Title :
Design of a cognitive tool to detect malicious images using the smart phone
Author :
Nishiyama, Hiroki ; Mizoguchi, Fumio
Author_Institution :
Fac. of Sci. & Tech., Tokyo Univ. of Sci., Noda, Japan
Abstract :
In this study, we design a cognitive tool to detect malicious images using a smart phone. This tool can learn shot images taken with the camera of a smart phone and automatically classify the new image as an malicious image in the smart phone. To develop the learning and classifier tool, we implement an image analysis function and a learning and classifier function using a support vector machine (SVM) with the smart phone. With this tool, the user can collect image data with the camera of a smart phone, create learning data, and classify the new image data according to the learning data in the smart phone. In this study, we apply this tool to a user interface of a cosmetics recommendation service system and demonstrate its effectiveness by in reducing the load of the diagnosis server in this service and improving the user service.
Keywords :
cognitive systems; image classification; learning (artificial intelligence); recommender systems; smart phones; support vector machines; user interfaces; SVM; classifier function; classifier tool; cognitive tool design; cosmetics recommendation service system; diagnosis server; image analysis function; learning function; learning tool; malicious image detection; smart phone; support vector machine; user interface; user service; Lead; Servers; Support vector machines; Wireless communication;
Conference_Titel :
Cognitive Informatics & Cognitive Computing (ICCI*CC), 2013 12th IEEE International Conference on
Conference_Location :
New York, NY
Print_ISBN :
978-1-4799-0781-6
DOI :
10.1109/ICCI-CC.2013.6622276