Lopresti daniel p (3 Ergebnisse)
- Hardcover
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Hardcover. Zustand: Very Good. No Jacket. Hardcover 2005 library bound edition. Ex-library book with stamps and labels attached. Binding firm. Pages unmarked and clean. Laminated covers and text in very good condition. Series: Lecture Notes in Computer Science ;3517. [vi, 141 p. : ill. ; 24 cm].
- Softcover
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Zustand: New. In.
- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 protocol…s 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.
