Internet services offered for human use are suffering abuse by computer programs ('bots, spiders, scrapers, etc). We can defend against such attacks with CAPTCHAs---Completely Automatic Public Turing tests to tell Computers and Human Apart---which are special cases of 'human interactive proofs' (HIPs), security protocols allowing people easily to authenticate themselves over networks as members of given groups.
I will review six years of HIP R&D, share highlights of the first two HIP workshops (the most recent held at Lehigh last May), and describe CAPTCHAs now in use and on the horizon. An arms race appears to be shaping up.
One of the best ways to engineer a CAPTCHA is to exploit the gap in ability between humans and machines in attempting to read images of text. I will reveal details of ScatterType, a reading-based CAPTCHA developed here in collaboration with Avaya Labs. Its legibility has been validated by experiments on human subjects and it has resisted attack (so far) by advanced computer-vision techniques.
[Joint work with Richard Fateman, Allison Coates, Kris Popat, Monica Chew, Tom Breuel, Mark Luk, Terry Riopka, Michael Moll, Dan Lopresti, Sui-Yu Wang, Jon Bentley, and Colin Mallows.]
Dr. Baird is a Professor of Computer Science & Engineering at Lehigh Univ. and (with Dan Lopresti) heads up Lehigh's Pattern Recognition Research lab. Prior to joining academia he was a researcher and research manager at Bell Labs and the Xerox Palo Alto Research Center. He was elected Fellow of the IEEE and also of the IAPR, and received an ICDAR Outstanding Contributions award. He has served on the Editorial Board of several journals including IEEE Trans on PAMI and CVIU, and he's a founding member of the Editorial Board of the Int'l J. on Document Analysis and Recognition. He has published three books and seventy-five technical articles, and he holds seven patents. He has been founder, co-organizer, or program co-chair for six conferences and workshops.