The purpose driven privacy preservation for accelerometer-based activity recognition

[1]  Dan Meng,et al.  An Information-Aware Privacy-Preserving Accelerometer Data Sharing , 2017, ICPCSEE.

[2]  Kamalika Chaudhuri,et al.  Composition properties of inferential privacy for time-series data , 2017, 2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[3]  Jorge Gonçalves,et al.  A data hiding approach for sensitive smartphone data , 2016, UbiComp.

[4]  Patrick Olivier,et al.  Beyond activity recognition: skill assessment from accelerometer data , 2015, UbiComp.

[5]  Lama Nachman,et al.  Unobtrusive gait verification for mobile phones , 2014, SEMWEB.

[6]  Fady Alajaji,et al.  Notes on information-theoretic privacy , 2014, 2014 52nd Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[7]  Mani B. Srivastava,et al.  ipShield: A Framework For Enforcing Context-Aware Privacy , 2014, NSDI.

[8]  Muriel Médard,et al.  From the Information Bottleneck to the Privacy Funnel , 2014, 2014 IEEE Information Theory Workshop (ITW 2014).

[9]  Weng-Keen Wong,et al.  Physical Activity Recognition from Accelerometer Data Using a Multi-Scale Ensemble Method , 2013, IAAI.

[10]  Tadayoshi Kohno,et al.  SensorSift: balancing sensor data privacy and utility in automated face understanding , 2012, ACSAC '12.

[11]  Darakhshan J. Mir.  Information-Theoretic Foundations of Differential Privacy , 2012, FPS.

[12]  Flávio du Pin Calmon,et al.  Privacy against statistical inference , 2012, 2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[13]  David Leoni,et al.  Non-interactive differential privacy: a survey , 2012, WOD.

[14]  Xingshe Zhou,et al.  Energy Efficient Activity Recognition Based on Low Resolution Accelerometer in Smart Phones , 2012, GPC.

[15]  Jun Han,et al.  ACCessory: password inference using accelerometers on smartphones , 2012, HotMobile '12.

[16]  Ke Wang,et al.  Inferential or Differential: Privacy Laws Dictate , 2012, ArXiv.

[17]  Jun Han,et al.  ACComplice: Location inference using accelerometers on smartphones , 2012, 2012 Fourth International Conference on Communication Systems and Networks (COMSNETS 2012).

[18]  H. Vincent Poor,et al.  A Theory of Privacy and Utility in Databases , 2011, ArXiv.

[19]  Frank McSherry,et al.  Probabilistic Inference and Differential Privacy , 2010, NIPS.

[20]  John Krumm,et al.  A survey of computational location privacy , 2009, Personal and Ubiquitous Computing.

[21]  Ciaran O'Driscoll,et al.  Privacy in context: Privacy issues in Ubiquitous Computing applications , 2008, 2008 Third International Conference on Digital Information Management.

[22]  Naftali Tishby,et al.  The information bottleneck method , 2000, ArXiv.

[23]  Naftali Tishby,et al.  Agglomerative Information Bottleneck , 1999, NIPS.

[24]  Jiguo Yu,et al.  Latent-Data Privacy Preserving With Customized Data Utility for Social Network Data , 2018, IEEE Transactions on Vehicular Technology.

[25]  G. C. Garriga,et al.  Consumer Journey Analytics in the Context of Data Privacy and Ethics , 2018 .

[26]  Gary M. Weiss,et al.  The Benefits of Personalized Smartphone-Based Activity Recognition Models , 2014, SDM.

[27]  Duc A. Tran,et al.  The 11th International Conference on Mobile Systems and Pervasive Computing (MobiSPC-2014) A Study on Human Activity Recognition Using Accelerometer Data from Smartphones , 2014 .

[28]  H. Kriegel,et al.  Activity Recognition on 3 D Accelerometer Data ( Technical Report ) , 2013 .