Title
Scene Tagging: Image-Based Captcha Using Image Composition And Object Relationships
Keywords
access control; CAPTCHA; HIP; image/video recognition; multi-object composition; security
Abstract
In this paper, we propose a new form of image-based CAPTCHA we term "scene tagging". It tests the ability to recognize a relationship between multiple objects in an image that is automatically generated via composition of a background image with multiple irregularly shaped object images, resulting in a large space of possible images and questions without requiring a large object database. This composition process is accompanied by a carefully designed sequence of systematic image distortions that makes it difficult for automated attacks to locate/identify objects present. Automated attacks must recognize all or most objects contained in the image in order to answer a question correctly, thus the proposed approach reduces attack success rates. An experimental study using several widely-used object recognition algorithms (PWD-based template matching, SIFT, SURF) shows that the system is resistant to these attacks with a 2% attack success rate, while a user study shows that the task required can be performed by average users with a 97% success rate. © 2010 ACM.
Publication Date
7-16-2010
Publication Title
Proceedings of the 5th International Symposium on Information, Computer and Communications Security, ASIACCS 2010
Number of Pages
345-350
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1145/1755688.1755736
Copyright Status
Unknown
Socpus ID
77954463552 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/77954463552
STARS Citation
Matthews, Peter and Zou, Cliff C., "Scene Tagging: Image-Based Captcha Using Image Composition And Object Relationships" (2010). Scopus Export 2010-2014. 1067.
https://stars.library.ucf.edu/scopus2010/1067