High Capacity and Secure Steganography Using Texture Synthesis

文獻上最新之偽裝學演算法為Wu and Wang提出的可逆材質合成(SRTS)，具有提供定額嵌入量、抵抗偽裝偵測之特性。本論文提出的兩個演算法來提高材質合成偽裝學演算法之藏量缺失並增加其嵌入訊息之安全性。 我們提出的第一個演算法名稱為「結合組合關係與可逆材質合成之藏密學演算法」(SCRTS)。首先，以每個可嵌入區塊個數對應1個組合關係位元 (n)，我們計算得出二進制組合秘密訊息量。接著，我們一次讀入所有可嵌入的二進制組合秘密訊息，並將之轉成可嵌入區塊之0或1的組合關係序列C。吳學者Wu and Wang在做材質合成時，每個欲合成之區塊是根據k 位元的區塊秘密訊息所轉換之十進制排名R，來源材質中選取對應排名之區塊。我們的演算法除了考慮區塊秘密訊息外，也考慮組合秘密訊息所轉出的組合關係序列。若該區塊之組合關係序列為1，則需要在來源材質中，選取偏移2k+1排名之區塊。反之，若該區塊之組合關係序列為0，則修正Wu and Wang演算法，在來源材質中選取R+1排名之區塊。我們提出的演算法，可以嵌入區塊秘密訊息外，也可以嵌入組合秘密訊息，故能提供比Wu and Wang演算法更高的嵌入藏量。擷取秘密訊息時，需逐一比對每個合成區塊之排名，並將之轉成2進制區塊秘密訊息。此外，根據排名，我們也逐一產生對應的0或1組合關係序列。當完成擷取所有區塊秘密訊息後，我們才能根據所產出完整的組合關係序列，順利能擷取得出2進制組合秘密訊息。由於組合關係序列之每個位元環環相扣，某個錯誤的單一位元，會影響整體組合關係序列與所擷取出得到的組合秘密訊息之正確性。我們演算法使用組合關係數，能提供比Wu and Wang更高的嵌入安全性。 我們提出的第二個演算法，名稱為「結合組合關係與可逆材質合成且具驗證特性之藏密學演算法」(SCRTSA)。考量來源材質是擷取區塊訊息與組合訊息不可或缺的資訊，任何些微的像素更動，影響擷取秘密訊息的正確性。故SCRTSA演算法使用雜湊編碼，利用其「雪崩效應」，來驗證來源材質之完整性。首先。發送端將來源材質所有像素的R、G、B通道數值全部串聯起來，形成一個長串的像素二進位序列。接著，我們使用第三代安全雜湊演算法(SHA3)，產出長度為128位16進制的發送端雜湊編碼序列。我們將此序列視為秘密金鑰，並以安全的管道送給接收方。接收端欲擷取秘密訊息時，先重複上述動作，產出的接收方雜湊編碼序列。接著，比對接收方與發送端之雜湊編碼序列；若兩者相同，則可繼續擷取秘密訊息；若兩者相異，則代表來源材質曾被竄改，所擷取之秘密訊息亦可能遭受竄改。SCRTSA演算法使用雜湊編碼，即使來源材質內像素1個位元被竄改，亦可藉由「雪崩效應」來驗證完整性，故安全性高於吳學者Wu and Wang原始之演算法。我們也擴展可嵌入區塊個數對應組合關係之位元數(n)，來計算二進制組合秘密訊息量。具言之，選取合成區塊之原則如下：首先，對每個欲合成區塊，我們先讀取k位元之區塊秘密訊息（其對應之十進制為R），同時讀取n位元的組合秘密訊息（其對應之十進制為G）；接著，將0至2^(k+n)-1之候選區塊平均分割成2^n等分。最後，我們第G+1個等分內，選取第R個區塊排名為合成區塊。SCRTSA演算法使用更大的組和關係位元(n≥2)，故能提供比第一個演算法SCRTS更高的嵌入量，相對的也高於Wu and Wang原始演算法所能提供之藏量。實驗結果顯示：在參數k=5，n=2-4的條件下，我們的SCRTSA演算法可以提高學者20-40%的嵌入藏量，成效優異。 綜合以上，本文提出兩個藏密學演算法SCRTS與SCRTSA，已大幅改善Wu and Wang可逆材質合成藏密學演算法之嵌入量與安全性之缺失。演算法可實質用於藏密學應用。This thesis proposes two algorithms to improve disadvantages of the embedding capacity and security encountered for Wu’s steganography using reversible texture synthesis scheme. Steganography Using Combinatorics and Reversible Texture Synthesis, abbreviated by SCRTS, is the first algorithm. We observe that a combination of n embeddable patches, taking (n/2) at a time, can carry l-bit of binary combination message. In the first step of SCRTS, we convert l-bit of binary combination message that is given into to a combinatorics sequence consisting of bits “0” or “1,” where each bit corresponds to an embeddable patch to be synthesized. In Wu’s scheme, each embeddable patch can convey k-bit secret patch message. Specifically, a patch is selected from the candidate list which has the corresponding decimal R-th rank during the texture synthesis. In contrast, in our SCRTS algorithm, if an embeddable patch has a corresponding combinatorics bit “1,” we select the patch from a candidate list that has the offset ranking R+1 for texture synthesis. If an embeddable patch has a corresponding combinatorics bit “0”, we select the patch which has the offset ranking R+2k +1. In this manner, SCRTS offers not only the patch messages but also the combination message, thereby providing the embedding capacity larger than Wu’s original scheme. When extracting secret messages, we compare the currently synthesized patch with the same location in the stego texture synthesis image. This allows us to determine the decimal rank and extract k-bit binary pattern of the currently processed patch. By processing each embeddable patch, we gradually build the combinatorics sequence. Only when the entire sequence is built completely can we re-construct the l-bit of secret combination message, thus accomplishing the task of the message extraction. Contributed from the interlocking of combinatorics sequence, our SCRTS offers more secure message concealment. Steganography Using Combinatorics and Reversible Texture Synthesis with Authentication (SCRTSA) represents the second algorithm we introduce. Since the source texture is the indispensable data and any slight change may decline the message extraction, SCRTSA algorithm adopts the hash encoding to verify the integrity of source texture prior to message extraction. First, we combine all pixels in the three primary color channels to form a binary pixel sequence. Then, the secure hash algorithm 3 is adopted to generate 128-digit hash encoding sequence in the hexadecimal notational system. This hash encoding sequence, regarding as a secret key, is delivered to the receiver via a secure channel. During the message extraction, the receiver reconstructs the hash encoding sequence from the stego texture synthesis image and compares it with the existing one previously delivered. The “avalanche effect” feature inherited from the hash encoding sequence ensures that the receiver to verify the integrity of the source texture, even though a single bit in the source texture is tampered. We further generalize the combinatorics sequence from the original 1-bit to n-bit scheme. The steps of message concealment are modified as follows. First, for each embeddable patch to be synthesized, we read in k-bit secret patch message, which has the corresponding decimal value R. At the same time, we read in n-bit secret combinatorial message which has the corresponding decimal value G. Next, we evenly build 2^n sets with indices 0 to 2^n-1 from the a total of 2^(k+n) candidate patches which have ranks from 0 to 2^(k+n)-1. Finally, we select the patch which has the rank R as the synthesized patch from the (G+1)-th set. In this way, SCRTSA adopts a generalized combinatorics sequences (n≥2), therefore offering larger embedding capacity than that provided by the SCRTS algorithm. Experimental result shows that using the parameters of k=5 and n=2-4, our SCRTSA offers 20% to 40% more capacity than the competitive algorithm. In conclusion, this thesis recommends two algorithms, SCRTS and SCRTSA. Both schemes improve the disadvantages encountered in the current state-of-the-art steganographic algorithms using reversible texture synthesis. We believe the steganography community is beneficial to the proposed algorithms, extending the feasibility of the steganographic applications.致謝 i 摘要 ii Abstract iv 第一章、緒論 1 第二章、相關研究 3 第三章、使用組合關係及可逆材質合成之藏密學 7 3.1 SCRTS演算法秘密訊息嵌入流程 8 3.1.1 產生編號索引表 9 3.1.2 決定組合數藏量及組合關係序列 10 3.1.3 產生組合關係表 13 3.1.4 產生組合影像 14 3.1.5 訊息導向材質合成 15 3.2 SCRTS秘密訊息取出流程 18 3.2.1 產生編號索引表 19 3.2.2 還原來源材質 19 3.2.3 產生組合影像 19 3.2.4 訊息擷取及認證 19 3.2.5 SCRTS擷取合成以及組合秘密訊息 20 3.3 SCRTS理論與安全性分析 20 3.3.1 SCRTS理論分析 20 3.3.2 SCRTS安全性分析 21 3.4 SCRTS實驗結果 22 3.4.1 SCRTS藏入位元數結果與分析 22 3.4.2 SCRTS視覺化比較 27 3.4.3 量測數據分析 34 3.4.4 偽裝偵測數據分析 38 3.4.5 SRTS與SCRTS分析 43 3.5 小結 56 第四章、結合組合關係與可逆材質合成且具驗證特性之藏密學演算法 57 4.1 SCRTSA嵌入流程 57 4.1.1 組合關係藏量以及SCRTSA嵌入演算法 58 4.2 SCRTSA秘密訊息取出流程 59 4.2.1 SCRTSA擷取區塊以及組合秘密訊息 60 4.3 SCRTSA理論與安全性分析 60 4.3.1 SCRTSA理論分析 60 4.3.2 SCRTSA安全性分析 61 4.4 SCRTSA實驗結果 65 4.3.1 SCRTSA藏入位元數結果與分析 65 4.3.2 SCRTSA視覺化比較 67 4.3.3 量測數據分析 76 4.3.4 偽裝偵測數據分析 80 4.3.5 SRTS與SCRTSA分析 84 第五章、結論與未來工作 97 5.1 結論 97 5.2 未來工作 98 參考資料 99 中英文對照表 102 英中文對照表 104 附件1 106 附件2 11