论物证检验的数码影像接合重叠方法

数码影像的特征接合重叠比对是取代传统特征接合重叠法的重要方法之一,其在检验中具有明显的可行性及操作优势。     

显带染色体电子计算机辅助分析

应用委托开发的软件“中国人群区带染色体辅助分析系统”对国人染色体G带相片进行电子计算机分析。结果显示，该软件能有效快速地记录各个体核型，并能对不同个体来源的相同序号的染色体作直观比较．为染色体多态性应用于亲子鉴定创造了良好条件．     

基于角膜图像的人体死亡时间推断模型初探

目的尸体角膜随死后时间延长发生的形态学变化是规律性较好的指标,常用来判断死亡时间(postmortem interval,PMI)。本文尝试用机器视觉代替人的肉眼主观判断,收集尸体样本以建立通过人体角膜图像推断PMI的模型。方法收集实际案例建立包含505例人体死后角膜图像的数据库,PMI范围为0.24h(约死后14min)至492h(约死后20.5d),大致分为三类(依次为:0~<6h、6~<20h、20h及以上)或二类(0~<15h、15h及以上);使用由华盛顿大学陈天奇博士提出的Xgboost模型分别进行二分类与三分类分析;使用多种卷积神经网络模型分别进行分类和回归学习,并通过比较最终选择了由微软研究院提出的ResNet模型进行分析。结果Xgboost在三分类时预测准确率依次为71.8%、40.7%、65.7%,二分类时为90%、48.5%。ResNet分类模型中,精准率、召回率在三分类时分别依次为:81%、75%,30%、50%,61%、71%,二分类时为:70%、92%,76%、38%。ResNet回归模型中,比较整个模型的预测结果,0~6h内的预测值与真实值较为接近,均值误差为0.5616,均方误差为0.5873,6h之后开始出现较大误差。结论分类和回归模型都在0~6h之内得到了很好的结果,说明在此时间段内,角膜图像噪声较低,可预测性强。     

Descrambling data on solid-state disks by reverse-engineering the firmware

Data recovery is an important component of digital forensic research. Although recovering data from hard drives or small-scale mobile devices has been well studied, solid-state disks (SSDs) have a very different internal architecture and some additional functions, and it is not clear whether these differences will have an effect on data recovery. Data scrambling is an additional function of an SSD controller which can improve data reliability, but makes data recovery difficult. In this research, the dedicated flash software was first introduced that can acquire the physical image of an SSD without destroying the device hardware. Based on the software, a validation experiment was presented to evaluate the effect of data scrambling on data recovery and the causes of the effect were analyzed. Then two approaches to descrambling the data in the flash chips were proposed and their advantages and disadvantages discussed. After that, a procedure to identify the scrambling seeds that are used to descramble the scrambled data was described. Finally, descrambling software was implemented based on the second descrambling method. The experiment shows that this software can successfully descramble the data from an SSD flash drive regardless of the internal structure of the scrambler in the SSD controller and can generate an unscrambled physical image on which most existing data-recovery techniques can be effective.     

A New Anti‐forensic Scheme—Hiding the Single JPEG Compression Trace for Digital Image

To prevent image forgeries, a number of forensic techniques for digital image have been developed that can detect an image's origin, trace its processing history, and can also locate the position of tampering. Especially, the statistical footprint left by JPEG compression operation can be a valuable source of information for the forensic analyst, and some image forensic algorithm have been raised based on the image statistics in the DCT domain. Recently, it has been shown that footprints can be removed by adding a suitable anti‐forensic dithering signal to the image in the DCT domain, this results in invalid for some image forensic algorithms. In this paper, a novel anti‐forensic algorithm is proposed, which is capable of concealing the quantization artifacts that left in the single JPEG compressed image. In the scheme, a chaos‐based dither is added to an image's DCT coefficients to remove such artifacts. Effectiveness of both the scheme and the loss of image quality are evaluated through the experiments. The simulation results show that the proposed anti‐forensic scheme can verify the reliability of the JPEG forensic tools.     

Color Separation in Forensic Image Processing Using Interactive Differential Evolution

Color separation is an image processing technique that has often been used in forensic applications to differentiate among variant colors and to remove unwanted image interference. This process can reveal important information such as covered text or fingerprints in forensic investigation procedures. However, several limitations prevent users from selecting the appropriate parameters pertaining to the desired and undesired colors. This study proposes the hybridization of an interactive differential evolution (IDE) and a color separation technique that no longer requires users to guess required control parameters. The IDE algorithm optimizes these parameters in an interactive manner by utilizing human visual judgment to uncover desired objects. A comprehensive experimental verification has been conducted on various sample test images, including heavily obscured texts, texts with subtle color variations, and fingerprint smudges. The advantage of IDE is apparent as it effectively optimizes the color separation parameters at a level indiscernible to the naked eyes.     

Understanding Variations of Soil Mapping Units and Associated Data for Forensic Science

Soil samples have potential to be useful in forensic investigations, but their utility may be limited due to the inherent variability of soil properties, the wide array of analytical methods, and complexity of data analysis. This study examined the differentiation of similar soils based on both gross (texture, color, mineralogy) and explicit soil properties (elemental composition, cation exchange, Fe‐oxyhydroxides). Soils were collected from Fallbrook and adjacent map units from Riverside and San Diego Counties in California. Samples were characterized using multiple techniques, including chemical extracts, X‐ray diffraction (XRD), and Fourier transform infrared spectroscopy. Results were analyzed using multiple analytical approaches to compare counties and land uses. Some analyses (XRD, extractions) were better at distinguishing among samples than others (color, texture). Ratios of rare earth elements were particularly useful for distinguishing samples between counties. This potential to “fingerprint” soils illustrates the usefulness of a comprehensive soil database for criminal investigators.     

Identification of Natural Images and Computer‐Generated Graphics Based on Statistical and Textural Features

To discriminate the acquisition pipelines of digital images, a novel scheme for the identification of natural images and computer‐generated graphics is proposed based on statistical and textural features. First, the differences between them are investigated from the view of statistics and texture, and 31 dimensions of feature are acquired for identification. Then, LIBSVM is used for the classification. Finally, the experimental results are presented. The results show that it can achieve an identification accuracy of 97.89% for computer‐generated graphics, and an identification accuracy of 97.75% for natural images. The analyses also demonstrate the proposed method has excellent performance, compared with some existing methods based only on statistical features or other features. The method has a great potential to be implemented for the identification of natural images and computer‐generated graphics.     

论相貌侦查技术员的想象力

相貌侦查是指刑事侦查部门从事模拟画像及颅骨复原等专业技术的人员专门绘制嫌疑人或塑造死者肖像用于通缉疑犯、查找死者身份的专门侦查工作。这种技术员再创造的能力需要侦查人员的丰富想象力。     

足迹信息的计算机管理与查询

目的　根据国内足迹计算机管理系统的现状和需求 ,研制了适合我国刑侦工作特点的足迹管理与查询系统。方法　通过建立鞋厂鞋样、现场足迹和犯罪嫌疑人足迹数据库 ,利用足迹分析与比对软件进行管理和查询。结果　该软件完全能实现足迹管理计算机化 ,降低技术人员的劳动强度 ,提高足迹信息的使用率。结论　该软件使用方便快捷 ,适合推广使用