本計晝提出一種部分混沌視覺經驗模態拆解水下聲音感測網路認證與加密方法。設計概 念為整合一種二維混沌攪亂器、經驗模態拆解演算法和二維方塊間隔方法達到快速、強韌和不可預測 視覺加密機制。原始聲音訊號應用經驗模態拆解演算法，拆解成數個本質模態函數和一個殘餘函數。 分析各個本質模態函數和殘餘函數能量參考總能量分佈比，第一能量參考總能量分佈比本質模態函 數，第二能量參考總能量分佈比本質模態函數，應用混沌演算法加密。將第一能量參考總能量分佈比 本質模態函數混沌加密訊號，第二能量參考總能量分佈比本質模態函數混沌加密訊號和其餘本質模態 函數和一個殘餘函數合成為部分加密聲音訊號。應用皮爾森相關係數討論未加密水下聲音訊號、部分 加密水下聲音訊號和全加密水下聲音訊號加密關聯性。相較全加密水下聲音訊號演算法，部分加密水 下聲音訊號加密速度較快，複雜度較低。This project aims to develop a partial chaotic/empirical mode decomposition (EMD) visual authentication and encryption method for underwater voice sensor network. The basic design concept is to integrate two-dimensional (2D) chaos-based encryption scramblers, the EMD algorithm, and a 2D block interleaver method to achieve a fast, robust and unpredictable visual encryption mechanism. The original voice signal is decomposed into several intrinsic mode functions (IMFs) and one residual function (RF) using the EMD algorithm. The energy ratios of the ith IMF and RF of a voice signal to its refereed total energy are analyzed. The maximum and second maximum energy ratios of the IMFs of a voice signal to its refereed total energy are encrypted using the chaotic encryption algorithms. The maximum and second maximum energy ratios of the encrypted IMFs, the unencrypted IMFs, and the RF are combined to generate partial chaotic visually encrypted voice signals. Following this, the Pearson correlation coefficients of original and partial chaotic visually encrypted underwater voice signals, original and full chaotic visually encrypted underwater voice signals, and partial and full chaotic visually encryption underwater voice signals are investigated. When compared to a full chaotic visual encryption system developed using an EMD algorithm, the partial chaotic visual cryptosystem was found to be less complex and have a higher encryption speed.
underwater voice signals
authentication and encryption