Title :
A CAPTCHA Recognition Algorithm Based on Holistic Verification
Author :
Shu-guang, Huang ; Liang, Zhang ; Peng-po, Wang ; Hong-wei, Han
Author_Institution :
Dept. of Comput. Applic., Electron. Eng. Inst., Hefei, China
Abstract :
CAPTCHA is a new kind of network security mechanism. Studying the recognition of CAPTCHA can help to discover its hidden defects and thus make it more secure. For closely-connected CAPTCHAs that can hardly be recognized by methods of state of art, this paper proposed a new recognition algorithm based on holistic verification. During the process of this algorithm, Recurrent Neural Network (RNN) was first used to recognize unknown CAPTCHAs. Then, recognition results were verified by SVM rejection, synthetic data generation and Extreme Learning Machine (ELM). Experiments results show that this algorithm can not only recognize closely-connected CAPTCHAs but also effectively boost the recognition rate of RNN.
Keywords :
image recognition; recurrent neural nets; support vector machines; CAPTCHA recognition algorithm; ELM; RNN; Recurrent Neural Network; SVM; extreme learning machine; holistic verification; network security mechanism; Character recognition; Feature extraction; Humans; Image recognition; Image segmentation; Security; Training; CAPTCHA recognition; Extreme learning machine; Network security; Synthetic data generation;
Conference_Titel :
Instrumentation, Measurement, Computer, Communication and Control, 2011 First International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-0-7695-4519-6
DOI :
10.1109/IMCCC.2011.136
