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Empirical Data from Mobile and IP Telephony
2008
Journal of Communications Software and Systems
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This paper presents a comparison between recent mobile and IP telephony measurements and telephony measurement obtained nearly four decades ago. ...
This paper provides empirical traffic data and observations of telephony traffic patterns in mobile and IP telephony. ...
Finally, Section III-C compares the standard traffic demand profiles in the ITU-T E.523 recommendations with the profiles observed in the IP telephony measurements, in particular for international calls ...
doi:10.24138/jcomss.v4i1.237
fatcat:qxxud5pkdbdxtnyja73wrcrzbm
Profile deformation of aggregated flows handled by premium and low priority services within the Géant network
2010
Proceedings of the 6th International Wireless Communications and Mobile Computing Conference on ZZZ - IWCMC '10
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Nonetheless, the profile of the QoS traffic may deform by multiplexing in successive domains invalidating the traffic descriptor. ...
Therefore, studying traffic profile deformation in the domains results crucial in QoS networks. ...
Jordi Domingo Pascual for his cooperation and support during the stage in the Universitat Politècnica de Catalunya in Barcelona. ...
doi:10.1145/1815396.1815475
dblp:conf/iwcmc/BatallaBC10
fatcat:kkowh2fwpnbezmegyxhtkkrot4
SAFEM: Scalable analysis of flows with entropic measures and SVM
2012
2012 IEEE Network Operations and Management Symposium
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The prototype SAFEM (Scalable Analysis of Flows with Entropic Measures) uses spatial-temporal Netflow record aggregation and applies entropic measures to traffic. ...
This approach allows Internet operators, to whom botnets and spam are major threats, to detect large-scale distributed attacks. ...
For an IP address, the proportion of traffic it matches is computed regarding the total volume of traffic. This measure can be expressed as bytes or packets. ...
doi:10.1109/noms.2012.6211943
dblp:conf/noms/FrancoisWSE12
fatcat:zaueflweinfc3n6tdujre7g7wm
Online detection of network traffic anomalies using behavioral distance
2009
2009 17th International Workshop on Quality of Service
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To construct accurate online traffic profiles, we introduce horizontal and vertical distance metrics between various traffic features (i.e., packet header fields) in the traffic data streams. ...
per-flow state; (3) it is scalable to high speed traffic links because of the aggregation, and (4) using various combinations of packet features and measuring distances between them, it is capable for ...
The normal profile learned during the training period is used as a reference to measure the distance between itself and the current profile of traffic features in the testing period. ...
doi:10.1109/iwqos.2009.5201415
dblp:conf/iwqos/SengarWWWJ09
fatcat:5cue6wy73zhvbivtgkoq7qsucu
Behavior Profiling and Analysis in Wireless Home Networks
2010
2010 7th IEEE Consumer Communications and Networking Conference
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traffic behavior in IP networks [5] , [6] . ...
To analyze the behavior of each legitimate computer, we first separate its inbound traffic based on the applications, and measure the distributions of the traffic features. ...
doi:10.1109/ccnc.2010.5421571
dblp:conf/ccnc/XuWW10
fatcat:vn4s65zpczbezciyb276lkzaq4
A novel measure for low-rate and high-rate DDoS attack detection using multivariate data analysis
2016
2016 8th International Conference on Communication Systems and Networks (COMSNETS)
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We extract three basic parameters of network traffic, namely, entropy of source IPs, variation of source IPs, and packet rate to analyze the behavior of network traffic for attack detection. ...
In this paper, we introduce a statistical measure called Feature Feature score for multivariate data analysis to distinguish DDoS attack traffic from normal traffic. ...
The measure uses entropy of source IPs (E sip ), variation index of source IPs (V sip ), packet rate (P rate ), and distinct source IPs (D sip ). ...
doi:10.1109/comsnets.2016.7439939
dblp:conf/comsnets/HoqueBK16
fatcat:pp63qsux6rdjphe2o6jcdsixpq
On detecting and identifying faulty internet of things devices and outages
2021
Bulletin of Electrical Engineering and Informatics
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Our measurements show that the two methods can effectively detect and identify malfunctioned or defective IoT devices. ...
Based on the collected traffic or flow entropy, these methods can determine the health status of IoT devices by comparing captured traffic behavior with normal traffic patterns. ...
The normal/expected traffic profile contains the the expected number of packets for each block, and the expected bitwise summation of source IP addresses. ...
doi:10.11591/eei.v10i6.2698
fatcat:lj4j6nhw6rag7jqc2mosfbo7ie
An adaptive profile-based approach for detecting anomalous traffic in backbone
2019
IEEE Access
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More specifically, a more comprehensive metrics set is defined from the dimensions of temporal, spatial, category, and intensity to compose IP traffic behavior characteristic spectrum for fine-grained ...
Then, the digital signature matrix obtained by using the ant colony optimization (ACO) algorithm is applied to construct the baseline profile of the normal traffic behavior. ...
ACKNOWLEDGMENT Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of those sponsors. ...
doi:10.1109/access.2019.2914303
fatcat:peziujuwcnenrgvzqaaocgvj6a
Conception, Implementation, and Evaluation of a QoS-Based Architecture for an IP Environment Supporting Differentiated Services
[chapter]
2001
Lecture Notes in Computer Science
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IP level mechanisms providing the defined services. ...
The paper successively presents the design principles of the proposed architecture, the networking platform on which the architecture has been developed and the experimental measurements validating the ...
Note that the second and third points are compliant to the expectations as we only consider in-profile traffic; measurements with out of profile traffic would show a receiving throughput inferior to the ...
doi:10.1007/3-540-44763-6_10
fatcat:vscacbvj45hotffounfrvkrqbu
Behavior Analysis of Internet Traffic Using Graph and Similarity Matrix
2015
International Journal of Science and Research (IJSR)
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At that point by applying a basic and effective algorithm and similarity matrices and cluster coefficient of one mode projection graph, inherent clustered groups of internet application are discovered. ...
As system activity of utilizations, for example, video spilling and distributed applications proceeds to grow it is difficult task to understand behavior patterns of end host and other network application ...
Profiling and clustering internet hosts The objective of this research is to study the behavior of IP Network nodes (IP hosts) from the prospective of their communication behavior patterns to setup hosts ...
doi:10.21275/v4i12.nov152057
fatcat:vlt7f4eyhngrviaskk3tyaslve
On Enhancing Diffserv Architecture by Dynamic Policy Provisioning Using Network Feedback
[chapter]
2003
IFIP Advances in Information and Communication Technology
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This artic\e describes an approach to improve IP packet marking entering a Diffserv domain through dynamic policy provisioning and network feedback signaling. ...
This allows dynamic reallocation and management of resources based on current network state and applications QoS requirements. ...
I
Figure 1 : 1 Hierarchical aggregation of traffie measurements
Figure 2 : 2 Dynamic Policy Provisioning
I•• NetworkUnderLoad Aecept video out-of-profile trafiic • Mark in and out of profile video ...
doi:10.1007/978-0-387-35620-4_23
fatcat:l6j7vd656ndunp3zf4xujuqomu
Dynamic QoS Adaptation Using COPS and Network Monitoring Feedback
[chapter]
2002
Lecture Notes in Computer Science
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This paper presents an approach to handle out of profile traffic using Common Open Policy Service and network monitoring feedback. ...
This later, depending on the network state, pushes policy decision rules to the Policy Enforcement Point in order to accept, remark or drop out-of-profile traffic dynamically. ...
With a known IP address and/or IP port number, the administrator can specify a policy that refers to user application IP address and marks traffic coming from that address appropriately. ...
doi:10.1007/3-540-45812-3_20
fatcat:upa7q5ghazhsvnvi4vc54thc4a
Baseline Profile Stability for Network Anomaly Detection
2006
Third International Conference on Information Technology: New Generations (ITNG'06)
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Although there has been some preliminary research, the details of profiling, such as the profile format, its size and the traffic stability by site or time, have not been widely available. ...
The result of this study can be used practically to anomaly-based IDS for determining the stability of the traffic for a particular site, and the number of required traffic profiles based on the traffic ...
This research guides how to check whether a particular site has meaningful traffic stability, how to measure the stability within a site, and how to decide the number of required traffic profiles. ...
doi:10.1109/itng.2006.38
dblp:conf/itng/KimJS06
fatcat:anqtisp2hjenfludqozny7h3ui
A behavior-aware profiling of handheld devices
2015
2015 IEEE Conference on Computer Communications (INFOCOM)
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Prior efforts only focused on studying either the comparative characterization of aggregate network traffic between BYOHs and non-BYOHs or network performance issues, such as TCP and download times or ...
In response, we design and deploy BROFILER, a behavior-aware profiling framework that improves visibility into the management of BYOHs. The contributions of our work are two-fold. ...
The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the National Science Foundation ...
doi:10.1109/infocom.2015.7218455
dblp:conf/infocom/WeiVMNF15
fatcat:4t4iuxxvovfwznjqwuk3a3t4fy
Towards a user network profiling for internal security using top-k rankings similarity measures
2017
2017 40th International Conference on Telecommunications and Signal Processing (TSP)
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This work proposes a new approach to identify whether a network user is having or not a normal behavior, by analyzing host traffic using top-k ranking similarity measures. ...
In campus area networks, the risk of having internal attacks is high because of their topologies and the amount of users. ...
Parres-Peredo built a priori and compared with the current user profile by means of similarity measures for top-k rankings. ...
doi:10.1109/tsp.2017.8075928
dblp:conf/tsp/Parres-PeredoPC17
fatcat:oowrptqzxzatpnpn5k4j3ihsjy
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