Human Interactive Proofs and Document Image Analysis
DAS '02 Proceedings of the 5th International Workshop on Document Analysis Systems V
WWW '03 Proceedings of the 12th international conference on World Wide Web
Using a Text-to-Speech Synthesizer to Generate a Reverse Turing Test
ICTAI '03 Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Telling humans and computers apart automatically
Communications of the ACM - Information cities
Designing human friendly human interaction proofs (HIPs)
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
IMAGINATION: a robust image-based CAPTCHA generation system
Proceedings of the 13th annual ACM international conference on Multimedia
Human computation
Asirra: a CAPTCHA that exploits interest-aligned manual image categorization
Proceedings of the 14th ACM conference on Computer and communications security
Usability of CAPTCHAs or usability issues in CAPTCHA design
Proceedings of the 4th symposium on Usable privacy and security
Machine learning attacks against the Asirra CAPTCHA
Proceedings of the 15th ACM conference on Computer and communications security
A low-cost attack on a Microsoft captcha
Proceedings of the 15th ACM conference on Computer and communications security
Evaluating existing audio CAPTCHAs and an interface optimized for non-visual use
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
What's up CAPTCHA?: a CAPTCHA based on image orientation
Proceedings of the 18th international conference on World wide web
The robustness of a new CAPTCHA
Proceedings of the Third European Workshop on System Security
Scene tagging: image-based CAPTCHA using image composition and object relationships
ASIACCS '10 Proceedings of the 5th ACM Symposium on Information, Computer and Communications Security
CAPTCHA: using hard AI problems for security
EUROCRYPT'03 Proceedings of the 22nd international conference on Theory and applications of cryptographic techniques
An Audio CAPTCHA to Distinguish Humans from Computers
ISECS '10 Proceedings of the 2010 Third International Symposium on Electronic Commerce and Security
How Good Are Humans at Solving CAPTCHAs? A Large Scale Evaluation
SP '10 Proceedings of the 2010 IEEE Symposium on Security and Privacy
Attacks and design of image recognition CAPTCHAs
Proceedings of the 17th ACM conference on Computer and communications security
Recognizing objects in adversarial clutter: breaking a visual captcha
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
The Failure of Noise-Based Non-continuous Audio Captchas
SP '11 Proceedings of the 2011 IEEE Symposium on Security and Privacy
Breaking reCAPTCHAs with unpredictable collapse: heuristic character segmentation and recognition
MCPR'12 Proceedings of the 4th Mexican conference on Pattern Recognition
A novel gesture-based CAPTCHA design for smart devices
BCS-HCI '13 Proceedings of the 27th International BCS Human Computer Interaction Conference
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We present SEMAGE (SEmantically MAtching imaGEs), a new image-based CAPTCHA that capitalizes on the human ability to define and comprehend image content and to establish semantic relationships between them. A SEMAGE challenge asks a user to select semantically related images from a given image set. SEMAGE has a two-factor design where in order to pass a challenge the user is required to figure out the content of each image and then understand and identify semantic relationship between a subset of them. Most of the current state-of-the-art image-based systems like Assira [20] only require the user to solve the first level, i.e., image recognition. Utilizing the semantic correlation between images to create more secure and user-friendly challenges makes SEMAGE novel. SEMAGE does not suffer from limitations of traditional image-based approaches such as lacking customization and adaptability. SEMAGE unlike the current text-based systems is also very user-friendly with a high fun factor. These features make it very attractive to web service providers. In addition, SEMAGE is language independent and highly flexible for customizations (both in terms of security and usability levels). SEMAGE is also mobile devices friendly as it does not require the user to type anything. We conduct a first-of-its-kind large-scale user study involving 174 users to gauge and compare accuracy and usability of SEMAGE with existing state-of-the-art CAPTCHA systems like reCAPTCHA (text-based) [6] and Asirra (image-based) [20]. The user study further reinstates our points and shows that users achieve high accuracy using our system and consider our system to be fun and easy.