Unobtrusive Multimodal Biometrics for Ensuring Privacy and Information Security with Personal Devices

Vildjiounaite, Elena; Mäkelä, Satu-Marja; Lindholm, Mikko; Riihimäki, Reima; Kyllönen, Vesa; Mäntyjärvi, Jani; Ailisto, Heikki

doi:10.1007/11748625_12

Cited by 58 publications

(44 citation statements)

References 17 publications

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“…They also report significant improvements in identification performance that can stem from using dynamic video information instead of static image snapshots on a database of 35 different people. Highlighting the privacy concerns of video recording discussed in Bohn et al [27] and reliability issues of face recognition techniques for user authentication, Vildjiounaite et al [28], deploy a fusion of accelerometer based gait recognition and speaker recognition as an unobtrusive and marginally privacy-threatening means of user authentication with personal mobile devices. They have reported improved performance in the combination mode as opposed to individual modalities for a user base of 31.…”

Section: Biometrics In Smart Environmentsmentioning

confidence: 99%

Biometrics Driven Smart Environments: Abstract Framework and Evaluation

Menon

Jayaraman

Govindaraju

Ubiquitous Intelligence and Computing

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Abstract. We present an abstract framework for 'smart indoor environments' that are monitored unobtrusively by biometrics capture devices, such as video cameras, microphones, etc. Our interest is in developing smart environments that keep track of their occupants and are capable of answering questions about the whereabouts of the occupants. We abstract the smart environment by a state transition system: Each state records a set of individuals who are present in various zones of the environment. Since biometric recognition is inexact, state information is probabilistic in nature. An event abstracts a biometric recognition step, and the transition function abstracts the reasoning necessary to effect state transitions. In this manner, we are able to accommodate different types of biometric sensors and also different criteria for state transitions. We define the notions of 'precision' and 'recall' of a smart environment in terms of how well it is capable of identifying occupants. We have developed a prototype smart environment based upon our proposed concepts, and provide experimental results in this paper. Our conclusion is that the state transition model is an effective abstraction of a smart environment and serves as a basis for integrating various recognition and reasoning capabilities.

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Section: Biometrics In Smart Environmentsmentioning

confidence: 99%

Biometrics Driven Smart Environments: Abstract Framework and Evaluation

Menon

Jayaraman

Govindaraju

Ubiquitous Intelligence and Computing

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“…Some of these projects focus on keeping sensed data such as location information private [33], while other projects are designing devices that can act as secure keys for providing and receiving personal information [184]. In lieu of transporting specialized devices, biometric information can be used to access sensors and collected information [165].…”

Section: Privacy and Security Challengesmentioning

confidence: 99%

Ambient intelligence: Technologies, applications, and opportunities

Cook

Augusto

Jakkula

2009

Pervasive and Mobile Computing

822

443

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“…After the appearance of smartphones that contain sophisticated sensors such as accelerometers and global positioning system (GPS) functionality, the trend of applying context awareness in the research field of user authentication began to take place. Typical examples are shown in the application of recognizing gait with an accelerometer on a smartphone while considering the position the smartphone is being held in [13]- [16]. In these examples, the difference in authentication accuracy was evaluated in specific usage environments, namely, different holding positions; however, the idea of the context awareness shown in [12], where an authentication algorithm is adjusted in accordance with a user's context, has still yet to be reached.…”

Section: Related Workmentioning

confidence: 99%

Toward More Secure and Convenient User Authentication in Smart Device Era

Yoshida

Ohki

2017

IEICE Trans. Inf. & Syst.

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SUMMARY With the rapid spread of smart devices, such as smartphones and tablet PCs, user authentication is becoming increasingly important because various kinds of data concerning user privacy are processed within them. At present, in the case of smart devices, password-based authentication is frequently used; however, biometric authentication has attracted more attention as a user authentication technology. A smart device is equipped with various sensors, such as cameras, microphones, and touch panels, many of which enable biometric information to be obtained. While the function of biometric authentication is available in many smart devices, there remain some problems to be addressed for more secure and convenient user authentication. In this paper, we summarize the current problems with user authentication on smart devices and propose a novel user authentication system based on the concept of context awareness to resolve these problems. We also present our evaluation of the performance of the system by using biometric information that was acquired from smart devices. The evaluation demonstrates the effectiveness of our system.

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Unobtrusive Multimodal Biometrics for Ensuring Privacy and Information Security with Personal Devices

Cited by 58 publications

References 17 publications

Biometrics Driven Smart Environments: Abstract Framework and Evaluation

Biometrics Driven Smart Environments: Abstract Framework and Evaluation

Ambient intelligence: Technologies, applications, and opportunities

Toward More Secure and Convenient User Authentication in Smart Device Era

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