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A Lifelog Data Portfolio for Privacy Protection Based on Dynamic Data Attributes in a Lifelog Service

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Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2017)

Abstract

With the challenge of contemporary mobile computing, quantified self-data need a well-established data service model based on information sources which takes individual privacy into account. This paper presents a lifelog attribute data portfolio (LLADP) that will be used for practically modeling life events and for digitizing such information. In this article, we also propose the privacy implications of lifelogging for each attribute. We designed an attribute portfolio on the basis of the kinds of lifelog services that are already provided in contemporary wearable devices. We aim to map real life models with computerized data models. However, life events may be impossible to completely record because of current device limitations. Thus, we aim to propose a lifelog attribute data portfolio (LLADP) using hybrid cloud management that takes privacy implications and a basic privacy policy into account.

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References

  1. Shimojo, A., Kamada, S., Matsumoto, S., Nakamura, M.: On integrating heterogeneous lifelog services. In: Proceedings of the 12th International Conference on Information Integration and Web-based Applications & Services, Paris, pp. 263–272, Nov 2010. doi:10.1145/1967486.1967529

  2. Gurrin, C., Smeaton, A.F., Doherty, A.R.: Lifelogging: personal big data. In: Found Trends® in Information Retrieval 8(1), 1–125 (2014). https://pdfs.semanticscholar.org/0246/edc6c018faa245e1ec88ba0fe916be2c3081.pdf. Accessed 06 Mar 2017

  3. Ireland, K.: The Digital Divide. http://www.getsaga.com/blog/. Accessed 09 Mar 2017

  4. Ho, Y. sato-Shimokawara, E., Yamaguchi, T.: (2012) Data Mining of life log for developing a user model-based service application. In: 2012 IEEE International Conference on Automation Science and Engineering (CASE), Seoul, pp. 757–760. doi:10.1109/CoASE.2012.6386491

  5. Abe, M., Morinishi, Y., Maeda, A., Aoki, M., Inagaki, H.: A life log collector integrated with a remote-controller for enabling user centric services. IEEE Trans. Consum. Electron. 55(1), 295–302 (2009). doi:10.1109/TCE.2009.4814448

    Article  Google Scholar 

  6. Yang, P., Stankevicius, D., Marozas, V., Deng, Z., Liu, E., Lukosevicius, A., Dong, F., Xu, L., Min, G.: Lifelogging data validation model for internet of things enabled personalized healthcare. IEEE. Trans. Syst. Man Cybern.: Syst. PP(99), 1–15. doi:10.1109/TSMC.2016.2586075

  7. Duane, A., Gupta, R., Zhou, L., Gurrin, C.: Visual insights from personal lifelogs. In: Proceedings of the 12th NTCIR Conference on Evaluation of Information Access Technologies, Tokyo, pp. 386–389 (2016). http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings12/pdf/ntcir/LIFELOG/08-NTCIR12-LIFELOG-DuaneA.pdf. Accessed 10 Mar 2017

  8. Rawassizadeh, R., Tomitsch, M., Wac, K., Tjoa, A.M.: UbiqLog: a generic mobile phone-based life-log framework. Pers. Ubiquit. Comput. 17(4), 621–637 (2013). doi:10.1007/s00779-012-0511-8

    Article  Google Scholar 

  9. Machajdik, J., Hanbury, A., Garz, A., Sablatnig, R.: Affective computing for wearable diary and lifelogging systems: an overview. In: Machine Vision-Research for High Quality Processes and Products-35th Workshop of the Austrian Association for Pattern Recognition. Austrian Computer Society (2011). http://allan.hanbury.eu/lib/exe/fetch.php?media=machajdik_aapr_2011.pdf. Accessed 10 Mar 2017

  10. Boldt, L.C., et al.: Forecasting Nike’s sales using Facebook data. In: 2016 IEEE International Conference on Big Data (Big Data), Washington, DC, pp. 2447–2456 (2016). doi:10.1109/BigData.2016.7840881

  11. Kim, P.H., Giunchiglia, F.: Life logging practice for human behavior modeling. In: 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Seoul, pp. 2873–2878 (2012). doi:10.1109/ICSMC.2012.6378185

  12. Kim, M., Lee, D.W., Kim, K., Kim, J.H., Cho, W.D.: Predicting personal information behaviors with lifelog data. In: 2012, 9th International Conference & Expo on Emerging Technologies for a Smarter World (CEWIT), Incheon, pp. 1–3 (2012). doi:10.1109/CEWIT.2012.6606983

  13. Ryoo, D.W., Bae, C.: Design of the wearable gadgets for life-log services based on UTC. IEEE Trans. Consum. Electron. 53(4), 1477–1482 (2007). doi:10.1109/TCE.2007.4429240

  14. Huang, F.M., Huang, Y.H., Szu, C., Su, A.Y.S., Chen, M.C., Sun, Y.S.: A study of a life logging smartphone app and its power consumption observation in location-based service scenario. In: 2015 IEEE International Conference on Mobile Services, New York, NY, pp. 225–232 (2015). doi:10.1109/MobServ.2015.40

  15. Jalal, A., Kamal, S.: Real-time life logging via a depth silhouette-based human activity recognition system for smart home services. In: 2014 11th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), Seoul, pp. 74–80 (2014). doi:10.1109/AVSS.2014.6918647

  16. Ushiama, T., Watanabe, T.: A life-log search model based on Bayesian network. In: IEEE Sixth International Symposium on Multimedia Software Engineering, pp. 337–343. doi:10.1109/MMSE.2004.11 (2004), Huang, C.L., Huang, Y.H., Chen, J.J.: Life events segmentation based on lifelog recorded by wearable device. In: 2015 International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), Adelaide, SA, pp. 129–132 (2015). doi:10.1109/IIH-MSP.2015.19

  17. Lin, Y.-T.J, Lin, M.-Y.T, Li, K.-C.: Consumer involvement model of fan page: mining from Facebook data of a real celebrity fashion brand. In: 2015 12th International Conference on Service Systems and Service Management (ICSSSM), Guangzhou, pp. 1–6 (2015). doi:10.1109/ICSSSM.2015.7170187

  18. Gurrin, C., Albatal, R., Joho, H., Ishii, K.: A privacy by design approach to lifelogging. In: Digital Enlightenment Yearbook, pp. 49–73 (2014). http://doras.dcu.ie/20505/1/Gurrin.pdf. Accessed 09 Mar 2017

  19. Beck, M., Hao, W., Campan, A.: Accelerating the mobile cloud: using amazon mobile analytics and k-means clustering. In: 2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA, pp. 1–7 (2017). doi:10.1109/CCWC.2017.7868372

  20. Huang, C.L., Huang, Y.H., Chen, J.J.: Life events segmentation based on lifelog recorded by wearable device. In: 2015 International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), Adelaide, SA, pp. 129–132 (2015). doi:10.1109/IIH-MSP.2015.19

  21. Project Management Institute: A Guide to the Project Management Body of Knowledge. http://www.cs.bilkent.edu.tr/~cagatay/cs413/PMBOK.pdf. Accessed 23 Apr 2017

  22. Giunchiglia, F., Kim, P.H.: Lifelog data model and management: study on research challenges. Int. J. Comput. Inf. Syst. Industr. Manage. Appl. 5, 115–125 (2012). ISSN 2150-7988

    Google Scholar 

  23. Personal Information Protection Commission: About personal information protection law. https://www.ppc.go.jp/personal/general/ (in Japanese). Accessed 23 Apr 2017

  24. Tanimoto, S., Sakurada, Y., Seki, Y., Iwashita, M., Matsui, S., Sato, H., Kanai, A.: A study of data management in hybrid cloud configuration. In: 14th IEEE/ACIS, SNPD2013, pp. 381–386

    Google Scholar 

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Acknowledgements

This work was supported by the Japan Society for the Promotion of Science (JSPS, KAKENHI Grant Number 15H02783).

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Correspondence to Shigeaki Tanimoto .

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Chertchom, P. et al. (2018). A Lifelog Data Portfolio for Privacy Protection Based on Dynamic Data Attributes in a Lifelog Service. In: Lee, R. (eds) Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing. SNPD 2017. Studies in Computational Intelligence, vol 721. Springer, Cham. https://doi.org/10.1007/978-3-319-62048-0_8

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  • DOI: https://doi.org/10.1007/978-3-319-62048-0_8

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