[ISN] "Learning from Authoritative Security Experiment Results" (LASER 2012) Workshop Call for Papers

***LASER 2012 -- SUBMISSION DEADLINE EXTENDED TO APRIL 9, 2012*** 
Please make a note of this extension.  Details are below.

       LASER 2012 -- Learning from Authoritative Security Experiment
       Results

       The goal of this workshop is to provide an outlet for
       publication of unexpected research results in security -- to
       encourage people to share not only what works, but also what
       doesn't.  This doesn't mean bad research -- it means research
       that had a valid hypothesis and methods, but the result was
       negative. Given the increased importance of computer security,
       the security community needs to quickly identify and learn from
       both success and failure.

       Journal papers and conferences typically contain papers that
       report successful experiments that extend our knowledge of the
       science of security, or assess whether an engineering project
       has performed as anticipated. Some of these results have high
       impact; others do not. Unfortunately, papers reporting on
       experiments with unanticipated results that the experimenters
       cannot explain, or experiments that are not statistically
       significant, or engineering efforts that fail to produce the
       expected results, are frequently not considered publishable,
       because they do not appear to extend our knowledge.  Yet, some
       of these "failures" may actually provide clues to even more
       significant results than the original experimenter had intended.
       The research is useful, even though the results are unexpected.

       Useful research includes a well-reasoned hypothesis, a
       well-defined method for testing that hypothesis, and results
       that either disprove or fail to prove the hypothesis.  It also
       includes a methodology documented sufficiently so that others
       can follow the same path. When framed in this way,
       "unsuccessful" research furthers our knowledge of a hypothesis
       and testing method. Others can reproduce the experiment itself,
       vary the methods, and change the hypothesis; the original result
       provides a place to begin.

       As an example, consider an experiment assessing a protocol
       utilizing biometric authentication as part of the process to
       provide access to a computer system. The null hypothesis might
       be that the biometric technology does not distinguish between
       two different people; in other words, that the biometric element
       of the protocol makes the approach vulnerable to a masquerade
       attack. Suppose the null hypothesis is verified. It would still
       be worth publishing this result. First, it might prevent others
       from trying the same biometric method. Second, it might lead
       them to further develop the technology - to determine whether a
       different style of biometrics would improve matters, or if the
       environment in which authentication is being attempted makes a
       difference.  For example, a retinal scan may be a failure in
       recognizing people in a crowd, but successful where the users
       present themselves one at a time to an admission device with
       controlled lighting, or when multiple "tries" are included.
       Third, it might lead to modifying the encompassing protocol so
       as to make masquerading more difficult for some other reason.

       Equally important is research designed to reproduce the results
       of earlier work. Reproducibility is key to science, to validate
       or uncover errors or problems in earlier work. Failure to
       reproduce the results leads to a deeper understanding of the
       phenomena that the earlier work uncovers.

       The workshop focuses on research that has a valid hypothesis and
       reproducible experimental methodology, but where the results
       were unexpected or did not validate the hypotheses, where the
       methodology addressed difficult and/or unexpected issues, or
       that identified previously unsuspected confounding issues.

       We solicit research and position papers addressing these issues,
       especially (but not exclusively) on the following topics:

       * Unexpected research results in experimental security
       * Methods, statistical analyses, and designs for security
       experiments
       * Experimental confounds, mistakes, mitigations
       * Successes and failures in reproducing the experimental
       techniques and/or results of earlier work

       Extended abstracts, full position papers, and research
       submissions should be 6–10 pages long including tables, figures,
       and references. Please use the ACM Proceedings Format at
       http://www.acm.org/sigs/publications/proceedings-templates
       (Option 1, if using LaTeX).

       At least one author from every accepted paper must plan to
       attend the workshop and present.

       Schedule:                            Location:
       March 26, 2012        submissions deadline        SRI
       International
       May 7, 2012        decisions to authors        1100 Wilson
       Boulevard, Suite 2800
       June 15, 2012        final papers            Arlington, VA 22209
       July 18 & 19, 2012    workshop

       For further information:    http://www.laser-workshop.org

       Funded in part by a grant from NSF

       Program Committee:                      Organizing Committee:
       Matt Bishop (UC Davis), PC Co-Chair     Carrie Gates (CA Labs),
       General Chair
       Greg Shannon (CMU/CERT), PC Co-Chair    Matt Bishop (UC Davis),
       PC Co-Chair
       Alessandro Acquisti (CMU)               Greg Shannon (CMU/CERT),
       PC Co-Chair
       Ross Anderson (Cambridge)               Deb Frincke (NSA)
       Terry Benzel (USC/ISI)                  Christoph Schuba
       (Oracle), Publications Chair
       George Cybenko (Dartmouth)              Ed Talbot (Consultant)
       Jeremy Epstein (SRI)
       Carrie Gates (CA Labs)
       Dan Geer (In-Q-Tel)
       Kevin Killourhy (CMU)
       John Knight (University of Virginia)
       Tom Longstaff (JHU/APL)
       Roy Maxion (CMU)
       John McHugh (University of North Carolina)
       Vern Paxson (ICSI & UC Berkeley)
       Shari Pfleeger (Dartmouth/I3P)
       Angela Sasse (University College London)
       Christoph Schuba (Oracle)
       Gene Spafford (Purdue)
       Ed Talbot (Consultant)
       Steve Taylor (Dartmouth)
       Charles Wright (MIT/LL)


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