Affiliation:
1. National Institute of Technology, Kurukshetra, India
Abstract
This chapter discusses a model that allows the user to access social networking sites through login using smart phone-based biometric authentication. Currently, social networking websites permit the user to access their page through login and some sites provide auto fill system to login into users account through browser by permit. The browser saves the password in password protected space and automatically auto fills the password to access the account by user. This facility is not highly reliable due to the auto fill system for laptop users. When someone uses the laptop of others and visits any website, the auto fill system opens the content with saved password. Secondly, elderly people have problems logging into today's websites. To remember the password for every account is very difficult for elderly people. This chapter describes a model for security and authenticity. Authors used a hybrid model with android as the application with fingerprint authentication and chrome extension as the auto fill process for user access.
Reference69 articles.
1. Aggarwal, A., Rajadesingan, A., & Kumaraguru, P. (2012). PhishAri: Automatic realtimephishing detection on twitter, eCrime Res. Summit, eCrime, pp. 1–12.
2. Ahmed, E., DeLuca, B., Hirowski, E., Magee, C., Tang, I., & Coppola, J. F. (2017, May). Biometrics: Password replacement for elderly? In Proceedings 2017 IEEE Long Island Systems, Applications, and Technology Conference (LISAT), (pp. 1-6). IEEE.
3. Ala’M, A. Z., & Faris, H. (2017, April). Spam profile detection in social networks based on public features. In Proceedings 2017 8th International Conference on Information and Communication Systems (ICICS), (pp. 130-135). IEEE.
4. Toward Detecting Malicious Links in Online Social Networks through User Behavior
5. DNS rule-based schema to botnet detection