The Experts below are selected from a list of 315 Experts worldwide ranked by ideXlab platform
P. Pandey - One of the best experts on this subject based on the ideXlab platform.
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Restricting shoulder surfing: a modified graphical Password Technique
International Journal of Research, 2019Co-Authors: P. PandeyAbstract:Graphical Passwords are the ways in which user click on the image or user can select the image to authenticate themselves instead of giving Passwords. This technique is more secure that textual Password techniques. In this article, the shoulder surfing preventive mechanism of graphical Password authentication is given. Finally the Login Password system is proposed to deal with such type of problems. First time, we are introducing a modified approach is given to resolve the shoulder surfing based on recall and recognition based concepts. Usually it is seen that the most common vulnerability of graphical Password is shoulder surfing attack. This research aims to analyze the usability feature of recognition based and recall based graphical Password methods and present a technique to apply an image based Password that is safe from the shoulder surfing attack. In the similar context, the purpose of this paper is to present an alternative way to apply the recall and recognition based technique that will be protective for guess through shoulder surfing. And this graphical technique will be easy to memories the authentication Password and process of authentication.
Joao Baptista Tadanobu Yabuuti - One of the best experts on this subject based on the ideXlab platform.
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user authentication through typing biometrics features
IEEE Transactions on Signal Processing, 2005Co-Authors: Livia C F Araujo, Luiz H R Sucupira, Miguel Gustavo Lizarraga, Lee Luan Ling, Joao Baptista Tadanobu YabuutiAbstract:This paper uses a static keystroke dynamics in user authentication. The inputs are the key down and up times and the key ASCII codes captured while the user is typing a string. Four features (key code, two keystroke latencies, and key duration) were analyzed and seven experiments were performed combining these features. The results of the experiments were evaluated with three types of user: the legitimate, the impostor and the observer impostor users. The best results were achieved utilizing all features, obtaining a false rejection rate of 1.45% and a false acceptance rate of 1.89%. This approach can be used to improve the usual Login-Password authentication when the Password is no more a secret. This paper innovates using four features to authenticate users.
Livia C F Araujo - One of the best experts on this subject based on the ideXlab platform.
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user authentication through typing biometrics features
IEEE Transactions on Signal Processing, 2005Co-Authors: Livia C F Araujo, Luiz H R Sucupira, Miguel Gustavo Lizarraga, Lee Luan Ling, Joao Baptista Tadanobu YabuutiAbstract:This paper uses a static keystroke dynamics in user authentication. The inputs are the key down and up times and the key ASCII codes captured while the user is typing a string. Four features (key code, two keystroke latencies, and key duration) were analyzed and seven experiments were performed combining these features. The results of the experiments were evaluated with three types of user: the legitimate, the impostor and the observer impostor users. The best results were achieved utilizing all features, obtaining a false rejection rate of 1.45% and a false acceptance rate of 1.89%. This approach can be used to improve the usual Login-Password authentication when the Password is no more a secret. This paper innovates using four features to authenticate users.
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ICBA - User Authentication through Typing Biometrics Features
Biometric Authentication, 2004Co-Authors: Livia C F Araujo, Luiz H R Sucupira, Miguel Gustavo Lizarraga, Lee Luan Ling, João Baptista Tadanobu Yabu-utiAbstract:This paper uses a static typing biometrics in user authentication. The inputs are the key down and up times and the key ASCII codes captured while the user is typing a string. Four features (key code, two keystroke latencies and key duration) were analyzed, and, seven experiments were performed combining these features. The results of the experiments were evaluated involving three types of user: the legitimate, the impostor and the observer impostor users. The best results were achieved utilizing all features, obtaining a false rejection rate (FRR) of 1.45% and a false acceptance rate (FAR) of 1.89%. This approach can be used to improve the usual Login-Password authentication when the Password is no more a secret. This paper innovates using the combination of four features to authenticate users.
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Typing Biometrics User Authentication based on Fuzzy Logic
IEEE Latin America Transactions, 2004Co-Authors: Livia C F Araujo, Luiz H R Sucupira, João Baptista Tadanobu Yabu-uti, Gustavo M. Lizarraga, Luan Ling LeeAbstract:This paper uses a fuzzy logic approach in a static typing biometrics user authentication. The inputs are the down and up times, and the ASCII code of the keys that are captured while the user is typing a known string. In this research, it was collected four features (the key code, two keystroke latencies and the key duration) captured in two different strings. The first string was imposed, and the second one was chosen by each user. Seven experiments were developed utilizing a fuzzy logic classifier and the proposed features. The results of the experiments are evaluated in three situations of authentication: the legitimate user, the impostor and the specialist impostor. The best results were achieved utilizing all the features, obtaining a false rejection rate of 3.5% and a false acceptance rate of 2.9%. This approach can be used in the usual Login-Password authentication for improvement of the false acceptance rate, when the Password is no more a secret.In this paper recurrent neural networks are considered to realize traffic prediction in computer network.
Shipra Kumari - One of the best experts on this subject based on the ideXlab platform.
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A Remote Login Password Authentication Scheme Using Row Vector with Biometric
Advances in Intelligent Systems and Computing, 2015Co-Authors: Shipra KumariAbstract:Remote Login authentication is very important to access resources from remote computers to control the illegal access. In this paper, we propose a remote Login authentication scheme based on row vector theorems. In our scheme we use one way function to secure our message. In this scheme the system does not need to reconstruct any term of existing key table when a new user is inserted into a system. A legal user can freely choose and change his Password using smart card. Our scheme is secure against different attacks like replay attack, forged Login attack, Password guessing attack.
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Remote Login Password authentication scheme using tangent theorem on circle
Advances in Intelligent Systems and Computing, 2015Co-Authors: Shipra KumariAbstract:A remote Password authentication scheme based on a circle is proposed in this paper. In this scheme, we use some simple tangent theorem like secant tangent theorem to authenticate the user and the server. The security of this scheme depends on the tangent points located in a plane associated with the circle and tangent line. In our scheme, a legal user can freely choose and change his Password using his smart card.
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ICIT - Remote Login Password Authentication Scheme Based on Cuboid Using Biometric
2014 International Conference on Information Technology, 2014Co-Authors: Shipra KumariAbstract:In this paper, we propose a remote Password authentication scheme based on 3-D geometry with biometric value of a user. It is simple and practically useful and also a legal user can freely choose and change his Password using smart card that contains some information. The security of the system depends on the points on the diagonal of a cuboid in 3D environment. Using biometric value makes the points more secure because the characteristics of the body parts cannot be copied or stolen.
Luiz H R Sucupira - One of the best experts on this subject based on the ideXlab platform.
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user authentication through typing biometrics features
IEEE Transactions on Signal Processing, 2005Co-Authors: Livia C F Araujo, Luiz H R Sucupira, Miguel Gustavo Lizarraga, Lee Luan Ling, Joao Baptista Tadanobu YabuutiAbstract:This paper uses a static keystroke dynamics in user authentication. The inputs are the key down and up times and the key ASCII codes captured while the user is typing a string. Four features (key code, two keystroke latencies, and key duration) were analyzed and seven experiments were performed combining these features. The results of the experiments were evaluated with three types of user: the legitimate, the impostor and the observer impostor users. The best results were achieved utilizing all features, obtaining a false rejection rate of 1.45% and a false acceptance rate of 1.89%. This approach can be used to improve the usual Login-Password authentication when the Password is no more a secret. This paper innovates using four features to authenticate users.
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ICBA - User Authentication through Typing Biometrics Features
Biometric Authentication, 2004Co-Authors: Livia C F Araujo, Luiz H R Sucupira, Miguel Gustavo Lizarraga, Lee Luan Ling, João Baptista Tadanobu Yabu-utiAbstract:This paper uses a static typing biometrics in user authentication. The inputs are the key down and up times and the key ASCII codes captured while the user is typing a string. Four features (key code, two keystroke latencies and key duration) were analyzed, and, seven experiments were performed combining these features. The results of the experiments were evaluated involving three types of user: the legitimate, the impostor and the observer impostor users. The best results were achieved utilizing all features, obtaining a false rejection rate (FRR) of 1.45% and a false acceptance rate (FAR) of 1.89%. This approach can be used to improve the usual Login-Password authentication when the Password is no more a secret. This paper innovates using the combination of four features to authenticate users.
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Typing Biometrics User Authentication based on Fuzzy Logic
IEEE Latin America Transactions, 2004Co-Authors: Livia C F Araujo, Luiz H R Sucupira, João Baptista Tadanobu Yabu-uti, Gustavo M. Lizarraga, Luan Ling LeeAbstract:This paper uses a fuzzy logic approach in a static typing biometrics user authentication. The inputs are the down and up times, and the ASCII code of the keys that are captured while the user is typing a known string. In this research, it was collected four features (the key code, two keystroke latencies and the key duration) captured in two different strings. The first string was imposed, and the second one was chosen by each user. Seven experiments were developed utilizing a fuzzy logic classifier and the proposed features. The results of the experiments are evaluated in three situations of authentication: the legitimate user, the impostor and the specialist impostor. The best results were achieved utilizing all the features, obtaining a false rejection rate of 3.5% and a false acceptance rate of 2.9%. This approach can be used in the usual Login-Password authentication for improvement of the false acceptance rate, when the Password is no more a secret.In this paper recurrent neural networks are considered to realize traffic prediction in computer network.
