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