日本データベース学会

dbjapanメーリングリストアーカイブ(2006年)

DBSJ & ACM SIGMODJ 講演会のご案内 (12月18日)


dbjapanの皆様、

12月18日に下記の講演会がございます。
奮ってご参加ください。

 ☆☆☆  Prof. Calton Pu 講演会のご案内   ☆☆☆

共催 日本データベース学会
   ACM SIGMOD日本支部

日時 12月18日(月) 午後5時半〜午後6時半
場所 東京大学生産技術研究所 E棟 会議室B(Ew-502)
      E棟 5階 エレベータをあがってすぐ
      http://www.iis.u-tokyo.ac.jp/map/index.html

Title : Denial of Information

Speaker : Calton Pu
         Professor and John P. Imlay, Jr. Chair in Software
         College of Computing
         Georgia Institute of Technology

参加費 無料

参加ご希望の方は、
 日本データベース学会のホームページにて
   ( http://www.dbsj.org/ )
   会員登録の後(会費無料、すでに登録されている方は結構です)、
      sigmodj_lecture [at] tkl.iis.u-tokyo.ac.jpに
   添付の参加申込書をお送り下さい。

皆様のご参加をお待ちしております。

                        日本データベース学会 副会長・企画委員長
                        (ACM SIGMOD日本支部 支部長) 北川博之

                       担当委員  中野 美由紀
          
                        連絡(問合せ)先 日本データベース学会、ACM SIGMOD
日本支部
                                sigmodj_lecture [at] tkl.iis.u-tokyo.ac.jp
                http://www.dbsj.org/



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日本データベース学会・ACM SIGMOD日本支部共催 講演会 参加申し込み

12月18日(月)の講演会に参加
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Title : Denial of Information

Speaker : Calton Pu
         Professor and John P. Imlay, Jr. Chair in Software
         College of Computing
         Georgia Institute of Technology

				
ABSTRACT

Denial of Information (DOI) was introduced as an information analog of
Denial of
Service attacks.  A DOI attack consists of the injection of noise or
misleading
information to make it more difficult, expensive, or time-consuming to
find the
real answer in a large and evolving data set.  Well known problems that are
examples of DOI include: email spam, web spam, and blog spam.  We will
discuss
the technical challenges in DOI defense, focusing on the adversarial
learning
problem, where the defense (e.g., a statistical learning filter such as
Na・e Bayesian
or Support Vector Machine) must take input from the adversary (the
spammer).
There is no known general solution to the adversarial learning problem and
we discuss the limitations of retraining techniques that can only alleviate
the problem.  At the same time, we show that (contrary to expectations)
it is
possible to defend statistical filters for email spam against camouflage
attacks,
]where legitimate tokens are mixed into spam messages.  We will also
discuss other
areas susceptible to DOI and some of the progress made in these other areas.



--------------------------
Biography of Calton Pu

Calton Pu was born in Taiwan and grew up in Brazil.  He received his PhD
from
University of Washington in 1986 and served on the faculty of Columbia
University
and Oregon Graduate Institute.  Currently, he is holding the position of
Professor
and John P. Imlay, Jr. Chair in Software at the College of Computing,
Georgia
Institute of Technology.  He is currently working on three areas.
First, he is
using automated code generation techniques to automate and ensure the
correct
deployment of large scale N-tier applications in the Elba project.  Second,
he is investigating software and statistical techniques to defend
against Denial
of Information attacks in areas such as email and web spam.  Third, he
is working
on the application of specialization and other techniques to ensure the
reliability,
trust, and security of system and application software.  He has been the
principal
investigator of the Infosphere, Synthetix, and Immunix projects, with
technical
contributions such as Epsilon Serializability, Reflective Transaction
Framework,
and Continual Queries over the Internet.  His collaborations include
applications
of these techniques in scientific research on macromolecular structure
data, weather
data, and environmental data, as well as in industrial settings.  He has
published
more than 50 journal papers and book chapters, 150 conference and
refereed workshop
papers, and served on more than 100 program committees, including the
co-PC chairs
of SRDS'95, ICDE・9, COOPIS・2, SRDS・3, and co-general chair of
ICDE'97, CIKM'01,
ICDE・6.

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中野 美由紀		東京大学 生産技術研究所 喜連川研究室
Miyuki NAKANO		Institute of Industrial Science, Univ. of Tokyo
miyuki [at] tkl.iis.u-tokyo.ac.jp