Biblio

Adaptive authentication systems identify and enforce suitable methods to verify that someone (user) or something (device) is eligible to access a service or a resource. An authentication method is usually adapted in response to changes in the security risk or the user's behaviour. Previous work on adaptive authentication systems provides limited guidance about i) what and how contextual factors can affect the selection of an authentication method; ii) which requirements are relevant to an adaptive authentication system and iii) how authentication methods can affect the satisfaction of the relevant requirements. In this paper, we provide a holistic framework informed by previous research to characterize the adaptive authentication problem and support the development of an adaptive authentication system. Our framework explicitly considers the contextual factors that can trigger an adaptation, the requirements that are relevant during decision making and their trade-offs, as well as the authentication methods that can change as a result of an adaptation. From the gaps identified in the literature, we elicit a set of challenges that can be addressed in future research on adaptive authentication.

{In the last few decades, Internet of things (IOT) is one of the key elements in industrial revolution 4.0 that used mart phones as one of the best technological advances' intelligent device. It allows us to have power over devices without people intervention, either remote or voice control. Therefore, the “Smart Radar Door “system uses a microcontroller and mobile Bluetooth module as an automation of smart door lock system. It is describing the improvement of a security system integrated with an Android mobile phone that uses Bluetooth as a wireless connection protocol and processing software as a tool in order to detect any object near to the door. The mob ile device is required a password as authentication method by using microcontroller to control lock and unlock door remotely. The Bluetooth protocol was chosen as a method of communication between microcontroller and mobile devices which integrated with many Android devices in secured protocol}.

Dependence of the individuals on the Internet for performing the several actions require secure data communication. Thus, the reliable data communication improves the confidentiality. As, enhanced security leads to reliable and faster communication. To improve the reliability and confidentiality, there is dire need of fully secured authentication method. There are several methods of password protections were introduced to protect the confidentiality and reliability. Most of the existing methods are based on alphanumeric approaches, but few methods provide the dual authentication process. In this paper, we introduce improved graphical password authentication using Twofish Encryption and Visual Cryptography (TEVC) method. Our proposed TEVC is unpredictably organized as predicting the correct graphical password and arranging its particles in the proper order is harder as compared to traditional alphanumeric password system. TEVC is tested by using JAVA platform. Based on the testing results, we confirm that proposed TEVC provides secure authentication. TEVC encryption algorithm detected as more prudent and possessing lower time complexity as compared to other known existing algorithms message code confirmation and fingerprint scan with password.

Authentication is one of the key aspects of securing applications and systems alike. While in most existing systems this is achieved using usernames and passwords it has been continuously shown that this authentication method is not secure. Studies that have been conducted have shown that these systems have vulnerabilities which lead to cases of impersonation and identity theft thus there is need to improve such systems to protect sensitive data. In this research, we explore the combination of the user's location together with traditional usernames and passwords as a multi factor authentication system to make authentication more secure. The idea involves comparing a user's mobile device location with that of the browser and comparing the device's Bluetooth key with the key used during registration. We believe by leveraging existing technologies such as Bluetooth and GPS we can reduce implementation costs whilst improving security.

Standard classification procedures of both data mining and multivariate statistics are sensitive to the presence of outlying values. In this paper, we propose new algorithms for computing regularized versions of linear discriminant analysis for data with small sample sizes in each group. Further, we propose a highly robust version of a regularized linear discriminant analysis. The new method denoted as MWCD-L2-LDA is based on the idea of implicit weights assigned to individual observations, inspired by the minimum weighted covariance determinant estimator. Classification performance of the new method is illustrated on a detailed analysis of our pilot study of authentication methods on computers, using individual typing characteristics by means of keystroke dynamics.