Inferring Identity Using Accelerometers in Television Remote Controls

Chang, Keh‐Minn; Hightower, Jeffrey; Kveton, Branislav

doi:10.1007/978-3-642-01516-8_11

Cited by 27 publications

(25 citation statements)

References 5 publications

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“…Implicit authentication systems have been proposed based on many different features. These include systems that authenticate the user based on biometrics [36,40,42,50], accelerometers [11], gait recognition [33,23,20], call and SMS pattern [51], location pattern [10,52,9,12,53], keystroke dynamics [14,28,60,38,19,58], proximity to other devices [32,48], and touchscreen dynamics [57,16,21]. Industry products such as Sentry from AdmitOne Security 2 and BehavioMobile from BehavioSec 3 implement implicit authentication.…”

Section: Related Workmentioning

confidence: 99%

Reconciling user privacy and implicit authentication for mobile devices

Shahandashti¹,

Safa²

2015

Computers & Security

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In an implicit authentication system, a user profile is used as an additional factor to strengthen the authentication of mobile users. The profile consists of features that are constructed using the history of user actions on her mobile device over time. The profile is stored on the server and is used to authenticate an access request originated from the device at a later time. An access request will include a vector of recent measurements of the features on the device, that will be subsequently matched against the features stored at the server, to accept or reject the request. The features however include private information such as user location or web sites that have been visited. We propose a privacypreserving implicit authentication system that achieves implicit authentication without revealing information about the usage profiles of the users to the server. We propose an architecture, give a formal security model and a construction with provable security in two settings where: (i) the device follows the protocol, and (ii) the device is captured and behaves maliciously.

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Section: Related Workmentioning

confidence: 99%

Reconciling user privacy and implicit authentication for mobile devices

Shahandashti¹,

Safa²

2015

Computers & Security

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“…Decision trees are popular for their simplicity of use, interpretability, and good runtime performance. Decision trees are popular in applications to recognize: identity / ability (e.g., [8]), interruptibility (e.g., [2,42]), mobility (e.g., [45]), etc.…”

Section: Rulesmentioning

confidence: 99%

Toolkit to support intelligibility in context-aware applications

Lim

Dey

2010

Proceedings of the 12th ACM International Conference on Ubiquitous Computing

103

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Context-aware applications should be intelligible so users can better understand how they work and improve their trust in them. However, providing intelligibility is nontrivial and requires the developer to understand how to generate explanations from application decision models. Furthermore, users need different types of explanations and this complicates the implementation of intelligibility. We have developed the Intelligibility Toolkit that makes it easy for application developers to obtain eight types of explanations from the most popular decision models of context-aware applications. We describe its extensible architecture, and the explanation generation algorithms we developed. We validate the usefulness of the toolkit with three canonical applications that use the toolkit to generate explanations for end-users.

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“…on privacy-preserving biometric systems [22,24,25,29] and implicit authentication systems using accelerometers [9], gait recognition [20], user location [8,30,10,7], and fingerprints [34] can be found in Appendix A.…”

Section: Related Workmentioning

confidence: 99%

Privacy-Preserving Implicit Authentication

Safa

Shahandashti

2014

ICT Systems Security and Privacy Protection

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Abstract. In an implicit authentication system, a user profile is used as an additional factor to strengthen the authentication of mobile users. The profile consists of features that are constructed using the history of user actions on her mobile device over time. The profile is stored on the server and is used to authenticate an access request originated from the device at a later time. An access request will include a vector of recent measurements of the features on the device, that will be subsequently matched against the features stored at the server, to accept or reject the request. The features however include private information such as user location or web sites that have been visited. We propose a privacy-preserving implicit authentication system that achieves implicit authentication without revealing information about the usage profiles of the users to the server. We propose an architecture, give a formal security model and a construction with provable security in two settings where: (i) the device follows the protocol, and (ii) the device is captured and behaves maliciously.

show abstract

Inferring Identity Using Accelerometers in Television Remote Controls

Cited by 27 publications

References 5 publications

Reconciling user privacy and implicit authentication for mobile devices

Reconciling user privacy and implicit authentication for mobile devices

Toolkit to support intelligibility in context-aware applications

Privacy-Preserving Implicit Authentication

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