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VoIP Traffic Detection in Tunnelled and Anonymous Networks Using Deep Learning

Faiz Ul Islam, Guangjie Liu, Jiangtao Zhai, Weiwei Liu
2021 IEEE Access  
[54] PPTP and IPsec encrypted network traffic flows (Packet headers) 29 network traffic attributes UF Classifying of encryption type via C4.5, and application identification via SVM IPsec  ...  The Deep packet scheme achieved 0.94 recall in the classification of major traffic classes and 0.98 in the network traffic application identification. Klenilmar et al.  ... 
doi:10.1109/access.2021.3073967 fatcat:rdeatf6ghrgbhjkg5th4p4aqte

Device Type Identification via Network Traffic and Lightweight Convolutional Neural Network for Internet of Things

Guangwei Qing, Huifang Wang, Liang Guo, Jie Yang
2020 IEEE Access  
INDEX TERMS Lightweight convolutional neural network, network traffic, device type identification (DTI), Internet of Things (IoT).  ...  Recently, deep learning (DL) has been considered as a powerful tools for classification or identification, and some researches have introduced DL into DTI for advanced performance.  ...  DTI VIA NETWORK TRAFFIC There are lots of researches about network traffic-based DTI via machine learning (ML) and DL. Y.  ... 
doi:10.1109/access.2020.3032469 fatcat:766vpwo5nbhgznmtkp77fglpuy

Deep Packet: A Novel Approach For Encrypted Traffic Classification Using Deep Learning [article]

Mohammad Lotfollahi, Ramin Shirali Hossein Zade, Mahdi Jafari Siavoshani, Mohammdsadegh Saberian
2018 arXiv   pre-print
Internet traffic classification has become more important with rapid growth of current Internet network and online applications.  ...  Deep packet with CNN as its classification model achieved recall of 0.98 in application identification task and 0.94 in traffic categorization task.  ...  The identification of this kind of applications is one of the most challenging task in network traffic classification.  ... 
arXiv:1709.02656v3 fatcat:bpc2ndwlbbhsrapvrazkkdmxfi

SDN-Enabled FiWi-IoT Smart Environment Network Traffic Classification Using Supervised ML Models

Elaiyasuriyan Ganesan, I-Shyan Hwang, Andrew Tanny Liem, Mohammad Syuhaimi Ab-Rahman
2021 Photonics  
This paper, we propose a machine learning supervised network traffic classification scheduling model in SDN enhanced-FiWi-IoT that can intelligently learn and guarantee traffic based on its QoS requirements  ...  We capture the different IoT and non-IoT device network traffic trace files based on the traffic flow and analyze the traffic traces to extract statistical attributes (port source and destination, IP address  ...  network traffic flow in SDN, device classification in IoT and network traffic analysis.  ... 
doi:10.3390/photonics8060201 fatcat:xte7aviqrzdkrntp6mkgeq3qma

Toward the Accurate Identification of Network Applications [chapter]

Andrew W. Moore, Konstantina Papagiannaki
2005 Lecture Notes in Computer Science  
One consequence of this is that a simple inspection of the port numbers used by flows may lead to the inaccurate classification of network traffic.  ...  Well-known port numbers can no longer be used to reliably identify network applications.  ...  Lastly, in future work we intend to address the issue of how much information needs to be accessible by a traffic classifier for the identification of different network applications.  ... 
doi:10.1007/978-3-540-31966-5_4 fatcat:n56j6a3rjnfpfjjfknw3hzkxpa

Classification of Network Traffic via Packet-Level Hidden Markov Models

Alberto Dainotti, Walter de Donato, Antonio Pescape, Pierluigi Salvo Rossi
2008 IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference  
Traffic classification and identification is a fertile research area.  ...  Beyond Quality of Service, service differentiation, and billing, one of the most important applications of traffic classification is in the field of network security.  ...  of different applications; (ii) the ability to classify encrypted traffic; (iii) the identification of malicious traffic flows.  ... 
doi:10.1109/glocom.2008.ecp.412 dblp:conf/globecom/DainottiDPR08 fatcat:7txebyuffba65fqoto2ze2nywm

İnşaat Mühendisliğinde Derin Öğrenme Algoritmalarının Değerlendirilmesi ve Uygulanması

Melda ALKAN ÇAKIROĞLU, Ahmet Ali SÜZEN
2020 El-Cezeri: Journal of Science and Engineering  
As a result, infrastructure inspection, damage assessment and object identification applications via field images have produced successful results in civil engineering thanks to CNN deep neural network  ...  The algorithm is widely used algorithm in deep learning, especially in classification and detection / identification applications.  ... 
doi:10.31202/ecjse.679113 fatcat:5buojg4dsfadtjy4xzvlwogmhi

Proposal of Machine Learning Approach for Identification of Instant Messaging

Abdurrahman Pektas
2018 International Journal of Intelligent Systems and Applications in Engineering  
Therefore, classification of encrypted network traffic is mandatory for ensuring security.  ...  Identification of Internet protocol from either raw network traffic or either network flows plays a crucial role at maintaining and improving the security of computer systems.  ...  In [13] , WhatsApp voice calls are characterize via blind traffic detection in order to discriminate WhatsApp calls from other network applications.  ... 
doi:10.18201/ijisae.2018642060 fatcat:izkmexhb4ng6hdkh4oamgvgrry

Signatures of Viber Security Traffic

M.A.K. Sudozai, N. Habib, S. Saleem, A.A. Khan
2017 Journal of Digital Forensics, Security and Law  
In this paper, we present a novel methodology of identification of Viber traffic over the network and established a model which can classify its services of audio and audio/video calls, message chats including  ...  Our findings on Viber traffic signatures are applicable to most recent version of Viber 6.2.2 for android and iOS devices.  ...  CONCLUSION In this work, we demonstrated a reliable framework of identification of secure Viber traffic over the IP network and its further classification in to voice calls, voice/video calls, chat messages  ... 
doi:10.15394/jdfsl.2017.1477 fatcat:nofhq3lhgrb57mo5wwjjoplfhy

A novel privacy preserving user identification approach for network traffic

N. Clarke, F. Li, S. Furnell
2017 Computers & security  
This paper presents a novel approach to the identification of users from network traffic using only the metadata of the traffic (i.e. rather than payload) and the creation of application-level user interactions  ...  This results in an increasingly voluminous footprint with respect to the network traffic that is created as a consequence.  ...  , and traffic classifications.  ... 
doi:10.1016/j.cose.2017.06.012 fatcat:x5amv2a6jzdyvn7r64za4qbbrm

Guest Editorial Deep Packet Inspection: Algorithms, Hardware, and Applications

Ying-Dar Lin, Po-Ching Lin, Viktor K. Prasanna, H. Jonathan Chao, John W. Lockwood
2014 IEEE Journal on Selected Areas in Communications  
Therefore, the network devices equipped with the capability of DPI can provide numerous functions, such as network intrusion detection, traffic classification and contentaware policy control of network  ...  traffic, which will be otherwise much restricted if only packet headers are known.  ...  Traffic classification or network protocol identification is an essential part for content-aware network management. The third section covers three papers about protocol identification.  ... 
doi:10.1109/jsac.2014.2371093 fatcat:ze5m5gzosvhbjgyrp63pen5rta

Traffic Analysis of Mobile Broadband Networks

Geza Szabo, Daniel Orincsay, Balazs Peter Gero, Sandor Gyori, Tamas Borsos
2007 Proceedings of the 3rd International ICSTConference on Wireless Internet  
Several traffic classification approaches co-exist in the literature, but none of them performs well for all different application traffic types present in the Internet.  ...  In this study we compare and benchmark the currently known traffic classification methods on network traces captured in an operational 3G mobile network.  ...  else tunneled via HTTP.  ... 
doi:10.4108/wicon.2007.2157 dblp:conf/wicon/SzaboOGGB07 fatcat:nydzxafmivevdpmzicgmytweyu

FlowQoS

M. Said Seddiki, Muhammad Shahbaz, Sean Donovan, Sarthak Grover, Miseon Park, Nick Feamster, Ye-Qiong Song
2014 Proceedings of the third workshop on Hot topics in software defined networking - HotSDN '14  
, and the second classifier performs application identification performing application classification may be prohibitive.  ...  Current fier performs early application identification of HTTP and HTTPS home routers generally have limited computational resources, so traffic  ... 
doi:10.1145/2620728.2620766 dblp:conf/sigcomm/SeddikiSDGPFS14 fatcat:dm54inlg2bdxrpbasclodinayy

A Survey of HTTPS Traffic and Services Identification Approaches [article]

Wazen M. Shbair, Thibault Cholez, Jerome Francois, Isabelle Chrisment
2020 arXiv   pre-print
This survey details the techniques used to monitor HTTPS traffic, from the most basic level of protocol identification (TLS, HTTPS), to the finest identification of precise services.  ...  This migration towards a secure Web using HTTPS comes with important challenges related to the management of HTTPS traffic to guarantee basic network properties such as security, QoS, reliability, etc.  ...  [29] demonstrate how application behaviour still can be used as a signature to identify the application, even if its traffic is transmitted via HTTPS flows.  ... 
arXiv:2008.08339v1 fatcat:5fd344t7knbo5bpmhgleatowum

Toward In-Network Deep Machine Learning for Identifying Mobile Applications and Enabling Application Specific Network Slicing

Akihiro NAKAO, Ping DU
2018 IEICE transactions on communications  
This paper reports our initial attempt to apply deep machine learning for identifying application types from actual mobile network traffic captured from an MVNO, mobile virtual network operator and to  ...  within network to classify mobile traffic into fine grained slices, by identifying application types and devices so that we can apply Quality-of-Service (QoS) control, mobile edge/multi-access computing  ...  First, we posit that in future mobile network, in-network deep machine learning for application and device specific identification and traffic classification becomes possible and show the ground for this  ... 
doi:10.1587/transcom.2017cqi0002 fatcat:b24n5zc46vboxnbzsnntl3sfqu
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