| NSF Org: |
CNS Division Of Computer and Network Systems |
| Recipient: |
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| Initial Amendment Date: | January 18, 2007 |
| Latest Amendment Date: | June 22, 2011 |
| Award Number: | 0643906 |
| Award Instrument: | Continuing Grant |
| Program Manager: |
Jeremy Epstein
CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | August 15, 2007 |
| End Date: | July 31, 2013 (Estimated) |
| Total Intended Award Amount: | $400,000.00 |
| Total Awarded Amount to Date: | $432,000.00 |
| Funds Obligated to Date: |
FY 2008 = $80,000.00 FY 2009 = $176,000.00 FY 2011 = $96,000.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
201 OLD MAIN UNIVERSITY PARK PA US 16802-1503 (814)865-1372 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
201 OLD MAIN UNIVERSITY PARK PA US 16802-1503 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): |
Special Projects - CNS, ADVANCED NET INFRA & RSCH, TRUSTWORTHY COMPUTING |
| Primary Program Source: |
01000809DB NSF RESEARCH & RELATED ACTIVIT 01000910DB NSF RESEARCH & RELATED ACTIVIT 01001112DB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
Sencun Zhu
Pennsylvania State University
0643906
CAREER: Combating Worm Propagation in Emergent Networks
Panel ID: 070111
Abstract
Worms have emerged as one of the leading threats to our
information systems and critical infrastructures. Despite the
tremendous research effort in combating worms, new computer and
system vulnerabilities are continuously reported and new worm
attacks keep succeeding. Another significant trend in worm attacks
is that the number of worm attacks against emergent networks, such
as P2P networks, cellphone networks, and sensor networks, is
rapidly growing. Because of the unique communication models and/or
resource constraints of the emergent networks, most of the
existing solutions for Internet worm defenses are not directly
applicable.
The objective of this project is to combat worm propagation in
these emergent networks. Specifically, various approaches are
designed for rapidly distributing security patches to P2P nodes
infected by worms propagating via file sharing applications and
topological scanning. Also, both device and network sides defenses
are used to contain cellphone worms that propagate through either
multimedia messaging services or Bluetooth interfaces. Finally, it
includes mechanisms to confine worms that propagate by exploiting
the monoculture of sensor programs in sensor networks. The
proposed research will provide fundamental services and tools to
combat worms in emergent networks. It draws upon a variety of
topics including cryptography, graph theory (graph coloring,
percolation theory, partition, dominating set), system (mobile
systems), networking (P2P, cellular network, sensor network) and
statistics. The results of the project will be disseminated widely
through publications and talks, and the proposed research will
also be integrated with the education curricula.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Major findings:
--we can improve the effectiveness of cellphone worm containment by leveraging social ties among mobile nodes.
--we can detect cellphone malware by distinguishing user and machine behaviors.
--we can model the dynamic behavior of software to identify plagiarism and malware.
--we can leverage the existing P2P infrastructure and its topology information to efficiently distribute security patches in the arms-race with
worm propagation.
--Software-diversity can greatly increase the survivability of a sensor network against sensor worm attacks.
--We can detect social network worms such as koobface worm efficiently with a small number of decoy accounts in a social network.
--It is feasible to identify, based on the binary code, the algorithm that is implemented in a software. We developed an efficient run-time value based mechanism to detect algorithm plagiarism.
--Currently smartphones have many vulnerabilities (by design) which allow information leakage and spam/phishing attacks. The table below shows whether spamming (second column) or phishing (third column) is possible for different mobile phone platforms (first column).
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