Generating secure images for CAPTCHAs through noise addition

David Lorenzi, Pratik Chattopadhyay, Emre Uzun, Jaideep Vaidya, Shamik Sural, Vijayalakshmi Atluri

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

As online automation, image processing and computer vision become increasingly powerful and sophisticated, methods to secure online assets from automated attacks (bots) are required. As traditional text based CAPTCHAs become more vulnerable to attacks, new methods for ensuring a user is human must be devised. To provide a solution to this problem, we aim to reduce some of the security shortcomings in an alternative style of CAPTCHA - more specifically, the image CAPTCHA. Introducing noise helps image CAPTCHAs thwart attacks from Reverse Image Search (RIS) engines and Computer Vision (CV) attacks while still retaining enough usability to allow humans to pass challenges. We present a secure image generation method based on noise addition that can be used for image CAPTCHAs, along with 4 different styles of image CAPTCHAs to demonstrate a fully functional image CAPTCHA challenge system.

Original languageEnglish (US)
Title of host publicationSACMAT 2015 - Proceedings of the 20th ACM Symposium on Access Control Models and Technologies
PublisherAssociation for Computing Machinery
Pages169-172
Number of pages4
ISBN (Electronic)9781450335560
DOIs
StatePublished - Jun 1 2015
Event20th ACM Symposium on Access Control Models and Technologies, SACMAT 2015 - Vienna, Austria
Duration: Jun 1 2015Jun 3 2015

Publication series

NameProceedings of ACM Symposium on Access Control Models and Technologies, SACMAT
Volume2015-June

Other

Other20th ACM Symposium on Access Control Models and Technologies, SACMAT 2015
CountryAustria
CityVienna
Period6/1/156/3/15

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Networks and Communications
  • Safety, Risk, Reliability and Quality
  • Information Systems

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