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雲端中最短路徑之隱匿 = Anonymizing Shortest Pa...
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國立高雄大學資訊管理學系碩士班
雲端中最短路徑之隱匿 = Anonymizing Shortest Paths in the Cloud
Record Type:
Language materials, printed : monographic
Paralel Title:
Anonymizing Shortest Paths in the Cloud
Author:
陳嘉葳,
Secondary Intellectual Responsibility:
國立高雄大學
Place of Publication:
[高雄市]
Published:
撰者;
Year of Publication:
2014[民103]
Description:
39面圖,表 : 30公分;
Subject:
隱私保護
Subject:
privacy preservation
Online resource:
http://handle.ncl.edu.tw/11296/ndltd/33368477530022747086
Notes:
參考書目:面34-35
Notes:
103年12月16日公開
Summary:
近幾年各種公佈資料的隱私保護技術已經被廣泛地研究,而在雲端運算環境下計算最短路徑距離,並同時保護雲端平台上各種資料之隱私,也逐漸受到關注。為了保護1-Neighborhood-d-Radius隱私,目前技術需要事前計算所有起終點之最短路徑,在圖形轉換時消耗大量時間成本。在本研究中,我們提出兩種新的隱私保護概念,(1) k-skip最短路徑隱私,(2)敏感路徑隱私,並結合k-skip最短路徑、節點階層和由下而上的圖形切割等技術,提出較有效率的圖形轉換與雲端環境最短路徑距離計算方法。在實驗分析中,我們探討本研究提出之兩種隱私保護方法對圖形轉換時間與最短路徑距離查詢時間造成之影響,以瞭解本研究提出演算法之特性。實驗結果顯示本研究所提出之演算法,可更有效率地進行圖形轉換與最短路徑距離之查詢。 Preserving privacy on various forms of published data has been studied extensively in recent years. In particular, shortest distance computing in the cloud, while maintaining neighborhood privacy, attracts latest attention. To preserve one-neighborhood privacy, current approach requires the calculation of all-pairs shortest paths in advance, which is time consuming for large graphs. In this work, we propose two new privacy protection concepts, (1) k-skip shortest path privacy and (2) sensitive shortest path privacy. Combining k-skip shortest path, vertex hierarchy and bottom up partitioning, the proposed techniques provide efficient partitioning and query processing. Numerical experiments demonstrating the characteristics of the proposed approach have been conducted, and results show that the proposed techniques can efficiently construct the shortest path sub graphs for the cloud environment and provide efficient queries on shortest path distances.
雲端中最短路徑之隱匿 = Anonymizing Shortest Paths in the Cloud
陳, 嘉葳
雲端中最短路徑之隱匿
= Anonymizing Shortest Paths in the Cloud / 陳嘉葳撰 - [高雄市] : 撰者, 2014[民103]. - 39面 ; 圖,表 ; 30公分.
參考書目:面34-35103年12月16日公開.
隱私保護privacy preservation
雲端中最短路徑之隱匿 = Anonymizing Shortest Paths in the Cloud
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近幾年各種公佈資料的隱私保護技術已經被廣泛地研究,而在雲端運算環境下計算最短路徑距離,並同時保護雲端平台上各種資料之隱私,也逐漸受到關注。為了保護1-Neighborhood-d-Radius隱私,目前技術需要事前計算所有起終點之最短路徑,在圖形轉換時消耗大量時間成本。在本研究中,我們提出兩種新的隱私保護概念,(1) k-skip最短路徑隱私,(2)敏感路徑隱私,並結合k-skip最短路徑、節點階層和由下而上的圖形切割等技術,提出較有效率的圖形轉換與雲端環境最短路徑距離計算方法。在實驗分析中,我們探討本研究提出之兩種隱私保護方法對圖形轉換時間與最短路徑距離查詢時間造成之影響,以瞭解本研究提出演算法之特性。實驗結果顯示本研究所提出之演算法,可更有效率地進行圖形轉換與最短路徑距離之查詢。 Preserving privacy on various forms of published data has been studied extensively in recent years. In particular, shortest distance computing in the cloud, while maintaining neighborhood privacy, attracts latest attention. To preserve one-neighborhood privacy, current approach requires the calculation of all-pairs shortest paths in advance, which is time consuming for large graphs. In this work, we propose two new privacy protection concepts, (1) k-skip shortest path privacy and (2) sensitive shortest path privacy. Combining k-skip shortest path, vertex hierarchy and bottom up partitioning, the proposed techniques provide efficient partitioning and query processing. Numerical experiments demonstrating the characteristics of the proposed approach have been conducted, and results show that the proposed techniques can efficiently construct the shortest path sub graphs for the cloud environment and provide efficient queries on shortest path distances.
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http://handle.ncl.edu.tw/11296/ndltd/33368477530022747086
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