Title context-based personal data protection in smart city

Function adjustment and multiple configuration can be realized due to the flexibility.

Chapter 6. Conclusion

Various concepts, applications and technologies are interacting to encompass every aspect of the citizen's life. Understanding this privacy-challenging environment and determine what to protect are the basic requirements for the development of effective personal data protection strategy. This paper elaborates the privacy concerns emerging in smart city construction and proposes a classified personal data protection architecture, which also contains the classification scheme based on data context. The involving principles and techniques are also introduced hierarchically. However, the fact is, it is very difficult to cover each and every aspect of the smart city, because smart city is extremely dynamic, and each service may require different data types and data operations. The specific protection mechanism in each phase, therefore, may be varied on the basis of the core architecture [16]. Data classification is a new trend of data protection. Especially in smart city context, where personal data are collected massively for the realization of city efficiency and friendly, it is nearly impossible for citizens' not to participate in data sharing activities. In this circumstance, to know what is more important, what deserves higher level of protection, become particularly necessary. Therefore, illustration of protective technologies along with a well-defined privacy architecture can contribute to the integration of the many tailored privacy solutions that suitable for different smart city applications and services.

In summary, the study on personal data protection in smart city is in initial stage, since the construction of smart city is still in development and exploration. More researches and progress will be accomplished in recent years. And the limitation of this paper is, it is quite difficult to gather huge volume of anonymized personal data that can match scale of smart city without the support from organizations or enterprises. Meanwhile, in order to train the classifier, it is also required that these data should cover various categories and amount within each category should be balanced without severe difference in quantity. The proposed context-based personal data classification scheme would be better demonstrated with experiment of real data. All in all, hope the systematic analysis and architecture on classified personal data protection in smart city will support comprehensive and customized privacy solutions for smart cities construction.

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Acknowledgement

Upon the completion of the thesis, I would like to take this opportunity to express my sincere gratitude to my supervisor Yevgeni Koucheryary and Professor Michael Komarov, who have given me important guidance on the thesis. Without their help and encouragement, this thesis could not have reached its present stage. Besides, during the study, they have also given me much advice and comments of doing research, which is of great value to my future study and work.

I am deeply obliged to all teachers whose insightful lectures have broadened my scope of vision and help me lay a necessary foundation for writing thesis. In China, there is an old saying that has been spreading for thousands of years: “ОЄС§ДЄЦШУЪЧрК¦”, which tells people the most principle in learning is to respect your teacher. I am so indebted to all instructors who encouraged me in my academy and project which granted me a lot of experience that I will surely benefit from.

My heartful thanks also goes to our coordinator Ekaterina German. It is not easy for me to start a new journey studying and living in Russia with language barrier, but Ekaterina always offers great help with patience whenever needed.

Another pleasure and honor to me in the past two years, is to knowing and getting acquainted with all members in our class. I can always learn a lot from your presentations and projects. And it is very impressive to work and study with you all.

Last but not least, I would like to express my gratitude to all the friends and family members who always support me, willingly discuss with me, and offer valuable advice. I really appreciate it.

My best wishes to you all.

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