臺灣博碩士論文加值系統

隨著智慧型行動裝置的普及使用、網路技術的進步與雲端運算環境的發展，傳統資訊隱藏技術的應用需求，例如，數位浮水印、數位證據與數位鑑識等等，將面臨新的挑戰。根據國際數據資訊(International Data Corporation, IDC) 研究顯示，未來的數位資料量將會以每兩年成長一倍的速度迅速增加，在數位資料量與日俱增的情況下，傳統的電腦已逐漸沒辦法負荷。因此，結合雲端運算分散式計算特性，發展具備處理龐大數量數位資料能力的雲端運算資訊隱藏技術將是一
個值得探討的議題。
本論文首先探討資訊隱藏演算法應用雲端運算 MapReduce 模型時，其通用包裝的調整方式，並以理論基礎較為成熟的 Least Significant Bit 」LSB)為例，實作出雲端運算資訊隱藏技術的核心功能。本論文所實作之雲端運算資訊隱藏技術，除與傳統方法作效能比較之外，並針對不同的載體影像大小、載體影像數量
及叢集節點規模等情況，實際測量及分析其對雲端運算資訊隱藏技術執行時間的影響。

誌謝.................................................................................................................................i
摘要................................................................................................................................ii
Abstract ........................................................................................................................ iii
第一章 緒論..................................................................................................................1
1.1 研究動機及背景............................................................................................1
1.2 研究目的........................................................................................................4
1.3 論文架構........................................................................................................5
第二章 背景知識與相關研究......................................................................................6
2.1 雲端運算與資訊隱藏相關研究....................................................................6
2.1.1 資訊隱藏技術跟雲端運算關係........................................................6
2.1.2 LSB 最小位元藏密法......................................................................7
2.2 雲端運算環境................................................................................................8
2.2.1 Hadoop...............................................................................................9
2.2.2 Hadoop Distributed File System(HDFS) .........................................12
2.3 MapReduce ..................................................................................................14
2.3.1 MapReduce 模型.............................................................................14
2.3.2 MapReduce Design Patterns ............................................................15
第三章 資訊隱藏演算法應用MapReduce 模型......................................................17
3.1 資訊隱藏演算法MapReduce 通用包裝模型............................................18
3.2 M/R-Based LSB 系統實作設計.................................................................23
3.2.1 M/R-Based LSB Patterns 選擇.......................................................23
3.2.2 M/R-Based LSB 虛擬碼.................................................................25
第四章 執行效能

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