NDLI: Identifying 802.11 Traffic From Passive Measurements Using Iterative Bayesian Inference

Content Provider	IEEE Xplore Digital Library
Author	Wei, W. Jaiswal, S. Kurose, J. Towsley, D. Kyoungwon Suh Bing Wang
Copyright Year	1993
Abstract	In this paper, we propose a classification scheme that differentiates Ethernet and WLAN TCP flows based on measurements collected passively at the edge of a network. This scheme computes two quantities, the fraction of wireless TCP flows and the degree of belief that a TCP flow traverses a WLAN inside the network, using an iterative Bayesian inference algorithm that we developed. We prove that this iterative Bayesian inference algorithm converges to the unique maximum likelihood estimate (MLE) of these two quantities. Furthermore, it has the advantage that it can handle any general K-classification problem given the marginal distributions of these classes. Numerical and experimental evaluations demonstrate that our classification scheme obtains accurate results. We apply this scheme to two sets of traces collected from two campus networks: one set collected from UMass in mid 2005 and the other collected from UConn in late 2010. Our technique infers that 4%-7% and 52%-55% of incoming TCP flows traverse an IEEE 802.11 wireless link in these two networks, respectively.
Sponsorship	IEEE Computer Society IEEE Communications Society Association for Computing Machinery (ACM)
Starting Page	325
Ending Page	338
Page Count	14
File Size	1128947
File Format	PDF
ISSN	10636692
Volume Number	20
Issue Number	2
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-04-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wireless LAN Wireless communication Monitoring Inference algorithms Maximum likelihood estimation Bayesian methods Communication system security wireless traffic detection IEEE 802.11 wireless LAN iterative Bayesian inference TCP ACK-pairs
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications Electrical and Electronic Engineering Computer Science Applications Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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