Adaptive authentication based on analysis of user behavior

Bakar, Khairul Azmi Abu; Haron, Galoh Rashidah

doi:10.1109/sai.2014.6918248

Cited by 20 publications

(6 citation statements)

References 3 publications

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“…The concept of graphs only benefited in providing basic insights into potential credential mixing risks within the network. Another study proposed an adaptive authentication for Malaysia government e-service, which combines multiple applications with single sign-on capabilities (Bakar & Haron, 2014). The user behavior profiling is generated based on the frequency of attribute values and the approach does not find the correlation between them.…”

Section: Trust Behaviormentioning

confidence: 99%

Application of Machine Learning to User Behavior-Based Authentication in Smartphone and Web

Jayabalan

2022

Applications of Machine Learning and Deep Learning for Privacy and Cybersecurity

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Authentication is the preliminary security mechanism employed in the information system to identify the legitimacy of the user. With technological advancements, hackers with sophisticated techniques easily crack single-factor authentication (username and password). Therefore, organizations started to deploy multi-factor authentication (MFA) to increase the complexity of the access to the system. Despite the MFA increasing the security of the digital service, the usable security should be given equal importance. The user behavior-based authentication provides a means to analyze the user interaction with the system in a non-intrusive way to identify the user legitimacy. This chapter presents a review of user behavior-based authentication in smartphones and websites. Moreover, the review highlights some of the common features, techniques, and evaluation criteria usually considered in the development of user behavior profiling.

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Section: Trust Behaviormentioning

confidence: 99%

Application of Machine Learning to User Behavior-Based Authentication in Smartphone and Web

Jayabalan

2022

Applications of Machine Learning and Deep Learning for Privacy and Cybersecurity

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“…4) Adaptive authentication: Authentication enables an application to identify its users. Adaptive authentication, also known as Risk Based Authentication, is a method for stronger authentication performed by profiling users' behavior and software and hardware usage profiling [18], and whenever a deviation is observed, step up authentication by challenging additional authentication scheme, for example, Two-Factor Authentication, and Multi-Factor Authentication (MFA).…”

Section: Application Defense Mechanismsmentioning

confidence: 99%

Challenges in Protecting Data for Modern Enterprises

Nur¹,

Kettani²

2020

JOEBM

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“…Fang Jing-Li has proposed [4], user authentication is an important part of information security. Bakar and Z. Zhang [5], [6] also proposed that user authentication allow users or systems that require access to prove their identities. Authentication requires supporting information to make sure that the information provided by users is in compliance with validation specifications.…”

Section: A User Authentication Technologymentioning

confidence: 99%

New User Authentication Based on Optical Spectrum and Its Realization of Embedded Systems

Su¹,

Kao²,

Shieh³

et al. 2018

IJCTE

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User authentication (UA) is the first and significant step for users before accessing information services. The most popular and typical approach to UA is based on username/password to identify and authenticate users. The traditional approach is neither convenient and nor reliable. In this paper, a new approach based on optical spectrum is proposed. The authentication code is generated according to optical spectrum to make password secure. Besides, the generated code is renewed after the code has been authenticated. Such a one-time password effectively protects systems from the malicious copy and skimming attacks. A numeric analysis illustrate that the proposed approach have lower crack probability than iris and fingerprint authentication. The proposed UA is realized on an Arduino Nano Board to verify the feasibility. The results illustrate the UA proposed by this study. Have potential to surpass the existing user authentication technology at security. And it is reliable, low-cost and feasible system design.

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Adaptive authentication based on analysis of user behavior

Cited by 20 publications

References 3 publications

Application of Machine Learning to User Behavior-Based Authentication in Smartphone and Web

Application of Machine Learning to User Behavior-Based Authentication in Smartphone and Web

Challenges in Protecting Data for Modern Enterprises

New User Authentication Based on Optical Spectrum and Its Realization of Embedded Systems

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