Source identification for mobile devices,based on wavelet transforms combined with sensor imperfections

One of the most relevant applications of digital image forensics is to accurately identify the device used for taking a given set of images, a problem called source identification. This paper studies recent developments in the field and proposes the mixture of two techniques (Sensor Imperfections and Wavelet Transforms) to get better source identification of images generated with mobile devices. Our results show that Sensor Imperfections and Wavelet Transforms can jointly serve as good forensic features to help trace the source camera of images produced by mobile phones. Furthermore, the model proposed here can also determine with high precision both the brand and model of the device.     

数字图像反取证技术综述

目的 数字图像的真实性问题备受人们关注,被动取证是解决该问题的有效途径。然而,如果伪造者在篡改图像的同时利用反取证技术对篡改的痕迹进行消除或伪造,那么已有的大量被动取证技术都将失效。回顾图像反取证技术的研究现状（包括兴起原因、实现原理、技术特点以及应用前景）,并根据已有文献总结反取证技术面临的主要挑战和机遇。方法 由于现有的被动取证技术大都基于遗留痕迹和固有特征的异同来辨识图像真伪,因此本文以不同的取证特征为线索来评述和比较反取证技术的原理和策略。结果 根据取证特征的不同,将反取证技术归纳为遗留痕迹隐藏、固有特征伪造和反取证检测等三类,并展示了当前各类反取证技术面临的难点和挑战。结论 对数字图像反取证技术进行总结和展望,并指出其算法未来在通用性、安全性、可靠性等方面将有待进一步的深入研究。     

Intrinsic Sensor Noise Features for Forensic Analysis on Scanners and Scanned Images

A large portion of digital images available today are acquired using digital cameras or scanners. While cameras provide digital reproduction of natural scenes, scanners are often used to capture hard-copy art in a more controlled environment. In this paper, new techniques for nonintrusive scanner forensics that utilize intrinsic sensor noise features are proposed to verify the source and integrity of digital scanned images. Scanning noise is analyzed from several aspects using only scanned image samples, including through image denoising, wavelet analysis, and neighborhood prediction, and then obtain statistical features from each characterization. Based on the proposed statistical features of scanning noise, a robust scanner identifier is constructed to determine the model/brand of the scanner used to capture a scanned image. Utilizing these noise features, we extend the scope of acquisition forensics to differentiating scanned images from camera-taken photographs and computer-generated graphics. The proposed noise features also enable tampering forensics to detect postprocessing operations on scanned images. Experimental results are presented to demonstrate the effectiveness of employing the proposed noise features for performing various forensic analysis on scanners and scanned images.      

Noise- and compression-robust biological features for texture classification

Texture classification is an important aspect of many digital image processing applications such as surface inspection, content-based image retrieval, and biomedical image analysis. However, noise and compression artifacts in images cause problems for most texture analysis methods. This paper proposes the use of features based on the human visual system for texture classification using a semisupervised, hierarchical approach. The texture feature consists of responses of cells which are found in the visual cortex of higher primates. Classification experiments on different texture libraries indicate that the proposed features obtain a very high classification near 97%. In contrast to other well-established texture analysis methods, the experiments indicate that the proposed features are more robust to various levels of speckle and Gaussian noise. Furthermore, we show that the classification rate of the textures using the presented biologically inspired features is hardly affected by image compression techniques.     

A generic content-based image retrieval framework for mobile devices

Multimedia mobile devices have created new possibilities for developing and accessing a variety of multimedia items such as images, audio and video clips. Personal multimedia items are, nowadays, being consumed at an enormous rate. Therefore, the management of these media items has become a pressing problem. In this paper, a client-server content-based image retrieval framework for mobile platforms is developed, which provides the capability of content-based query and browsing from mobile devices. The proposed framework provides an adaptive user interface and a generic structure, which supports a wide range of mobile devices. In this framework, a client requests the server for retrieval of particular images with a particular content. The server performs a content-based retrieval of images from a selected database and streams the retrieved results back to the client in an efficient way. The query results are transmitted over a wireless network and a certain number of similar images are rendered on the mobile device screen using thumbnail sizes. The proposed framework serves as a basis of content-based image retrieval on mobile devices. It addresses several important challenges such as hardware and software limitations as well as efficient use of the available network bandwidth.     

手机及小型手持数字设备数字取证研究综述

现代社会以手机和个人数字助理为代表的小型手持电子设备已经成为人们不可或缺的日常工具。随着信息和通信技术的发展,这些手持设备功能越来越增强,普及度越来越高,在各类案件中都可以见到这类数字手持设备的身影。因而对于这一类小型数字电子设备取证成为紧迫性的新研究领域。对这一类数字取证现状和相应工具作一综述。     

State of the art in passive digital image forgery detection: copy-move image forgery

Authenticating digital images is increasingly becoming important because digital images carry important information and due to their use in different areas such as courts of law as essential pieces of evidence. Nowadays, authenticating digital images is difficult because manipulating them has become easy as a result of powerful image processing software and human knowledge. The importance and relevance of digital image forensics has attracted various researchers to establish different techniques for detection in image forensics. The core category of image forensics is passive image forgery detection. One of the most important passive forgeries that affect the originality of the image is copy-move digital image forgery, which involves copying one part of the image onto another area of the same image. Various methods have been proposed to detect copy-move forgery that uses different types of transformations. The goal of this paper is to determine which copy-move forgery detection methods are best for different image attributes such as JPEG compression, scaling, rotation. The advantages and drawbacks of each method are also highlighted. Thus, the current state-of-the-art image forgery detection techniques are discussed along with their advantages and drawbacks.     

Hiding Traces of Resampling in Digital Images

Resampling detection has become a standard tool for forensic analyses of digital images. This paper presents new variants of image transformation operations which are undetectable by resampling detectors based on periodic variations in the residual signal of local linear predictors in the spatial domain. The effectiveness of the proposed method is supported with evidence from experiments on a large image database for various parameter settings. We benchmark detectability as well as the resulting image quality against conventional linear and bicubic interpolation and interpolation with a sinc kernel. These early findings on “counter-forensic” techniques put into question the reliability of known forensic tools against smart counterfeiters in general, and might serve as benchmarks and motivation for the development of much improved forensic techniques.      

A survey of passive technology for digital image forensics

Over the past years, digital images have been widely used in the Internet and other applications. Whilst image processing techniques are developing at a rapid speed, tampering with digital images without leaving any obvious traces becomes easier and easier. This may give rise to some problems such as image authentication. A new passive technology for image forensics has evolved quickly during the last few years. Unlike the signature-based or watermark-based methods, the new technology does not need any signature generated or watermark embedded in advance. It assumes that different imaging devices or processing would introduce different inherent patterns into the output images. These underlying patterns are consistent in the original untampered images and would be altered after some kind of manipulations. Thus, they can be used as evidence for image source identification and alteration detection. In this paper, we will discuss this new forensics technology and give an overview of the prior literatures. Some concluding remarks are made about the state of the art and the challenges in this novel technology.     

基于谱相关性的数字图像真伪鉴别

如何区分逼真的计算机生成图像和真实的自然图像,是数字图像取证领域的一个重要研究方向。提出了一种基于谱间相关性的图像真伪鉴别算法。在单CCD数码成像过程中,每个像素只采集单一颜色值,缺失的颜色值通过颜色滤波阵列插值获得,而基于颜色滤波阵列插值的去马赛克方法会引起彩色图像三个颜色分量之间较高的谱间相关性。算法利用小波变换和标准互相关系数提取颜色组件谱间相关性,作为区分和识别特征。通过在标准图像库上的实验测试,表明所提取特征有效捕获了二类图像的差别,并具有较高的检测率。     

A PRNU-based counter-forensic method to manipulate smartphone image source identification techniques

The increased diffusion of digital images generated by mobile devices through social networks, personal and professional communications, etc. is self-evident. This creates potential problems because some of these images may be used as supporting evidence for different criminal cases. In this paper, algorithms are proposed based on sensor noise and wavelet transforms which can alter the information which is usually employed to find the source of an image, and forge it so that it could point to a different, unrelated device. In the state of art we will show that there are already some algorithms capable of carrying out these manipulations, but they generally need much more and more complex data than our proposal. They also generally need physical access to the camera whose generated images you want to tamper. Our proposal algorithm to destruct the image identifiable data, only needs the picture which will be anonymized. Also, our proposal to forge the image identifiable data only needs a set of photos from the attacker camera, and the picture to be tampered. In particular, it does not need access to the camera that will be falsely linked to the picture. These scenarios are the most common and realistic. The algorithms proposed will help to strengthen existing techniques and develop new forensic approaches for mobile image source identification that will be more robust against attacks.     

Exact safety verification of hybrid systems using sums-of-squares representation

In this paper we discuss how to generate inductive invariants for safety verification of hybrid systems. A hybrid symbolic-numeric method is presented to compute inequality inductive invariants of the given systems. A numerical invariant of the given system can be obtained by solving a parameterized polynomial optimization problem via sum-of-squares （SOS） relaxation. And a method based on Gauss-Newton refinement and rational vector recovery is used to obtain the invariants with rational coefficients, which exactly satisfy the conditions of invariants. Several examples are given to illustrate our algorithm.     

Digital image ownership authentication via camouflaged unseen-visible watermarking

In recent years, end users can easily capture digital images using several devices, such as smartphones, mobile devices and digital imaging cameras, allowing such images to be easily copied, manipulated, transmitted or format converted without any restrictions. This fact suggests the necessity to develop digital tools, such as digital watermarking, to solve the issues associated with copyright protection and ownership authentication of digital images. To claim the ownership of a digital image, we propose a camouflaged, unseen-visible watermarking technique based on luminance and texture properties in conjunction with an image enhancement criterion. The proposed method has some advantages over invisible and visible watermarking methodologies in terms of readability and imperceptibility of the watermark, respectively. The experimental results demonstrate that the proposed scheme is effective and applicable for digital images on a variety of topics, including natural scenes and man-made objects, both indoors and outdoors. A comparison with previously reported methods based on unseen-visible watermarking techniques is also provided.     

Digital Image Forensics via Intrinsic Fingerprints

Digital imaging has experienced tremendous growth in recent decades, and digital camera images have been used in a growing number of applications. With such increasing popularity and the availability of low-cost image editing software, the integrity of digital image content can no longer be taken for granted. This paper introduces a new methodology for the forensic analysis of digital camera images. The proposed method is based on the observation that many processing operations, both inside and outside acquisition devices, leave distinct intrinsic traces on digital images, and these intrinsic fingerprints can be identified and employed to verify the integrity of digital data. The intrinsic fingerprints of the various in-camera processing operations can be estimated through a detailed imaging model and its component analysis. Further processing applied to the camera captured image is modelled as a manipulation filter, for which a blind deconvolution technique is applied to obtain a linear time-invariant approximation and to estimate the intrinsic fingerprints associated with these postcamera operations. The absence of camera-imposed fingerprints from a test image indicates that the test image is not a camera output and is possibly generated by other image production processes. Any change or inconsistencies among the estimated camera-imposed fingerprints, or the presence of new types of fingerprints suggest that the image has undergone some kind of processing after the initial capture, such as tampering or steganographic embedding. Through analysis and extensive experimental studies, this paper demonstrates the effectiveness of the proposed framework for nonintrusive digital image forensics.     

A Collaborative Digital Pathology System for Multi‐Touch Mobile and Desktop Computing Platforms

Collaborative slide image viewing systems are becoming increasingly important in pathology applications such as telepathology and E‐learning. Despite rapid advances in computing and imaging technology, current digital pathology systems have limited performance with respect to remote viewing of whole slide images on desktop or mobile computing devices. In this paper we present a novel digital pathology client–server system that supports collaborative viewing of multi‐plane whole slide images over standard networks using multi‐touch‐enabled clients. Our system is built upon a standard HTTP web server and a MySQL database to allow multiple clients to exchange image and metadata concurrently. We introduce a domain‐specific image‐stack compression method that leverages real‐time hardware decoding on mobile devices. It adaptively encodes image stacks in a decorrelated colour space to achieve extremely low bitrates (0.8 bpp) with very low loss of image quality. We evaluate the image quality of our compression method and the performance of our system for diagnosis with an in‐depth user study.     

MTK手机Flash芯片文件系统恢复研究

目前针对手机的取证软件大部分是从逻辑层面提取数据而不是从存储介质中提取数据,本文提出了从底层对闪存进行取证的方法,并给出三种从底层拷贝闪存数据的方法。基于MTK不同芯片型号的NandFlash使用的文件系统进行研究,针对不同MTK芯片型号的手机展示了如何拷贝FLASH存储介质中的数据,将提取的闪存镜像数据重组并转换为普通取证工具所能识别的文件系统,并在此基础上提取手机上的电话本、短信、图片等重要数据[1]。     

A forensic algorithm against median filtering based on coefficients of image blocks in frequency domain

Median filtering is a popular nonlinear denoising operator, it not only can be used for image enhancement, and it also is an effective tool in application of anti-forensics. So, the blind detection of median filtering is a particularly hot topic. Different from the existing median filtering forensic methods using the image pixel statistical features, this paper proposed a novel approach for detecting median filtering in digital images using coefficients of image blocks in frequency domain, based on the theory analysis and experiments test. Large numbers of experimental results show that the proposed approach achieved a high accuracy in median filtering detection and a good robustness of defending JPEG compression, the algorithm also can be used to locate the median filtering area. The approach achieves much better performance than the existing state-of-the-art methods with different format and size of image blocks, particularly when the image blocks are tiny and have high JPEG compression ratio.     

Identification of smartphone brand and model via forensic video analysis

Recording videos on smartphones and other mobile devices, given their enormous popularity, is currently very common. The portability of these devices facilitates their use for recording videos in a wide variety of situations, including while witnessing criminal activities. These videos can be later used as evidence in legal proceedings. Therefore, the forensic analysis of videos taken with mobile device videos is important, and could serve for legal and also investigative purposes. It is necessary, however, to use techniques that are quite specific to this type of devices, given some peculiar features of their cameras. In this paper, we will address the issue of video source acquisition identification by presenting a technique based on sensor noise and wavelet transform extraction from video key frames. These frames are extracted using an efficient algorithm that takes their content into account, improving the selection of frames to be analyzed over past proposals. The scheme presented consists of four stages: (1) Key frames extraction, (2) sensor pattern noise extraction, (3) feature extraction, and (4) classifier training and prediction. We also present experimental results that support the validity of the techniques used and show promising results.     

Efficient digital holographic 3d human image reconstruction and improvement on mobile devices

Advanced digital holography attracts a lot of attentions for 3D visualization nowadays. The representation of high-resolution digital holographic 3D human images suffers from computational inefficiency on the mobile devices due to the limited hardware for digital holographic processing. Specifically, to reconstruct the high-quality holographic image needs to compensate for the phase aberration, which needs lots of expensive optical hardware components to acquire measurements such as different axial distances, illumination angles, wavelengths, polarization states, and so on. To reduce computational complexity in digital holographic 3D human image reconstruction, we propose an efficient and effective algorithm to simplify Fresnel transforms for the mobile devices. Our algorithm reduces the number of FFTs and fastens the calculation of the exponential function in the Fresnel integral for the digital holography image reconstruction. Specifically, we reformulate the Fresnel integral and use a polynomial approximation to approximate the exponential function. In the holographic image quality improvement, we modify a maximum a posteriori (MAP) estimation to improve the quality of the reconstructed holographic 3D image restoration. Our algorithm outperforms previous approaches in not only smaller running time but also the better quality of the digital holographic 3D human image representation for the mobile devices.