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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/26270

    Title: 以互次或函式為基礎之秘密資料隱藏技術
    Authors: 詹啟祥
    Contributors: 資訊學院;資訊多媒體應用學系
    Keywords: 秘密資料隱藏技術;最不重要位元隱藏法;Information Hiding;LSB substitution;matching revisited
    Date: 2012
    Issue Date: 2013-07-18 15:53:12 (UTC+8)
    Abstract: 秘密資料隱藏技術中最基本的概念,是將秘密資料藏入多媒體中比較不重要的地方,以防止非法攻擊者發現。而在所有的秘密資料隱藏技術中,Mielikainen的方法具有高的「隱藏容量」,同時在藏入秘密資料位元時,也具有較少的像素修改數目。在本計畫中,我們將使用互斥或函式(XOR Function)將鄰近的像素串連起來,以期更進一步的減少像素修改的數目。在本計畫的第一年裡,我們首先修改Mielikainen的方法,利用互斥或函式(XOR Function) 的串連,使得像素的互次或函式值與鄰近的其他兩個像素有關。當我要更動某個像素的互次或函式值時,不只可以經由更動此像素來達成,還可以藉由修改其他兩個像素中的一個像素,來達到相同的目的。根據此概念,我們提出決定修改像素的演算法,來使藏入秘密資料位元時,減少對像素的修改量。在本計畫的第二年,像素的互次或函式值產生方式,不再只是與鄰近的兩個像素有關,而是與鄰近的其他若干個像素有關。由於參與的鄰近像素的增加,可能的情況也跟著增加,使我們無法像第一年一樣,將全部可能的情況列出,並根據變化來決定修改的像素。因此,我們利用貪婪演算法(Greedy algorithm),搜尋獲利最多的像素先進行修改,以藏入秘密資訊。可以預期的,第一年與第二年所提的方法會比Mielikainen的方法修改更少的像素。本計畫的結果,將會對秘密資料隱藏技術此領域,提供貢獻。

    The basic concept of information hiding embeds secret data into meaningful multimedia data so as to fool grabbers from perceiving the existence of secret data. Among all information hiding techniques, Mielikainen’s method has high embedding capacity (1 bpp) and few quantities of pixel modifications when embedding secret data. In this proposal, we propose two subjects that use XOR Function to link all pixels so as to further reduce the quantities of pixel modifications. In the first subject, Mielikainen’s method is modified and the XOR value of each pixel is related to its two neighboring pixels. Under the situation that the XOR value of a pixel is not compatible with the corresponding secret bit, we can modify not only the pixel itself but also one of its two neighboring pixels instead. According to this concept, our embedding algorithm is proposed to further reduce the quantities of pixel modifications. In the second subject, the XOR value of each pixel is related to a certain number of neighboring pixels. Owing to the increasing of the involved pixels for producing XOR value, the number of all possible situations becomes larger and the algorithm of the first subject is not suitable anymore. In this subject, Greedy algorithm is used to find pixels with great benefits and the pixels have high priority to be modified. It can be expected that the quantities of pixel modifications in the proposed method are fewer than those of Mielikainen’s method. The results of this project will effectively contribute to the area of information hiding.
    Appears in Collections:[行動商務與多媒體應用學系] 科技部研究計畫

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