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Nachrichten, Termine, Experten
Nachrichten, Termine, Experten
Die Digitalisierung des Alltagslebens hat zu einer stetig wachsenden Datensammelwut seitens Behörden, Unternehmen und selbst von Privatleuten geführt. Mittlerweile vorhandene computergestützte statistische Auswertungsmöglichkeiten können zu gesellschaftlichen Vorteilen, aber auch privaten Nachteilen führen. Den Stand der Dinge und Konfliktlösungsmöglichkeiten beleuchtet Prof. Dr. Johannes Gehrke von der Cornell University, Ithaca, New York in einem Informatik-Kolloquium an der TU Darmstadt (Gebäude S2 02, Hochschulstr. 10, Raum C110) am 25. April 2005 um 16 Uhr. Das Kolloquium mit dem Titel "Data Privacy for Data Mining and Data Publishing" wird in englischer Sprache gehalten und ist öffentlich zugänglich; eine formlose Anmeldung per E-Mail ist erwünscht an kraft@dekanat.informatik.tu-darmstadt.de. Gehrke kommt auf Einladung von Prof. Dr. Thomas Hofmann, Professor am Lehrstuhl für Intelligente Systeme an der TU Darmstadt und Leiter des Fraunhofer-Instituts für Integrierte Publikations- und Informationssysteme IPSI (http://www.ipsi.de). Ein Anfahrtplan findet sich unter http://www.informatik.tu-darmstadt.de.
Gehrke beschäftigt sich in seinem Vortrag vorrangig mit dem Zielkonflikt zwischen der gesellschaftlich notwendigen Sammlung und Aufbereitung von privaten Daten und dem Wunsch des Einzelnen, seine Privatsphäre zu bewahren. Eine mögliche Lösung sieht er in der anonymisierten statistischen Auswertung der personenbezogenen Daten. Weitere Informationen zu Johannes Gehrke finden sich unter http://www.cs.cornell.edu/johannes/ .
ABSTRACT des Vortrages:
The digitization of our daily lives has led to an explosion in the collection of data by governments, corporations, and individuals. Knowledge of statistical properties of this private data extracted through data mining techniques can have significant societal benefit, for example to understand social trends or to create knowledge through global collaboration. However, protection of privacy of personal data is equally important. What do we mean by data privacy in such a setting, and how can we bridge the two seemingly conflicting goals of sharing data while preserving privacy? We show how to use statistical techniques to learn from private data while preserving data privacy. We show that in order to correctly quantify privacy, we have to model the knowledge of an attacker, and we give a novel definition of privacy that quantifies the information flow to an attacker. We then show two applications of our methodology: an approach to privacy-preserving data mining using randomization and a method for limiting disclosure in data publishing. Parts of this talk represent joint work with Rakesh Agrawal, Alexandre Evfimievski, Dan Kifer, Ashwin Machanavajjhala, Ramakrishnan Srikant, and Muthuramakrishnan Venkitasubramaniam.
SHORT BIOGRAPHY:
Johannes Gehrke is an Associate Professor in the Department of Computer Science at Cornell University and a Faculty Associate Director of the Cornell Theory Center. He obtained his Ph.D. in computer science from the University of Wisconsin-Madison in 1999. Johannes Gehrke's research interests are in the areas of data mining, data stream processing, data privacy, and applications of database and data mining technology to the sciences. Johannes has received a National Science Foundation Career Award, an Arthur P. Sloan Fellowship, an IBM Faculty Award, the Cornell College of Engineering James and Mary Tien Excellence in Teaching Award, and the Cornell University Provost's Award for Distinguished Scholarship. He is the author of numerous publications on data mining and database systems, and he co-authored the undergraduate textbook Database Management Systems (McGrawHill (2002), currently in its third edition), used at universities all over the world. Johannes has served as Area Chair for the International Conference on Machine Learning in 2003 and 2005, as co-Chair of the 2003 ACM SIGKDD Cup, and as Program co-Chair of the 2004 ACM International Conference on Knowledge Discovery and Data Mining. He is a member of the ACM SIGKDD Curriculum Commmittee. Johannes Gehrke has given courses and tutorials on data mining and data stream processing at international conferences and on Wall Street, and he has extensive industry experience as technical advisor and consultant.
Information on participating / attending:
Kostenlos, formlose Anmeldung per E-Mail ist erwünscht an kraft@dekanat.informatik.tu-darmstadt.de
Date:
04/25/2005 16:00 - 04/25/2005 17:00
Event venue:
TU Darmstadt (Gebäude S2 02, Hochschulstr. 10, Raum C110)
64289 Darmstadt
Hessen
Germany
Target group:
Scientists and scholars, Students
Email address:
Relevance:
regional
Subject areas:
Information technology, Law, Media and communication sciences, Politics, Social studies
Types of events:
Entry:
04/12/2005
Sender/author:
Presse Institute
Department:
Kommunikation
Event is free:
yes
Language of the text:
English
URL of this event: http://idw-online.de/en/event13795
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