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  • 學位論文

高效率且安全透過私人手機進行都市環境資料收集

Efficient and Secure People-Centric Urban Environmental Data Collection

指導教授 : 雷欽隆
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摘要


我們提出了一個方案來解決都市中透過私人手機進行環境資料收集所遇到的隱私洩漏問題,安全性問題以及效能問題,因為要透過私人行動裝置為媒介來收集都市的環境資訊時,使用者的隱私權會被洩漏,因此我們給予每個裝置假名並且週期性更新來讓收集者難以辨識出使用者真實身分,除此之外,因為在都市內會有很多區域的行動裝置密度很高,如果讓每個行動裝置都感測並上傳資料,這樣會造成行動裝置浪費電力,而收集者也會收集到很多不必要的資料,也浪費了無線網路資源,所以我們提出一個分散式選舉演算法,讓鄰近區域內只有被選出的幾個行動裝置需要感測跟上傳資料來解決這些問題。最後,因為某些惡意使用者會故意上傳假資料來影響資料收集的正確性,經過實驗證明,我們所提出的方法也有效的解決了這個問題。

並列摘要


We propose a scheme that solves privacy, security, efficiency issues in people-centric urban environmental data collection. When a server wants to collect urban environmental data by private mobile devices carried by users, users will be concern that his location privacy’s may be leaked, so we used periodic pseudonyms to solve this problem. In urban areas, mobile devices may gather together, so the server will receive a lot of redundant data and devices’ power consumption for sensing and uploading data are wasted. We used distributed election protocol to determine a small, specific group of nodes that needs sensing and uploading data. Besides, the scheme can detect malicious nodes and efficiently eliminate malicious nodes’ effects on data collection tasks.

參考文獻


1. Hull, B., et al. CarTel: a distributed mobile sensor computing system. 2006. ACM.
2. Eisenman, S.B., et al., BikeNet: A mobile sensing system for cyclist experience mapping. ACM Transactions on Sensor Networks (TOSN), 2009. 6(1): p. 6.
4. Abdelzaher, T., et al., Mobiscopes for human spaces. Pervasive Computing, IEEE, 2007. 6(2): p. 20-29.
5. Riva, O. and C. Borcea, The Urbanet revolution: Sensor power to the people! Pervasive Computing, IEEE, 2007. 6(2): p. 41-49.
7. Grosky, W., et al., Senseweb: An infrastructure for shared sensing. Multimedia, IEEE, 2007. 14(4): p. 8-13.

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