Biometric data on the edge for secure, smart and user tailored access to cloud services

被引:11
作者
Barra, Silvio [1 ]
Castiglione, Aniello [2 ]
Narducci, Fabio [2 ]
De Marsico, Maria [3 ]
Nappi, Michele [4 ]
机构
[1] Univ Cagliari, Dept Math & Comp Sci, Cagliari, Italy
[2] Univ Naples Parthenope, Dept Sci & Technol, Naples, Italy
[3] Sapienza Univ Rome, Rome, Italy
[4] Univ Salerno, Dept Comp Sci, Salerno, Italy
来源
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE | 2019年 / 101卷
关键词
Edge Computing; Mobile Computing; IoT; Biometric Recognition; Context Awareness; RECOGNITION; SYSTEMS;
D O I
10.1016/j.future.2019.06.019
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
We are living an era in which each of us is immersed in a fully connected environment. The smart devices worn everyday by everyone let the users be projected into the so called IoT world, whose main aim is to provide tools and strategies to solve problems of everyday life as well as to improve well-being and quality of life. Such a goal can be achieved in several ways, but consumer specific services should be provided according to their daily habits, as well as temporary needs. This can be made possible by current mobile devices and their built-in sensors, which can infer the context where the owner operates and the performed activities to build up a user profile. In this work, an architecture for cloud services supply is proposed, based on subject continuous authentication and context (status/activity) recognition. A subject and the context are authenticated/recognised by means of the cyclic recognition of signals captured by the sensors of his/her smartphone, e.g., accelerometer and gyroscope. In order to test the accuracy of the proposed context recognition, the H-MOG dataset has been used, which provides joint acquisitions of status data (Sitting or Walking) related to the activity performed (Reading, Writing, or Navigating Map). (C) 2019 Elsevier B.V. All rights reserved.
引用
收藏
页码:534 / 541
页数:8
相关论文
共 30 条
[1]  
Abate AF, 2018, INT C PATT RECOG, P3120, DOI 10.1109/ICPR.2018.8545797
[2]  
[Anonymous], 2018, 2018 INT WORKSH BIOM, DOI DOI 10.1109/IWBF.2018.8401563
[3]  
[Anonymous], FUTURE GENER COMPUT
[4]  
[Anonymous], FUTURE GENER COMPUT
[5]   Privacy Protection in Biometric-Based Recognition Systems [A marriage between cryptography and signal processing] [J].
Barni, Mauro ;
Droandi, Giulia ;
Lazzeretti, Riccardo .
IEEE SIGNAL PROCESSING MAGAZINE, 2015, 32 (05) :66-76
[6]   Continuous Authentication on Smartphone by Means of Periocular and Virtual Keystroke [J].
Barra, Silvio ;
Marras, Mirko ;
Fenu, Gianni .
NETWORK AND SYSTEM SECURITY (NSS 2018), 2018, 11058 :212-220
[7]   Cloud-Based Biometrics (Biometrics as a Service) for Smart Cities, Nations, and Beyond [J].
Barra, Silvio ;
Castiglione, Aniello ;
De Marsico, Maria ;
Nappi, Michele ;
Choo, Kim-Kwang Raymond .
IEEE CLOUD COMPUTING, 2018, 5 (05) :92-+
[8]   BIOMETRICS-AS-A-SERVICE: CLOUD-BASED TECHNOLOGY, SYSTEMS, AND APPLICATIONS [J].
Barra, Silvio ;
Choo, Kim-Kwang Raymond ;
Nappi, Michele ;
Castiglione, Arcangelo ;
Narducci, Fabio ;
Ranjan, Rajiv .
IEEE CLOUD COMPUTING, 2018, 5 (04) :33-37
[9]   Fusion of physiological measures for multimodal biometric systems [J].
Barra, Silvio ;
Casanova, Andrea ;
Fraschini, Matteo ;
Nappi, Michele .
MULTIMEDIA TOOLS AND APPLICATIONS, 2017, 76 (04) :4835-4847
[10]   Privacy-Preserving Biometric Identification Using Secure Multiparty Computation [J].
Bringer, Julien ;
Chabanne, Herve ;
Patey, Alain .
IEEE SIGNAL PROCESSING MAGAZINE, 2013, 30 (02) :42-52