Project Description
The MR-Net project ran from 2006 to 2010 and is now complete.
Its research results are now used by several other projects at ISI and elsewhere.
For follow-on work, please see current work by the ANT Lab.
MADCAT is a joint research effort of
USC/Information Sciences Institute,
USC’s Electrical Engineering Dept.,
and
Colorado State University’s Computer Science Dept.
The Internet can be a dangerous place, with malware
taking control of users’ computers and turning them against others
or themselves.
Many compromised computers generate
maltraffic, which includes
denial-of-service (DoS) attacks, spyware reporting home,
unauthorized applications (applications in violation of a corporate
acceptable use policy such as peer-to-peer file sharing, chat, games),
spam (both inbound and outbound), and worms.
Firewalls, intrusion detection systems, anti-virus programs, proxies and filters
all try to defend against maltraffic.
Unfortunately, defense is increasingly difficult
due to
traffic encryption,
edge-level aggregation (making filtering and blacklisting
result in collateral damage),
and
large traffic volumes and active cloaking
allowing maltraffic to hide itself.
MADCAT proposes to use
signal processing and detection theory
as new tools to address these problems in detecting maltraffic.
MADCAT is supported by the National Science Foundation’s
Networking Technology and Systems (NeTS) program,
grant number
CNS-0626696.
People
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Genevieve Bartlett, researcher
(USC CS Dept. and ISI)
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Xinming He, USC CS PhD graduate (2006)
(USC CS Dept.)
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John Heidemann, PI on this project, project leader and professor
(USC/ISI)
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Wen-tien Kung, USC EE MS graduate (2005)
(USC EE Dept.)
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Sean McPherson, USC EE PhD graduate (2011)
(USC EE Dept.)
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Urbashi Mitra, professor
(USC EE Dept.)
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Antonio Ortega, professor
(USC EE Dept.)
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Christos Papadopoulos, co-PI on this project, professor
(University of Memphis)
christos.papadopoulos (at) memphis.edu
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Rishi Sinha, USC CS PhD graduate (2006)
(USC CS Dept.)
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Gautam Thatte, USC EE PhD graduate (2011)
(USC EE Dept.)
Publications
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Lin Quan, John Heidemann and Yuri Pradkin 2012. Detecting Internet Outages with Precise
Active Probing (extended). Technical Report ISI-TR-2012-678b. USC/Information Sciences Institute.
[PDF]
Details
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Lin Quan and John Heidemann 2011. Detecting Internet Outages with Active Probing (extended). Technical Report ISI-TR-2011-672. USC/Information Sciences Institute.
[PDF]
Details
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Lin Quan and John Heidemann 2010. On the Characteristics and Reasons of Long-lived Internet Flows. Proceedings of the ACM Internet Measurement Conference (Melbourne, Australia, Nov. 2010), 444–450.
[DOI]
[PDF]
Details
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Xue Cai and John Heidemann 2010. Understanding Block-level Address Usage
in the Visible Internet. Proceedings of the ACM SIGCOMM Conference (New Delhi, India, Aug. 2010), 99–110.
[DOI]
[PDF]
Details
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Gautam Thatte, Urbashi Mitra and John Heidemann 2010. Parametric Methods for Anomaly Detection in Aggregate Traffic. ACM/IEEE Transactions on Networking. 19, 2 (Aug. 2010), 512–525.
[DOI]
[PDF]
Details
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Xue Cai and John Heidemann 2010. Understanding Block-level Address Usage
in the Visible Internet (extended). Technical Report ISI-TR-2009-665. USC/Information Sciences Institute.
[PDF]
Details
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Lin Quan and John Heidemann 2010. On the Characteristics and Reasons of
Long-lived Internet Flows (extended). Technical Report ISI-TR-2010-667. USC/Information Sciences Institute.
[PDF]
Details
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Chris Wilcox, Christos Papadopoulos and John Heidemann 2010. Correlating Spam Activity with IP Address Characteristics. Proceedings of the IEEE Global Internet Symposium (San Diego, California, USA, Mar. 2010), 1–6.
[DOI]
[PDF]
Details
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Genevieve Bartlett, John Heidemann and Christos Papadopoulos 2009. Using Low-Rate Flow Periodicities for Anomaly
Detection: Extended. Technical Report ISI-TR-2009-661. USC/Information Sciences Institute.
[PDF]
Details
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Gautam Thatte, Urbashi Mitra and John Heidemann 2009. Parametric Methods for Anomaly Detection in Aggregate Traffic. Technical Report ISI-TR-2009-663b. USC/Information Sciences Institute.
[PDF]
Details
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Gautam Thatte, Urbashi Mitra and John Heidemann 2009. Parametric Methods for Anomaly Detection in Aggregate Traffic. Technical Report ISI-TR-2009-663. USC/Information Sciences Institute.
[PDF]
Details
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John Heidemann and Christos Papadopoulos 2009. Uses and Challenges for Network Datasets. Proceedings of the IEEE Cybersecurity Applications and Technologies Conference for Homeland Security (CATCH) (Washington, DC, USA, Mar. 2009), 73–82.
[DOI]
[PDF]
Details
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Xue Cai and John Heidemann 2009. Understanding Address Usage in the Visible Internet. Technical Report ISI-TR-2009-656. USC/Information Sciences Institute.
[PDF]
Details
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Xinming He, Christos Papadopoulos, John Heidemann, Urbashi Mitra and Usman Riaz 2009. Remote Detection of Bottleneck Links Using Spectral and Statistical Methods. Computer Networks. 53, 3 (Feb. 2009), 279–298.
[DOI]
[PDF]
Details
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John Heidemann, Yuri Pradkin, Ramesh Govindan, Christos Papadopoulos, Genevieve Bartlett and Joseph Bannister 2008. Census and Survey of the Visible Internet. Proceedings of the ACM Internet Measurement Conference (Vouliagmeni, Greece, Oct. 2008), 169–182.
[PDF]
Details
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Xue Cai and John Heidemann 2008. Active Probing to Classify Internet Address Blocks
(poster abstract). Proceedings of the ACM SIGCOMM Conference (Seattle, Washington, USA, Aug. 2008), to appear.
[PDF]
Details
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Xue Cai and John Heidemann 2008. Active Probing to Classify Internet Address Blocks
(poster abstract). Technical Report ISI-TR-2008-653. USC/Information Sciences Institute.
[PDF]
Details
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Gautam Thatte, Urbashi Mitra and John Heidemann 2008. Detection of Low-Rate Attacks in Computer Networks. Proceedings of the 11th IEEE Global Internet Symposium (Phoenix, Arizona, USA, Apr. 2008), 1–6.
[DOI]
[PDF]
Details
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John Heidemann, Yuri Pradkin, Ramesh Govindan, Christos Papadopoulos, Genevieve Bartlett and Joseph Bannister 2008. Census and Survey of the Visible Internet (extended). Technical Report ISI-TR-2008-649b. USC/Information Sciences Institute.
[PDF]
Details
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Genevieve Bartlett, John Heidemann, Christos Papadopoulos and James Pepin 2007. Estimating P2P Traffic Volume at USC. Technical Report ISI-TR-2007-645. USC/Information Sciences Institute.
[PDF]
Details
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Urbashi Mitra, Antonio Ortega, John Heidemann and Christos Papadopoulos 2006. Detecting and Identifying Malware: A New Signal Processing Goal. IEEE Signal Processing Magazine. 23, 5 (Sep. 2006), 107–111.
[PDF]
Details
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Alefiya Hussain, John Heidemann and Christos Papadopoulos 2006. Identification of Repeated Denial of Service Attacks. Proceedings of the IEEE Infocom (Barcelona, Spain, Apr. 2006), to appear.
[PDF]
Details
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Xinming He, Christos Papadopoulos, John Heidemann, Urbashi Mitra, Usman Riaz and Alefiya Hussain 2005. Spectral Analysis of Bottleneck Traffic. Technical Report USC-CSD-TR-05-854. University of Southern California Computer Science Department.
[PDF]
Details
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Alefiya Hussain, John Heidemann and Christos Papadopoulos 2004. Distinguishing between Single and Multi-source Attacks using Signal Processing. Computer Networks. 46, 4 (Nov. 2004), 479–503.
[PDF]
Details
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Xinming He, Christos Papadopoulos, John Heidemann and Alefiya Hussain 2004. Spectral Characteristics of Saturated Links. Technical Report USC-CSD-TR-827. University of Southern California Computer Science Department.
[PDF]
Details
For related publications, please see the
ANT publications web page.
Software
See also the ANT software web page.
Traces
See the ANT traces page.