浮水印演算法在近期的研究中蔚為流行，原因是因為網路與科技的發展，資訊傳播的速度提升，導致惡意散波與盜版的猖獗，而個人智慧財產也因此遭受挑戰，故發展出浮水印的演算法以用於保護個人智慧財產，而本論文研究也針對此方面提出一個更安全並且運算複雜度更低的演算法。
本論文探討之演算法為展頻浮水印演算法，展頻浮水印的發展先是著重於浮水印的解出正確率並且提出改善，而後則是面臨容量上的問題，在2015年與2018年時，學者Yong Xiang等人提出了分別兩種不同之高容量嵌入演算法，但後者的演算法中存在了安全性上的問題，於是同年另一名學者徐詠翔提出了使用互補碼法，做為浮水印嵌入的基礎，並且也有效的提升了安全性及維持原有的解出率。本論文研究提出在解出率不變的情形下，藉由互補碼的排列產生序列，並且分層將浮水印資訊嵌入各層序列當中，達到多層浮水印的效果，提供多重使用者共同擁有同一智慧財產之音檔，本論文演算法不僅提供多重使用者使用，也降低了演算法複雜度、提升偽隨機序列產生速度以及浮水印萃取正確率。
本研究演算法，經由實驗並且使用常見的數位信號處理進行攻擊，最後以相同感知音訊品質評估為基準與其他演算法做比較，最後以位元錯誤率(Bit Error Ratio)進行實驗的分析，實驗之結果顯示出本論文之演算法擁有較好的位元錯誤率。對於演算法偽隨機序列產生複雜度及比例因數選擇，也實驗了不同演算法的產生時間，實驗結果證明本研究提出之演算法降低了偽隨機序列組數以及產生序列的運算複雜度，同時保有較低的比例因數計算時間。

Many spread spectrum (SS) based audio watermarking schemes to protect copyright have been proposed but they all have the host signal interference problem and capacity problem. The major drawback of SS-based audio watermarking methods is the low embedding capacity. In the past, a number of spread spectrum (SS) based audio watermarking methods have been proposed to deal with the host signal interference problem. In recent years, Yong-Xiang and Iynkaran Natgunanathan proposed a novel SS-besed audio watermarking method using Gram-Schmidt orthogonalization method to generats orthogonal pseudonoise (PN)sequences. This method can embed lager number of watermark bit but it has security problem. However, since this method has security problem, Yong-Siang Syu then proposed new method which use complementart codes to be the PN sequences that pocess lower computational cost and high security but it maintains high embedding capacity. In this thesis, we proposed a spread spectrum audio watermarking scheme using the same complementary codes to be the PN sequences but it can embed multi-layer watermark which available to multiple users. By adjusting scaling factor, which not only process lower bit error ratio than Yong-Siang’s method but also maintains security and capacity. The performance of the proposed SS-based audio watermarking method is demonstrated by simulation results

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