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Privacy-Enabled Smart Home Framework with Voice Assistant

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Abstract

Smart home environment plays a prominent role in improving the quality of life of the residents by enabling home automation, health care and safety through various Internet of Things (IoT) devices. However, a large amount of data generated by sensors in a smart home environment heighten security and privacy concerns among potential users. Some of the data can be sensitive as it contains information about users’ private activities, location, behavioural patterns and health status. Other concerns of the users are towards the distribution and sharing of data to third parties. In this chapter, we propose privacy-enabled smart home framework consisting of three major components: activity recognition and occupancy detection, privacy-preserving data management and voice assistant. The proposed platform includes unobtrusive sensors for multiple occupancy detection and activity recognition. The privacy-enabled voice assistant performs interaction with smart home. We also present a detailed description of system architecture with service middleware.

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References

  1. Adadi A, Berrada M (2018) Peeking inside the black-box: a survey on Explainable Artificial Intelligence (XAI). IEEE Access 6:52138–52160

    Article  Google Scholar 

  2. Ahmad J, Larijani H, Emmanuel R, Mannion M, Javed A (2018) Occupancy detection in non-residential buildings—a survey and novel privacy preserved occupancy monitoring solution. Appl Comput Inform. https://doi.org/10.1016/j.aci.2018.12.001

  3. Apthorpe N, Huang DY, Reisman D, Narayanan A, Feamster N (2018) Keeping the smart home private with smart(er) IoT traffic shaping. arXiv preprint arXiv:181200955

    Google Scholar 

  4. Bos JW, Lauter K, Naehrig M (2014) Private predictive analysis on encrypted medical data. J Biomed Inform 50:234–243

    Article  Google Scholar 

  5. Chen H, Liu X, Yin D, Tang J (2017) A survey on dialogue systems: recent advances and new frontiers. ACM SIGKDD Explor Newsl 19(2):25–35

    Article  Google Scholar 

  6. Chen L, Nugent C, Okeyo G (2014) An ontology-based hybrid approach to activity modeling for smart homes. IEEE Trans Hum Mach Syst 44(1):92–105

    Article  Google Scholar 

  7. Chen Z, Jiang C, Xie L (2018) Building occupancy estimation and detection: a review. Energy Build 169:260–270

    Article  Google Scholar 

  8. Das A, Degeling M, Wang X, Wang J, Sadeh N, Satyanarayanan M (2017) Assisting users in a world full of cameras: a privacy-aware infrastructure for computer vision applications. In: 2017 IEEE conference on computer vision and pattern recognition workshops (CVPRW), IEEE, pp 1387–1396

    Google Scholar 

  9. Dwork C (2011) Differential privacy. In: Encyclopedia of cryptography and security, pp 338–340

    Google Scholar 

  10. Fuxreiter T, Mayer C, Hanke S, Gira M, Sili M, Kropf J (2010) A modular platform for event recognition in smart homes. In: The 12th IEEE international conference on e-health networking, applications and services, IEEE, pp 1–6

    Google Scholar 

  11. GDPR (2018) General Data Protection Regulation (GDPR) final text neatly arranged. [online] Available at: https://www.gdpr-info.eu/. Accessed 16 Apr 2019

  12. Holzinger A, Biemann C, Pattichis CS, Kell DB (2017) What do we need to build explainable AI systems for the medical domain? arXiv preprint arXiv:171209923

    Google Scholar 

  13. Holzinger A, Kieseberg P, Weippl E, Tjoa AM (2018) Current advances, trends and challenges of machine learning and knowledge extraction: from machine learning to explainable AI. In: International cross-domain conference for machine learning and knowledge extraction. Springer, Cham, pp 1–8

    Google Scholar 

  14. Jia R, Dong R, Sastry SS, Sapnos CJ (2017) Privacy-enhanced architecture for occupancy-based HVAC control. In: 2017 ACM/IEEE 8th international conference on cyber-physical systems (ICCPS), IEEE, pp 177–186

    Google Scholar 

  15. Jung Y (2017) Hybrid-aware model for senior wellness service in smart home. Sensors 17(5):1182

    Article  Google Scholar 

  16. Liu B, Andersen MS, Schaub F, Almuhimedi H, Zhang SA, Sadeh N, Agarwal Y, Acquisti A (2016) Follow my recommendations: a personalized privacy assistant for mobile app permissions. In: Twelfth symposium on usable privacy and security (SOUPS 2016), pp 27–41

    Google Scholar 

  17. Machado E, Singh D, Cruciani F, Chen L, Hanke S, Salvago F, Kropf J, Holzinger A (2018) A conceptual framework for adaptive user interfaces for older adults. In: 2018 IEEE international conference on pervasive computing and communications workshops (PerCom Workshops), IEEE, pp 782–787

    Google Scholar 

  18. Merdivan E, Vafeiadis A, Kalatzis D, Henke S, Kropf J, Votis K, Giakoumis D, Tzovaras D, Chen, L, Hamzaoui R, Geist M (2018) Image-based natural language understanding using 2D convolutional neural networks. arXiv preprint arXiv:181010401

    Google Scholar 

  19. Mittelstadt B, Russell C, Wachter S (2018) Explaining explanations in AI. arXiv preprint arXiv:181101439

    Google Scholar 

  20. Mnih V, Kavukcuoglu K, Silver D, Rusu AA, Veness J, Bellemare MG, Graves A, Riedmiller M, Fidjeland AK, Ostrovski G, Petersen S (2015) Human-level control through deep reinforcement learning. Nature 518(7540):p529

    Article  Google Scholar 

  21. Monteriù A, Prist M, Frontoni E, Longhi S, Pietroni F, Casaccia S, Scalise L, Cenci A, Romeo L, Berta R, Pescosolido L (2018) A smart sensing architecture for domestic monitoring: methodological approach and experimental validation. Sensors 18(7):p2310

    Article  Google Scholar 

  22. Naehrig M, Lauter K, Vaikuntanathan V (2011) Can homomorphic encryption be practical? In: Proceedings of the 3rd ACM workshop on cloud computing security workshop, ACM, pp 113–124

    Google Scholar 

  23. Okeyo G, Chen L, Wang H (2014) Combining ontological and temporal formalisms for composite activity modelling and recognition in smart homes. Future Gener Comput Syst 39:29–43

    Article  Google Scholar 

  24. Park Y, Kang S, Seo J (2018) An efficient framework for development of task-oriented dialog systems in a smart home environment. Sensors 18(5):1581

    Article  Google Scholar 

  25. Pathak M, Rane S, Sun W, Raj B (2011) Privacy preserving probabilistic inference with hidden Markov models. In: 2011 IEEE international conference on acoustics, speech and signal processing (ICASSP), IEEE, pp 5868–5871

    Google Scholar 

  26. Pathak MA, Raj B (2013) Privacy-preserving speaker verification and identification using gaussian mixture models. IEEE Trans Audio Speech Lang Process 21(2):397–406

    Article  Google Scholar 

  27. Pieraccini R, Huerta J (2005) Where do we go from here? Research and commercial spoken dialog systems. In: 6th SIGdial workshop on discourse and dialogue

    Google Scholar 

  28. Psychoula I, Merdivan E, Singh D, Chen L, Chen F, Hanke S, Kropf J, Holzinger A, Geist M (2018) A deep learning approach for privacy preservation in assisted living. In: 2018 IEEE international conference on pervasive computing and communications workshops (PerCom workshops), IEEE, pp 710–715

    Google Scholar 

  29. Psychoula I, Singh D, Chen L, Chen F, Holzinger A, Ning H (2018) Users’ privacy concerns in IoT based applications. In: 2018 IEEE SmartWorld, ubiquitous intelligence & computing, advanced & trusted computing, scalable computing & communications, cloud & big data computing, internet of people and smart city innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), IEEE, pp 1887–1894

    Google Scholar 

  30. Ribeiro MT, Singh S, Guestrin C (2016) Why should i trust you? Explaining the predictions of any classifier. In: Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining, ACM, pp 1135–1144

    Google Scholar 

  31. Serban IV, Lowe R, Henderson P, Charlin L, Pineau J (2015) A survey of available corpora for building data-driven dialogue systems. arXiv preprint arXiv:151205742

    Google Scholar 

  32. Singh D, Merdivan E, Hanke S, Kropf J, Geist M, Holzinger A (2017) Convolutional and recurrent neural networks for activity recognition in smart environment. In: Towards integrative machine learning and knowledge extraction. Springer, Cham, pp 194–205

    Chapter  Google Scholar 

  33. Singh D, Merdivan E, Psychoula I, Kropf J, Hanke S, Geist M, Holzinger A (2017) Human activity recognition using recurrent neural networks. In: International cross-domain conference for machine learning and knowledge extraction. Springer, Cham, pp 267–274

    Google Scholar 

  34. Singh D, Psychoula I, Kropf J, Hanke S, Holzinger A (2018) Users’ perceptions and attitudes towards smart home technologies. In: International conference on smart homes and health telematics. Springer, Cham, pp 203–214

    Google Scholar 

  35. Sivaraman V, Gharakheili HH, Vishwanath A, Boreli R, Mehani O (2015) Network-level security and privacy control for smart-home IoT devices. In: 2015 IEEE 11th international conference on wireless and mobile computing, networking and communications (WiMob), IEEE, pp 163–167

    Google Scholar 

  36. Sutskever I, Vinyals O, Le, QV (2014) Sequence to sequence learning with neural networks. In: Advances in neural information processing systems, pp 3104–3112

    Google Scholar 

  37. Wang D, Yang Q, Abdul A, Lim BY (2019) Designing theory-driven user-centric explainable AI. In: Proceedings of the SIGCHI conference on human factors in computing systems CHI, vol 19

    Google Scholar 

  38. Wang J, Chen Y, Hao S, Peng X, Hu L (2019) Deep learning for sensor-based activity recognition: a survey. Pattern Recogn Lett 119:3–11

    Article  Google Scholar 

  39. Xie P, Bilenko M, Finley T, Gilad-Bachrach R, Lauter K, Naehrig M (2014) Crypto-nets: neural networks over encrypted data. arXiv preprint arXiv:14126181

    Google Scholar 

  40. Yang J, Zou H, Jiang H, Xie L (2018) Device-free occupant activity sensing using WiFi-enabled IoT devices for smart homes. IEEE Internet Things J 5(5):3991–4002

    Article  Google Scholar 

  41. Zheng S, Apthorpe N, Chetty M, Feamster N (2018) User perceptions of smart home IoT privacy. Proc ACM Hum-Comput Interact 2(CSCW):200

    Article  Google Scholar 

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Acknowledgements

This work has been funded by the European Union Horizon2020 MSCA ITN ACROSSING project (GA no. 616757). The authors would like to thank the members of the project’s consortium for their valuable inputs.

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Correspondence to Deepika Singh .

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Singh, D. et al. (2020). Privacy-Enabled Smart Home Framework with Voice Assistant. In: Chen, F., García-Betances, R., Chen, L., Cabrera-Umpiérrez, M., Nugent, C. (eds) Smart Assisted Living. Computer Communications and Networks. Springer, Cham. https://doi.org/10.1007/978-3-030-25590-9_16

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  • DOI: https://doi.org/10.1007/978-3-030-25590-9_16

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