本文關(guān)鍵詞： 紙質(zhì)文件檢驗 數(shù)字化被動取證 文件來源取證 文件變造取證 文件碎片拼接　出處：《大連理工大學(xué)》2015年博士論文　論文類型：學(xué)位論文

【摘要】：隨著人們生活中數(shù)字化程度不斷加深,與打印、復(fù)印文件相關(guān)的民事和刑事案件也越來越多并呈逐年上升趨勢,傳統(tǒng)的文件檢驗方法須專業(yè)的人員和設(shè)備,并依靠物理、化學(xué)方法對可疑文件檢驗,這些方法存在檢測時間長、成本高、對文檢人員要求嚴(yán)格及有損檢測等特點。司法鑒定部門迫切需要新的取證手段對損壞文件進(jìn)行恢復(fù),對偽造、變造文件進(jìn)行取證。為減少對專業(yè)文檢人員和設(shè)備依賴,提高取證效率,近年來只利用計算機(jī)和掃描儀的紙質(zhì)文件被動取證技術(shù)逐漸發(fā)展起來,成為國際上信息安全的研研究熱點之一。本文從文件碎片拼接、文件來源取證和文件變造取證三個方面進(jìn)行紙質(zhì)文件的被動取證問題研究,具體工作如下：(1)針對紙質(zhì)文件碎片拼接,提出一種基于曲線匹配和信息對齊的文件碎片拼接方法。該方法利用曲線間距離描述曲線的相似性,并通過曲線相似性匹配尋找正確碎片對,在曲線匹配過程中,通過碎片上多元信息對齊來提高匹配效率。該方法結(jié)合計算機(jī)識別與人工選擇完成碎片拼接,對碎片旋轉(zhuǎn)具有魯棒性。實驗以DARPA提供的競賽題目為測試數(shù)據(jù)集,能夠?qū)η?個題目進(jìn)行有效拼接,所提出的方法在完成題目數(shù)量和匹配效率上均優(yōu)于現(xiàn)有方法。(2)針對紙質(zhì)文件來源取證,分別提出了紙張來源取證和設(shè)備類型取證方法。紙張來源取證方法主要利用紙張空白區(qū)域的紋理特征進(jìn)行紙張品牌的來源鑒別,特征包括灰度共生矩陣特征和傅里葉頻譜特征,該方法實現(xiàn)了紙張的數(shù)字化被動取證。此外,本文提出一種設(shè)備類型取證方法,該方法針對激光打印機(jī)、噴墨打印機(jī)和靜電復(fù)印機(jī)三種典型設(shè)備,對每個字符提取高斯噪聲能量、沖擊噪聲能量、字符輪廓粗糙度和字符邊緣平均梯度4維特征,使用SVM分類器進(jìn)行設(shè)備類型取證。該方法可對每個字符進(jìn)行設(shè)備類型取證,并且可以檢測由不同類型設(shè)備生成的變造文件。(3)針對紙質(zhì)文件的變造取證,提出一種基于字符幾何參數(shù)失真突變識別的取證方法。該方法通過掃描文件圖像與參考文件圖像的匹配獲得每個字符的失真參數(shù),利用參數(shù)失真幅度計算字符的變造概率,最后通過概率分布對變造字符進(jìn)行鑒別和定位。該方法對JPEG壓縮具有魯棒性,并可對文件進(jìn)行字符級取證,不需要提供待測文件的先驗知識,在算法性能上優(yōu)于現(xiàn)有算法。
[Abstract]:With the increasing digitization of people's lives, the number of civil and criminal cases related to printing and copying documents is increasing year by year. Traditional document inspection methods need professional personnel and equipment, and rely on physics. These methods have the characteristics of long testing time, high cost, strict requirements for document examiners and harmful detection. The forensic appraisal department urgently needs new methods to recover the damaged documents and forge them. In order to reduce the dependence on professional document inspectors and equipment and improve the efficiency of forensics, the passive forensics technology, which only uses computers and scanners, has been developed in recent years. This paper studies the passive forensics of paper documents from three aspects: document fragmentation, document source evidence and document alteration evidence. The main work is as follows: (1) for paper document fragment splicing, a method of document fragment splicing based on curve matching and information alignment is proposed, which uses the distance between curves to describe the similarity of curves. In the process of curve matching, the matching efficiency is improved by multi-element information alignment. This method combines computer recognition with artificial selection to complete the splicing of fragments. The experiment takes the competition topic provided by DARPA as the test data set, and can effectively splice the first three questions. The proposed method is superior to the existing method in terms of the number of questions completed and the efficiency of matching. The paper source evidence method mainly uses the texture features of the blank area of paper to identify the origin of the paper brand, which includes gray level co-occurrence matrix feature and Fourier spectrum feature. In addition, this paper puts forward a kind of equipment type evidence collection method, which is aimed at three typical equipments: laser printer, inkjet printer and electrostatic photocopier. Gao Si noise energy, impulse noise energy, character contour roughness and four-dimensional feature of average gradient of character edge are extracted from each character, and the device type evidence is obtained by using SVM classifier. And it can detect altered files generated by different types of equipment. In this paper, a method of obtaining evidence based on character geometric parameter distortion mutation identification is proposed, in which the distortion parameters of each character are obtained by matching the scanning file image with the reference file image, and the variation probability of the character is calculated by using the distortion amplitude of the parameter. Finally, the modified characters are identified and located by probability distribution. This method is robust to JPEG compression, and can be used to document character level forensics, and does not need to provide prior knowledge of the files to be tested, and the algorithm performance is better than the existing algorithm.
【學(xué)位授予單位】：大連理工大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2015
【分類號】：D918;TP391.41

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