Android Forensics Research Articles

Decoding digital interactions: An extensive study of TeamViewer's Forensic Artifacts across Windows and android platforms

The pervasive influence of digital technology has ushered in a new era of connectivity, reshaping the landscape of forensic science and challenging investigators to adapt to evolving methods of digital interaction. Remote access applications (RAAs) like TeamViewer have become integral tools for facilitating remote collaboration and support across various platforms. However, the widespread adoption of such applications has also led to an increase in cybercrimes, underscoring the critical need for meticulous forensic analysis. This study presents a comprehensive examination of TeamViewer's forensic artifacts across Windows and Android platforms, employing advanced forensic techniques such as registry analysis, disk forensics, memory forensics, and Android forensics. By meticulously dissecting digital evidence and uncovering valuable insights into user interactions, configuration settings, and session dynamics, this research aims to enhance understanding of remote access activities and empower forensic investigators with the tools needed to combat cybercrimes effectively. The findings highlight the forensic significance of each investigative approach and underscore the importance of continuous innovation in the field of digital forensics.

Study of identifying and managing the potential evidence for effective Android forensics

Since the advent of various IoT devices, the need for digital forensics for mobile devices that people use most closely in their daily lives has continued to grow. Besides, as Bring Your Own Device (BYOD) becomes the trend, devices store business-related information as well as privacy. Thus, mobile devices are becoming the most critical evidence of digital forensics. For practical mobile forensics, it is necessary to identify crime-related items among the many files inside the device accurately. Also, various user information for user behavior analysis from these files should be effectively extracted and managed as potential evidence to ensure integrity. This paper proposes an efficient forensics investigation method for mobile devices with Android OS, which holds the highest share in the world among mobile devices. In this paper, we studied data pre-processing (classification and identification of data), data analysis, evidence management, and Android data Taxonomy.

Identifying artefact on Microsoft OneDrive client to support Android forensics

Identifying artefact on Microsoft OneDrive client to support Android forensics

Identifying artefact on Microsoft OneDrive client to support Android forensics

Microsoft software is perhaps the most widely used around the world. As computing technology has evolved they have been at the cutting edge and have developed a number of groundbreaking and useful applications. Microsoft OneDrive is one such application. OneDrive is a cloud storage service offering 7 GB free storage to users. This technology can be misused and through it laws governing the cyber world violated. Current solutions to this are to perform digital forensics when cybercrime has occurred. This research used two different vendors of Android smartphones as experimentation objects. A model has been developed in this research, which provides instructions for digital mobile forensics analysis in finding artefacts related to the client's activities on OneDrive cloud storage application. These artefacts can be used as digital evidence by digital forensics investigators and the research increases the knowledge of cyber law practitioners.

Proposed Workable Process Flow with Analysis Framework for Android Forensics in Cyber-Crime Investigation

Proposed Workable Process Flow with Analysis Framework for Android Forensics in Cyber-Crime Investigation

An Android Communication App Forensic Taxonomy.

Due to the popularity of Android devices and applications (apps), Android forensics is one of the most studied topics within mobile forensics. Communication apps, such as instant messaging and Voice over IP (VoIP), are one popular app category used by mobile device users, including criminals. Therefore, a taxonomy outlining artifacts of forensic interest involving the use of Android communication apps will facilitate the timely collection and analysis of evidentiary materials from such apps. In this paper, 30 popular Android communication apps were examined, where a logical extraction of the Android phone images was collected using XRY, a widely used mobile forensic tool. Various information of forensic interest, such as contact lists and chronology of messages, was recovered. Based on the findings, a two-dimensional taxonomy of the forensic artifacts of the communication apps is proposed, with the app categories in one dimension and the classes of artifacts in the other dimension. Finally, the artifacts identified in the study of the 30 communication apps are summarized using the taxonomy. It is expected that the proposed taxonomy and the forensic findings in this paper will assist forensic investigations involving Android communication apps.

오류주입공격 실험 정밀도 분석 및 개선지표

ABSTRACT As the utilization rate of smart device increases, various applications for smart device have been developed. Since these applications can contain important data related to user behavio rs in digital forensic perspective, the analysis of them should be conducted in advance. However, lots of applications get to have new data format or type when they are updated. Therefore, whether the applications are updated or not should be checked o ne by one, and if they are, whether their data are changed should be also analyzed. But observing application data repeatedly is a time-consuming task, and that is why the effective method for dealing with this problem is needed. This paper suggests the automatic system which gets updated inf ormation and checks changed data by collecting application information. Keywords: Digital Forensics, Smartphone Forensics, Android Forensics, An droid Application, Android Data Acquisition접수일(2013년 12월 31일), 수정일(2014년 3월 4일), 게재확정일(2014년 3월 4일)* 본 연구는 2013년도 정부(교육과학기술부)의 재원으로 한국연구재단의 기초연구사업 지원을 받아 수행된 것임(과제번호: 2013-071188). 또한 부산광역시에서 지원하는 BB21과제에서 지원받았음.† 주저자, feei_@naver.com

Android forensics: Automated data collection and reporting from a mobile device

In this research, a prototype enterprise monitoring system for Android smartphones was developed to continuously collect many data sets of interest to incident responders, security auditors, proactive security monitors, and forensic investigators. Many of the data sets covered were not found in other available enterprise monitoring tools. The prototype system neither requires root privileges nor the exploiting of the Android architecture for proper operation, thereby increasing interoperability among Android devices and avoiding a spyware classification for the system. An anti-forensics analysis on the system was performed to identify and further strengthen areas vulnerable to tampering. The contributions of this research include the release of the first open-source Android enterprise monitoring solution of its kind, a comprehensive guide of data sets available for collection without elevated privileges, and the introduction of a novel design strategy implementing various Android application components useful for monitoring on the Android platform.

개인정보보호를 위한 안드로이드 로그캣 시스템 연구

최근 스마트폰의 급격한 보급으로 개인정보 침해사고 및 프라이버시 침해를 통한 여러 가지 사회문제가 급속도로 증가하고 있으며, 이에 따라 개인 정보보호를 위한 다양한 연구 및 기술 개발이 이루어지고 있다. 개인의 모든 정보가 거의 들어 있다고 해도 과언이 아닌 스마트폰의 정보유출은 우리의 일상에서 쉽고 빈번하게 발생할 수 있는데, 포렌식 분석 툴을 이용하여 증거를 수집하거나 분석하기란 쉽지 않은 일이다. 현재 안드로이드 포렌식 연구는 비휘발성 메모리로부터 데이터를 수집하여 분석하는 기법에 집중되어 왔으며, 휘발성 데이터에 대한 연구는 미미한 실정이다. 안드로이드 로그는 휘발성 저장매체로부터 수집될 수 있는 휘발성 데이터이다. 안드로이드 로그는 안드로이드 시스템에서부터 애플리케이션에 이르기까지 최근의 모든 구동내역과 관련한 기록이 로그로 저장되기 때문에 안드로이드폰 사용을 추적할 수 있는 자료로 활용이 충분하다. 본 논문에서는 포렌식 분석 툴을 이용하지 않고 로그를 필터링하여 개인의 정보 유출 유무를 판단하여 대응할 수 있는 방법을 제시한다. Various social problems through violating personal information and privacy are growing with the rapid spread of smartphones. For this reason, variety of researches and technology developments to protect personal information being made. The smartphone, contains almost all of the personal information, can cause data spill at any time. Collecting or analyzing evidence is not an easy job with forensic analyzing tool. Android forensics research has been focused on techniques to collect and analyze data from non-volatile memory but research for volatile data is very slight. Android log is the non-volatile data that can be collected by volatile storage. It is enough to use as a material to track the usage of the Android phone because all of the recent driven records from system to application are stored. In this paper, we propose a method to respond to determining the existence of personal information leakage by filtering logs without forensic analysis tools.