EAN: | 9783540260011 |
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Sachgruppe: | Informatik, EDV |
Sprache: | Englisch |
Seitenzahl: | 156 |
Produktart: | Kartoniert / Broschiert |
Herausgeber: | Baird, Henry S. Lopresti, Daniel P. |
Veröffentlichungsdatum: | 12.05.2005 |
Untertitel: | Second International Workshop, HIP 2005, Bethlehem, PA, USA, May 19-20, 2005, Proceedings |
Schlagworte: | Begründung / Beweis Beweis Intelligenz / Künstliche Intelligenz KI Künstliche Intelligenz - AI |
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E-commerce services are su?ering abuse by programs (bots, spiders, etc.) m- querading as legitimate human users. E?orts to defend against such attacks have, over the past several years, stimulated investigations into a new family of security protocols ¿ ¿Human Interactive Proofs¿ (HIPs) ¿ which allow a person to authenticate herself as a member of a given group: e.g., as a human (vs. a machine), as herself (vs. anyoneelse), as an adult (vs. a child). Most commercial usesofHIPstodayareCAPTCHAs,¿CompletelyAutomaticPublicTuringtests to tell Computers and Humans Apart,¿ which exploit the gap in ability between humans and machine vision systems in reading images of text. HIP challenges can also be non-graphical, e.g., requiring recognition of speech, solving puzzles, etc. Wearepleasedtopresentthe?rstrefereedandarchivallypublishedcollection of state-of-the-art papers on HIPs and CAPTCHAs. Each paper was reviewed by three members of the Program Committee, judged by the Co-chairs to be of su?cient relevance and quality, and revised by the authors in response to the referees¿ suggestions. The papers investigate performance analysis of novel CAPTCHAs, HIP - chitectures, and the role of HIPs within security systems. Kumar Chellapilla, Kevin Larson, Patrice Simard, and Mary Czerwinski describe user trials of a CAPTCHA designed to resist segmentation attacks, including a systematic evaluation of its tolerance by human users. Henry Baird, Michael Moll, and Sui- Yu Wang analyze data from a human legibility trial of another segmentati- resistantCAPTCHAandlocateahighlylegibleengineeringregime.AmaliaRusu and Venu Govindaraju describe research towards CAPTCHAs based on reading synthetically damaged images of real images of unconstrained handwritten text.