Forensic analysis of WeChat on Android smartphones

WeChat is one of the most popular instant-messaging smartphone applications in the world. At the end of 2015, WeChat had 697 million monthly active users from over 200 countries. Although WeChat was designed originally for communication between relatives and friends, its abundant social functions are now also used by criminals for communication, and even for the organization and coordination of criminal acts. Therefore, communication records of social networking services like WeChat extracted from the smartphones of criminals are always the vital digital evidences for the investigation and prosecution of criminal cases. At present, only a few literatures focused on WeChat forensics. This paper describes several common questions that arise in forensic examinations of Android WeChat and provides corresponding technical methods that are useful to address these questions. This paper is intended to provide vital references for the investigators and researchers working on the digital forensics.     

Integrity verification of the ordered data structures in manipulated video content

Video content stored in Video Event Data Recorders (VEDRs) are used as important evidence when certain events such as vehicle collisions occur. However, with sophisticated video editing software, assailants can easily manipulate video records to their advantage without leaving visible clues. Therefore, the integrity of video content recorded through VEDRs cannot be guaranteed, and the number of related forensic issues increases. Existing video integrity detection methods use the statistical properties of the pixels within each frame of the video. However, these methods require ample time, because they check frames individually. Moreover, the frame can easily be replaced and forged using the appropriate public software. To solve this problem, we propose an integrity checking mechanism using the structure of ordered fields in a video file, because existing video editing software does not allow users to access or modify field structures. In addition, because our proposed method involves checking the header information of video content only once, much less detection time is required compared with existing methods that examine the entire frames. We store an ordered file structure of video content as a signature in the database using a customized automated tool. The signature appears according to the video editing software. Then, the suspected video content is compared to a set of signatures. If the file structure matches with a signature, we recognize a manipulated video file by its corresponding editing software. We tested five types of video editing software that cover 99% of the video editing software market share. Furthermore, we arranged 305,981 saving options for all five video editing suites. As a result, we obtained 100% detection accuracy using stored signatures, without false positives, in a collection of 305,981 video files. The principle of this method can be applied to other video formats.     

Language translation for file paths

Forensic examiners are frequently confronted with content in languages that they do not understand, and they could benefit from machine translation into their native language. But automated translation of file paths is a difficult problem because of the minimal context for translation and the frequent mixing of multiple languages within a path. This work developed a prototype implementation of a file-path translator that first identifies the language for each directory segment of a path, and then translates to English those that are not already English nor artificial words. Brown's LA-Strings utility for language identification was tried, but its performance was found inadequate on short strings and it was supplemented with clues from dictionary lookup, Unicode character distributions for languages, country of origin, and language-related keywords. To provide better data for language inference, words used in each directory over a large corpus were aggregated for analysis. The resulting directory-language probabilities were combined with those for each path segment from dictionary lookup and character-type distributions to infer the segment's most likely language. Tests were done on a corpus of 50.1 million file paths looking for 35 different languages. Tests showed 90.4% accuracy on identifying languages of directories and 93.7% accuracy on identifying languages of directory/file segments of file paths, even after excluding 44.4% of the paths as obviously English or untranslatable. Two of seven proposed language clues were shown to impair directory-language identification. Experiments also compared three translation methods: the Systran translation tool, Google Translate, and word-for-word substitution using dictionaries. Google Translate usually performed the best, but all still made errors with European languages and a significant number of errors with Arabic and Chinese.     

Reverse engineering of ReFS

File system forensics is an important part of Digital Forensics. Investigators of storage media have traditionally focused on the most commonly used file systems such as NTFS, FAT, ExFAT, Ext2-4, HFS+, APFS, etc. NTFS is the current file system used by Windows for the system volume, but this may change in the future. In this paper we will show the structure of the Resilient File System (ReFS), which has been available since Windows Server 2012 and Windows 8. The main purpose of ReFS is to be used on storage spaces in server systems, but it can also be used in Windows 8 or newer. Although ReFS is not the current standard file system in Windows, while users have the option to create ReFS file systems, digital forensic investigators need to investigate the file systems identified on a seized media. Further, we will focus on remnants of non-allocated metadata structures or attributes. This may allow metadata carving, which means searching for specific attributes that are not allocated. Attributes found can then be used for file recovery. ReFS uses superblocks and checkpoints in addition to a VBR, which is different from other Windows file systems. If the partition is reformatted with another file system, the backup superblocks can be used for partition recovery. Further, it is possible to search for checkpoints in order to recover both metadata and content.Another concept not seen for Windows file systems, is the sharing of blocks. When a file is copied, both the original and the new file will share the same content blocks. If the user changes the copy, new data runs will be created for the modified content, but unchanged blocks remain shared. This may impact file carving, because part of the blocks previously used by a deleted file might still be in use by another file. The large default cluster size, 64 KiB, in ReFS v1.2 is an advantage when carving for deleted files, since most deleted files are less than 64 KiB and therefore only use a single cluster. For ReFS v3.2 this advantage has decreased because the standard cluster size is 4 KiB.Preliminary support for ReFS v1.2 has been available in EnCase 7 and 8, but the implementation has not been documented or peer-reviewed. The same is true for Paragon Software, which recently added ReFS support to their forensic product. Our work documents how ReFS v1.2 and ReFS v3.2 are structured at an abstraction level that allows digital forensic investigation of this new file system. At the time of writing this paper, Paragon Software is the only digital forensic tool that supports ReFS v3.x.It is the most recent version of the ReFS file system that is most relevant for digital forensics, as Windows automatically updates the file system to the latest version on mount. This is why we have included information about ReFS v3.2. However, it is possible to change a registry value to avoid updating. The latest ReFS version observed is 3.4, but the information presented about 3.2 is still valid. In any criminal case, the investigator needs to investigate the file system version found.     

Forensic acquisition and analysis of palm webOS on mobile devices

The emergence of webOS on Palm devices has created new challenges and opportunities for digital investigators. With the purchase of Palm by Hewlett Packard, there are plans to use webOS on an increasing number and variety of computer systems. These devices can store substantial amounts of information relevant to an investigation, including digital photographs, videos, call logs, SMS/MMS messages, e-mail, remnants of Web browsing and much more. Although some files can be obtained from such devices with relative ease, the majority of information of forensic interest is stored in databases on a system partition that many mobile forensic tools do not acquire. This paper provides a methodology for acquiring and examining forensic duplicates of user and system partitions from a device running webOS. The primary sources of digital evidence on these devices are covered with illustrative examples. In addition, the recovery of deleted items from various areas on webOS devices is discussed.     

Differentiating synthetic and optical zooming for passive video forgery detection: An anti-forensic perspective

A video can be manipulated using synthetic zooming without using the state-of-the-art video forgeries. Synthetic zooming is performed by upscaling individual frames of a video with varying scale factors followed by cropping them to the original frame size. These manipulated frames resemble genuine natural (optical) camera zoomed frames and hence may be misclassified as a pristine video by video forgery detection algorithms. Even if such a video is classified as forged, forensic investigators may ignore the results, believing it as part of an optical camera zooming activity. Hence, this can be used as an anti-forensic method which eliminates digital evidence. In this paper, we propose a method for differentiating optical camera zooming from synthetic zooming for video tampering detection. The features used for this method are pixel variance correlation and sensor pattern noise. Experimental results on a dataset containing 3200 videos show the effectiveness of the proposed method.     

File fragment encoding classification—An empirical approach

Over the past decade, a substantial effort has been put into developing methods to classify file fragments. Throughout, it has been an article of faith that data fragments, such as disk blocks, can be attributed to different file types. This work is an attempt to critically examine the underlying assumptions and compare them to empirically collected data. Specifically, we focus most of our effort on surveying several common compressed data formats, and show that the simplistic conceptual framework of prior work is at odds with the realities of actual data. We introduce a new tool, zsniff, which allows us to analyze deflate-encoded data, and we use it to perform an empirical survey of deflate-coded text, images, and executables. The results offer a conceptually new type of classification capabilities that cannot be achieved by other means.     

Passive forensics in image and video using noise features: A review

Due to present of enormous free image and video editing software on the Internet, tampering of digital images and videos have become very easy. Validating the integrity of images or videos and detecting any attempt of forgery without use of active forensic technique such as Digital Signature or Digital Watermark is a big challenge to researchers. Passive forensic techniques, unlike active techniques, do not need any preembeded information about the image or video. The proposed paper presents a comprehensive review of the recent developments in the field of digital image and video forensic using noise features. The previously existing methods of image and video forensics proved the importance of noises and encourage us for the study and perform extensive research in this field. Moreover, in this paper, forensic task cover mainly source identification and forgery detection in the image and video using noise features. Thus, various source identification and forgery detection methods using noise features are reviewed and compared in this paper for image and video. The overall objective of this paper is to give researchers a broad perspective on various aspects of image and video forensics using noise features. Conclusion part of this paper discusses about the importance of noise features and the challenges encountered by different image and video forensic method using noise features.     

A novel file carving algorithm for National Marine Electronics Association (NMEA) logs in GPS forensics

Globe positioning system (GPS) devices are an increasing importance source of evidence, as more of our devices have built-in GPS capabilities. In this paper, we propose a novel framework to efficiently recover National Marine Electronics Association (NMEA) logs and reconstruct GPS trajectories. Unlike existing approaches that require file system metadata, our proposed algorithm is designed based on the file carving technique without relying on system metadata. By understanding the characteristics and intrinsic structure of trajectory data in NMEA logs, we demonstrate how to pinpoint all data blocks belonging to the NMEA logs from the acquired forensic image of GPS device. Then, a discriminator is presented to determine whether two data blocks can be merged. And based on the discriminator, we design a reassembly algorithm to re-order and merge the obtained data blocks into new logs. In this context, deleted trajectories can be reconstructed by analyzing the recovered logs. Empirical experiments demonstrate that our proposed algorithm performs well when the system metadata is available/unavailable, log files are heavily fragmented, one or more parts of the log files are overwritten, and for different file systems of variable cluster sizes.     

Forensic investigation framework for the document store NoSQL DBMS: MongoDB as a case study

The NoSQL DBMS provides an efficient means of storing and accessing big data because its servers are more easily horizontally scalable and replicable than relational DBMSs. Its data model lacks a fixed schema, so that users can easily dynamically change the data model of applications. These characteristics of the NoSQL DBMS mean that it is increasingly used in real-time analysis, web services such as SNS, mobile apps and the storage of machine generated data such as logs and IoT (Internet of Things) data. Although the increased usage of the NoSQL DBMS increases the possibility of it becoming a target of crime, there are few papers about forensic investigation of NoSQL DBMS.In this paper, we propose a forensic investigation framework for the document store NoSQL DBMS. It is difficult to cover all of the NoSQL DBMS, as 'NoSQL' includes several distinct architectures; our forensic investigation framework, however, is focused on the document store NoSQL DBMS. In order to conduct an evaluative case study, we need to apply it to MongoDB, which is, a widely used document store NoSQL DBMS. For this case study, a crime scenario is created in an experimental environment, and then we propose in detail a forensic procedure and technical methods for MongoDB. We suggested many substantial technical investigation methods for MongoDB, including identifying real servers storing evidences in a distributed environment and transaction reconstruction method, using log analysis and recovering deleted data from the MongoDB data file structure.     

BitTorrent Sync: First Impressions and Digital Forensic Implications

With professional and home Internet users becoming increasingly concerned with data protection and privacy, the privacy afforded by popular cloud file synchronisation services, such as Dropbox, OneDrive and Google Drive, is coming under scrutiny in the press. A number of these services have recently been reported as sharing information with governmental security agencies without warrants. BitTorrent Sync is seen as an alternative by many and has gathered over two million users by December 2013 (doubling since the previous month). The service is completely decentralised, offers much of the same synchronisation functionality of cloud powered services and utilises encryption for data transmission (and optionally for remote storage). The importance of understanding BitTorrent Sync and its resulting digital investigative implications for law enforcement and forensic investigators will be paramount to future investigations. This paper outlines the client application, its detected network traffic and identifies artefacts that may be of value as evidence for future digital investigations.     

Forensic integrity verification of video recordings based on MTS files

Digital video is used in criminal trials as evidence with legal responsibility because video content vividly depicts events occurring at a crime scene. However, using sophisticated video editing software, assailants can easily manipulate visible clues for their own benefit. Therefore, the integrity of digital video files acquired or submitted as evidence must be ensured. Forensic analysis of digital video is key to ensuring the integrity of links with individual cameras. In this study, we analyzed whether it is possible to ensure the integrity of MTS video files. Herein, we propose a method to verify the integrity of MTS files encoded by advanced video coding high definition (AVCHD), which is frequently used for video recording. To verify MTS file integrity, we propose five features. Codec information, picture timing, and camera manufacture/model are modified AVI and MP4-like format video verification features. Group of pictures and Universally Unique Identifier patterns were specifically developed for MTS streams. We analyzed the features of 44 standard files recorded using all recording options of seven cameras. We checked whether integrity can be validated on unmanipulated videos recorded in various environments. In addition, we considered whether manipulated MTS files edited in video editing software could be validated. Experimental results show that all unmanipulated and manipulated MTS files with known recording devices were discriminated only when all five features were checked. These results show that the proposed method verifies the integrity of MTS files, strengthening the validity of MTS file-based evidence in trials.     

Forensic Taxonomy of Android Social Apps

An Android social app taxonomy incorporating artifacts that are of forensic interest will enable users and forensic investigators to identify the personally identifiable information (PII) stored by the apps. In this study, 30 popular Android social apps were examined. Artifacts of forensic interest (e.g., contacts lists, chronology of messages, and timestamp of an added contact) were recovered. In addition, images were located, and Facebook token strings used to tie account identities and gain access to information entered into Facebook by a user were identified. Based on the findings, a two‐dimensional taxonomy of the forensic artifacts of the social apps is proposed. A comparative summary of existing forensic taxonomies of different categories of Android apps, designed to facilitate timely collection and analysis of evidentiary materials from Android devices, is presented.     

Forensic analysis of Telegram Messenger on Android smartphones

In this paper we present a methodology for the forensic analysis of the artifacts generated on Android smartphones by Telegram Messenger, the official client for the Telegram instant messaging platform, which provides various forms of secure individual and group communication, by means of which both textual and non-textual messages can be exchanged among users, as well as voice calls.Our methodology is based on the design of a set of experiments suitable to elicit the generation of artifacts and their retention on the device storage, and on the use of virtualized smartphones to ensure the generality of the results and the full repeatability of the experiments, so that our findings can be reproduced and validated by a third-party.In this paper we show that, by using the proposed methodology, we are able (a) to identify all the artifacts generated by Telegram Messenger, (b) to decode and interpret each one of them, and (c) to correlate them in order to infer various types of information that cannot be obtained by considering each one of them in isolation.As a result, in this paper we show how to reconstruct the list of contacts, the chronology and contents of the messages that have been exchanged by users, as well as the contents of files that have been sent or received. Furthermore, we show how to determine significant properties of the various chats, groups, and channels in which the user has been involved (e.g., the identifier of the creator, the date of creation, the date of joining, etc.). Finally, we show how to reconstruct the log of the voice calls made or received by the user.Although in this paper we focus on Telegram Messenger, our methodology can be applied to the forensic analysis of any application running on the Android platform.     

电子邮件真伪鉴定初探

电子邮件作为网络沟通常见的形式之一，应用十分广泛，但涉及电子邮件的相关纠纷与犯罪问题也日益突出。很多案件由于无法判明电子邮件证据真实性，而导致诉讼无法正常进行、无奈拖延或者失败。为确定电子邮件证据真实性，对其进行科学鉴定显得十分重要，但电子邮件不同传统的物证、书证鉴定，其本身十分复杂，对其鉴定研究，必须分析常见的伪造形式，以及如何伪造，并在此基础上探讨鉴定的主要思路。     

Forensic Investigation of Cooperative Storage Cloud Service: Symform as a Case Study

Researchers envisioned Storage as a Service (StaaS) as an effective solution to the distributed management of digital data. Cooperative storage cloud forensic is relatively new and is an under‐explored area of research. Using Symform as a case study, we seek to determine the data remnants from the use of cooperative cloud storage services. In particular, we consider both mobile devices and personal computers running various popular operating systems, namely Windows 8.1, Mac OS X Mavericks 10.9.5, Ubuntu 14.04.1 LTS, iOS 7.1.2, and Android KitKat 4.4.4. Potential artefacts recovered during the research include data relating to the installation and uninstallation of the cloud applications, log‐in to and log‐out from Symform account using the client application, file synchronization as well as their time stamp information. This research contributes to an in‐depth understanding of the types of terrestrial artifacts that are likely to remain after the use of cooperative storage cloud on client devices.     

A comparison of forensic evidence recovery techniques for a windows mobile smart phone

Acquisition, decoding and presentation of information from mobile devices is complex and challenging. Device memory is usually integrated into the device, making isolation prior to recovery difficult. In addition, manufacturers have adopted a variety of file systems and formats complicating decoding and presentation.A variety of tools and methods have been developed (both commercially and in the open source community) to assist mobile forensics investigators. However, it is unclear to what extent these tools can present a complete view of the information held on a mobile device, or the extent the results produced by different tools are consistent.This paper investigates what information held on a Windows Mobile smart phone can be recovered using several different approaches to acquisition and decoding. The paper demonstrates that no one technique recovers all information of potential forensic interest from a Windows Mobile device; and that in some cases the information recovered is conflicting.     

Forensic investigation of cross platform massively multiplayer online games: Minecraft as a case study

Minecraft, a Massively Multiplayer Online Game (MMOG), has reportedly millions of players from different age groups worldwide. With Minecraft being so popular, particularly with younger audiences, it is no surprise that the interactive nature of Minecraft has facilitated the commission of criminal activities such as denial of service attacks against gamers, cyberbullying, swatting, sexual communication, and online child grooming. In this research, there is a simulated scenario of a typical Minecraft setting, using a Linux Ubuntu 16.04.3 machine (acting as the MMOG server) and Windows client devices running Minecraft. Server and client devices are then examined to reveal the type and extent of evidential artefacts that can be extracted.     

Windows系统中文件时间属性的变化及影响因素

目的分析Windows系统中不同因素对文件时间属性的影响,总结文件时间属性的变化规律。方法在FAT32和NTFS两种文件系统中,对文件和文件夹进行各种操作,记录其时间属性的变化情况,总结其规律并分析各种因素的影响。结果文件时间属性的更新与系统环境、操作方法、文件类型等因素有关,而且文件时间属性更新有特定的周期。结论Windows系统中文件时间属性的变化既有特定的规律,又受其它因素影响,在检验中应加以注意。