- 期刊
- OpenAccess
Accessing Social Network Sites Using Work Smartphone for Face Recognition and Authentication
並列摘要
Nowadays, Social Networking Sites (SNS) are increasingly getting the attention of academic, industrial researchers intrigued by their affordances and gradually gaining its importance and became a major method used to share thoughts, video, image, etc., in various domains such as research, politics, religion, academics and development. Apart of its strength points SNS has one major drawback which is the inefficient authentication of users to login. Due to this drawback; different types of fake message, non-social activities, national or personal threats, Numbers, videos and other important things are used for extortion people, which can be posted by some imposters or non-social personals. In spite of the importance of authentication in the social network, a handful number of researches conducted such accessing social network using efficient authentication technique to solve this problem. This study proposed a method to access a social network sites (such as Facebook and twitter) using face recognition techniques at the time of login in the site by Smartphones. Where Local Binary Pattern (LBP) was used to detect users face and the LBP histogram was used for features extraction. The proposed method obtained very promising results in term of accuracy (93.5%) and effectiveness for authentication of user identity.