This article presents a comprehensive analysis behavioral authentication systems based on keystroke dynamics using android mobile devices. Behavioral security authentication is an efficient biometric‐based security system that can be used to authenticate users. It is exploited to strengthen password authentication efficiently and inexpensively because no extra hardware is required in most of these schemes. Keystroke dynamic rhythm uses combinations of timing features and nontiming features that are extracted and processed from several devices such as classical keyboard and built‐in software keyboard in touch screen and smart phone devices. This work presents a comprehensive analysis of using biometric behavioral authentication system‐based on keystroke dynamics. Neural network classifiers are used in this work. The performance results show that keystroke dynamics provides good level in performance measures as a second authentication factor. The distinguishable role for nontiming features in addition to the timing features is demonstrated. These features have a significant role in improving the performance measures. The proposed model achieves low error rate of 0.3% for false acceptance rate, a false rejection of 1.5%, and an equal error rate of 0.9%. These are considered excellent enhancements when compared with previous reported results. Suggestions for future directions, and challenges for using behavioral‐based authentication systems are also highlighted.
Nowadays most systems became computerized and use internet for remote access, including systems which have critical and sensitive data such as banks and governmental institutions. This led to the huge need for a reliable and efficient authentication system to secure data. User authentication is mostly done using passwords. But it is not a sufficient way to use just a password since it has many drawbacks, like guessing them, brute force attacks, key-loggers and social engineering. Additional authentication procedure is needed to enhance password security. Keystroke dynamics is one of the famous behavioral measurements that rely on utilizing the typing rhythm of each individual. It is used to strengthen password authentication in an efficient and cheap way since no hardware will be added. This paper presents a comprehensive survey on research in the last two decades on keystroke dynamics authentication. The objective is to discuss, summarize and provide insightful comparison about the well-known approaches used in keystroke dynamics such as statistical and neural network approaches, as well as offering suggestions and possible future research directions, especially for touch-screen and mobile devices. Keystroke dynamics could provide a second authentication factor for touch screen devices, as they are rapidly increasing in their use and are replacing the classical keyboards in the markets.
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