************************************************************************ 
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*** Call for  
participation                                                            
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*** SIGCOMM 2006 Workshop on Mining network data (MineNet-06)  ***
*** (http://www.acm.org/sigs/sigcomm/sigcomm2006/?minenet)          ***
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*** Pisa, Italy. September 15,  
2006                                                    ***
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*** Co-located with ACM SIGCOMM  
2006                                          ***
*** Sponsored by  
ACM                                                                      
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Dear colleagues,

(We apologize if you received this already).

We would like to invite you to participate in the Second ACM SIGCOMM  
Workshop
on Mining network data (MineNet-06), Pisa, Italy, September 15, 2006.

The scope of the workshop and the advance program are attached below for
your perusal. We have tried to structure the workshop schedule to  
encourage
interaction  and discussions.  We hope you will enjoy the program.  
Please
share this with others who may be interested.


We  look forward to see you at the workshop in Pisa.

- Regards

Shubho Sen, Sambit Sahu
Workshop Chairs
MineNet 2006



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***    SIGCOMM 2006 Workshop on Mining network data  
(MineNet-06)       ***
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Call for Papers: http://www.sigcomm.org/sigcomm2006/?minenet

Advance Program: http://www.sigcomm.org/sigcomm2006/?minenet_program

Workshop Registration: http://www.sigcomm.org/sigcomm2006/?registrations

Early registration ends : Aug 9, 2006

Contact information: For general questions regarding the workshop,  
please
contact the organizers: {sen@research.att.com, sambits@us.ibm.com}




**************************
*** Workshop Scope ***
**************************

Welcome to the Second ACM SIGCOMM  Workshop on Mining Network Data

Todays IP networks are extensively instrumented for collecting a  
wealth of
information including traffic traces (e.g., packet or flow level  
traces),
control (e.g., router forwarding tables, BGP and OSPF updates), and
management (e.g., alarms, SNMP traps) data. The real challenge is to  
process
and analyze this vast amount of primarily unstructured information and
extract structures, relationships, and higher level knowledge  
embedded in it
and use it to aid network management and operations. The goal of this  
one
day workshop is to explore new directions in network data collection,
storage, and analysis techniques, and their application to network
monitoring, management, and remediation. The workshop will provide a  
venue
for researchers and practitioners from different backgrounds, including
networking, data mining, machine learning, and statistics, to get  
together
and collaboratively approach this problem from their respective vantage
points.







************************************************************************ 
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***                    MineNet 2006 Advance Program                    
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***********
Keynote:
***********

Title: On the Infrastructure for Network Data Mining: Concepts and  
Experiences.

Speaker: S. (Muthu) Muthukrishnan, Google.

Keynote Abstract:

A lot of focus on network data mining has been on "what",
that is, what analyses reveal interesting phenomena and prove
useful. This includes statistical analyses, model building and
parameter estimation, matching signatures and machine learning.

In this talk, the focus will be on the "how", that is,
how to design, build and use the infrastructure for supporting
a rich variety of mining tasks. The talk will discuss
--- the system architectures (Gigascope, CMON, Narus, MapReduce),
--- query languages and optimization (GSQL, User-defined functions,  
Sawzall), and
--- algorithms (streaming, approximate)
that form the infrastructure in large ISPs and web search companies.

The talk will also discuss experiences with cellular, IP and web data,
our successes thus far, and the challenges.


	

PAPER SESSION: Mining and Clustering
-----------------------------------------------------

1. Traffic Classification Using Clustering Algorithms Jeffrey Erman,  
Martin Arlitt, Anirban Mahanti (University of Calgary)

2. Mining Web Logs to Debug Distant Connectivity Problems Emre  
Kiciman, David Maltz, Moises Goldszmidt, John Platt (Microsoft Research)

3. Minerals: Using Data Mining to Detect Router Misconfigurations  
Franck Le, Sihyung Lee, Tina Wong, Hyong Kim (Carnegie Mellon  
University ), Darrell Newcomb (Network Operations, CENIC)

4. SVM Learning of IP Address Structure for Latency Prediction Robert  
Beverly, Karen Sollins, Arthur Berger (MIT CSAIL)
	

PAPER SESSION: Monitoring and Diagnosis
--------------------------------------------------------

1. Diagnosis of TCP Overlay Connection Failures using Bayesian  
Networks George Lee (Massachusetts Institute of Technology CSAIL) ,  
Lindsey Poole (Princeton University)

2. Toward Sophisticated Detection With Distributed Triggers Ling  
Huang (University of California, Berkeley) , Minos Garofalakis (Intel  
Research Berkeley) , Joe Hellerstein, Anthony D. Joseph (University  
of California, Berkeley) , Nina Taft (Intel Research Berkeley)

3. How to Extract BGP Peering Information from the Internet Routing  
Registry Giuseppe Di Battista, Tiziana Refice, Massimo Rimondini  
(University of Roma Tre)



SESSION: Panel discussion
------------------------------------

Title:  Online Traffic Recognition: A data mining challenge

Moderators:   Andre Broido, Google
                     Kave Salamatian, LIP6, Paris

	

PAPER  SESSION: Privacy and Security
---------------------------------------------------	

1. SC2D: An Alternative to Trace Anonymization Jeffrey C. Mogul (HP  
Labs) , Martin Arlitt (HP Labs, University of Calgary)

2. Privacy-Preserving Performance Measurements Matthew Roughan  
(University of Adelaide) , Yin Zhang (University of Texas, Austin)

3. Forensic Analysis of Autonomous System Reachability DK Lee, Sue  
Moon (Div. of Comp. Science, KAIST) , Taesang Choi, Taesoo Jeong (ETRI)