ITSME: Multi-modal and Unobtrusive Behavioural User Authentication for Smartphones

Buriro, Attaullah; Crispo, Bruno; Frari, Filippo Del; Klardie, Jeffrey; Wrona, Konrad

doi:10.1007/978-3-319-29938-9_4

Cited by 15 publications

(17 citation statements)

References 19 publications

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“…Several behavioral footprints including swiping [5], typing [4], walking [6], arm movements [7], and their possible fusion [8,9] have been studied in the past for authenticating individuals continuously [13]. The phone movement pattern was studied by Kumar et al [8], Sitova et al [9] and, Buriro et al [14] recently. Sitova et.…”

Section: Related Workmentioning

confidence: 99%

Continuous user authentication via unlabeled phone movement patterns

Kumar

Kundu

Shukla

et al. 2017

2017 IEEE International Joint Conference on Biometrics (IJCB)

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In this paper, we propose a novel continuous authentication system for smartphone users. The proposed system entirely relies on unlabeled phone movement patterns collected through smartphone accelerometer. The data was collected in a completely unconstrained environment over five to twelve days. The contexts of phone usage were identified using k-means clustering. Multiple profiles, one for each context, were created for every user. Five machine learning algorithms were employed for classification of genuine and impostors. The performance of the system was evaluated over a diverse population of 57 users. The mean equal error rates achieved by Logistic Regression, Neural Network, kNN, SVM, and Random Forest were 13.7%, 13.5%, 12.1%, 10.7%, and 5.6% respectively. A series of statistical tests were conducted to compare the performance of the classifiers. The suitability of the proposed system for different types of users was also investigated using the failure to enroll policy. 1

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Section: Related Workmentioning

confidence: 99%

Continuous user authentication via unlabeled phone movement patterns

Kumar

Kundu

Shukla

et al. 2017

2017 IEEE International Joint Conference on Biometrics (IJCB)

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“…Although the behavioral modalities are not considered to be unique enough for identification purposes, they have proved to be sufficiently unique for user authentication [112,113]. One or more modalities can be combined to increase their accuracy and enhance their usability.…”

Section: Something You Are: Behavioral Biometrics Behavioral Biometricsmentioning

confidence: 99%

“…is was a bimodal behavioral biometric based on user's smartphone holding style, by examining the hand and finger micromovements of users, while the users were signing on device's touchscreen. In an another approach, Buriro et al [113] proposed multimodal behavioral biometrics (swipe, pickup movement, and voice) for user authentication on smartphones and reported 7.57% HTER in an experiment involving 26 participants.…”

Section: Something You Are: Behavioral Biometrics Behavioral Biometricsmentioning

confidence: 99%

“…Authentication types Usability pros and cons indicated Security solutions or concerns reported Touch [9,113]; keystroke [115]; hold [8]; gait [116][117][118]; behavior profiling [119] Adaptive; continuous; multimodal;…”

Section: Modalitiesmentioning

confidence: 99%

“…risk-based; transparent [3,5,10,113,[119][120][121] [8,12,29,112,113,[115][116][117][122][123][124][125][126][127] end], P, auth}" holding of 3 prime attributes, where "begin" is authorization start date, "end" is either the constant ∞, or a deauthorization date after the start date, "P" is the duration of a session, and "auth" is an authorization function. Feng et al [4] determined that periodic authentication or automatic logouts are more detrimental while one-shot authentication solutions are prone to a wide variety of attacks.…”

Section: Modalitiesmentioning

confidence: 99%

See 2 more Smart Citations

Demystifying Authentication Concepts in Smartphones: Ways and Types to Secure Access

Gupta

Buriro

Crispo

2018

Mobile Information Systems

Self Cite

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Smartphones are the most popular and widespread personal devices. Apart from their conventional use, that is, calling and texting, they have also been used to perform multiple security sensitive activities, such as online banking and shopping, social networking, taking pictures, and e-mailing. On a positive side, smartphones have improved the quality of life by providing multiple services that users desire, for example, anytime-anywhere computing. However, on the other side, they also pose security and privacy threats to the users' stored data. User authentication is the first line of defense to prevent unauthorized access to the smartphone. Several authentication schemes have been proposed over the years; however, their presentation might be perplexing to the new researchers to this domain, under the shade of several buzzwords, for example, active, continuous, implicit, static, and transparent, being introduced in academic papers without comprehensive description. Moreover, most of the reported authentication solutions were evaluated mainly in terms of accuracy, overlooking a very important aspect-the usability. is paper surveys various types and ways of authentication, designed and developed primarily to secure the access to smartphones and attempts to clarify correlated buzzwords, with the motivation to assist new researchers in understanding the gist behind those concepts. We also present the assessment of existing user authentication schemes exhibiting their security and usability issues.

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Behavioral Biometrics in Mobile Banking and Payment Applications

Kałużny

2019

Business Information Systems Workshops

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ITSME: Multi-modal and Unobtrusive Behavioural User Authentication for Smartphones

Cited by 15 publications

References 19 publications

Continuous user authentication via unlabeled phone movement patterns

Continuous user authentication via unlabeled phone movement patterns

Demystifying Authentication Concepts in Smartphones: Ways and Types to Secure Access

Behavioral Biometrics in Mobile Banking and Payment Applications

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