.  ...  Thus, in this work we have investigated the identification of SSH encrypted traffic based on packet header features without using IP addresses, port numbers and payload data.  ...  Our thanks to John Sherwood, David Green and Dalhousie UCIS team for providing us the anonymized University traffic traces.  ... 
doi:10.1145/1570256.1570358 dblp:conf/gecco/AlshammariLHZ09 fatcat:jlfsgtzk3jgz5eb4ddmutfgtxa

Mitigation of Privacy Threats due to Encrypted Traffic Analysis through a Policy-Based Framework and MUD Profiles

Gianmarco Baldini, José L. Hernandez-Ramos, Slawomir Nowak, Ricardo Neisse, Mateusz Nowak
2020 Symmetry  
This paper proposes a mitigation approach for privacy risks related to the analysis of encrypted traffic which is based on the integration of three main components: (1) A machine learning component which  ...  In particular, different types of traffic (e.g., skype, web access) can be identified by extracting time based features and using them in a classifier.  ...  Acknowledgments: We acknowledge the reviewers for taking their time to review the manuscript and to improve the quality of the publication.  ... 
doi:10.3390/sym12091576 fatcat:64t4gqfuibauto7n22teiqp6ve

Deep Learning for Encrypted Traffic Classification: An Overview

Shahbaz Rezaei, Xin Liu
2019 IEEE Communications Magazine  
With the proliferation of deep learning methods, researchers have recently investigated these methods for traffic classification task and reported high accuracy.  ...  Traffic classification has been studied for two decades and applied to a wide range of applications from QoS provisioning and billing in ISPs to security-related applications in firewalls and intrusion  ...  Stronger Encryption Protocols Traffic classification for stronger encryption protocols, in particular QUIC and TLS 1.3, has not been well investigated.  ... 
doi:10.1109/mcom.2019.1800819 fatcat:7jxq62uvsbfzljiv5mrgaqyy3q

Inferring users' online activities through traffic analysis

Fan Zhang, Wenbo He, Xue Liu, Patrick G. Bridges
2011 Proceedings of the fourth ACM conference on Wireless network security - WiSec '11  
Traffic analysis may threaten user privacy, even if the traffic is encrypted.  ...  Results show that our system can distinguish different online applications on the accuracy of about 80% in 5 seconds and over 90% accuracy if the eavesdropping lasts for 1 minute.  ...  Thus in this paper, we investigate traffic classification on encrypted traffic in the MAC layer.  ... 
doi:10.1145/1998412.1998425 dblp:conf/wisec/ZhangHLB11 fatcat:pbf3sbgwgrd2bd6v47qvwaythy

A framework to classify heterogeneous Internet traffic with Machine Learning and Deep Learning techniques for Satellite Communications

Fannia Pacheco, Ernesto Exposito, Mathieu Gineste
2020 Computer Networks  
The proposed classification system will deal with different Internet communications (encrypted, unencrypted, and tunneled).  ...  Following this idea, this work aims at finding new Internet traffic classification approaches to improving the QoS.  ...  We want to thank the Département : Business Line Telecommunication, R&D department, for their assistance.  ... 
doi:10.1016/j.comnet.2020.107213 fatcat:vpzxc6jg4bee5mxaetyk22rh4u
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