Journal articles: 'Digital forensic analysis'

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Sachdeva, Shaweta, B. L. Raina, and Avinash Sharma. "Analysis of Digital Forensic Tools." Journal of Computational and Theoretical Nanoscience 17, no. 6 (June 1, 2020): 2459–67. http://dx.doi.org/10.1166/jctn.2020.8916.

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This paper aims to analyze different tools for Forensic Data Analysis comes under the branch of Digital Forensics. Forensic data analysis is done with digital techniques. Digital forensics becomes more important in law enforcement, due to the large use of computers and mobile devices. The pattern recognition system most appropriately fits into the Analysis Phase of the Digital Forensics. Pattern Recognition involves two processes. One Process is an analysis and the second process is recognition. The result of the analysis is taken out of the attributes from the patterns to be recognized i.e., a pattern of different faces and fingerprints. These attributes are then utilized for the further process in the analysis phase which provides attention on various techniques of pattern recognition that are applied to digital forensic examinations and is proposed to develop different forensic tools to collect evidence that would be helpful to solve specific types of crimes. This evidence further helps the examiner in the analysis phase of the digital forensic process by identifying the applicable data.

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Sabillon, Regner, Jordi Serra-Ruiz, Victor Cavaller, and Jeimy J. Cano. "Digital Forensic Analysis of Cybercrimes." International Journal of Information Security and Privacy 11, no. 2 (April 2017): 25–37. http://dx.doi.org/10.4018/ijisp.2017040103.

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This paper reviews the existing methodologies and best practices for digital investigations phases like collecting, evaluating and preserving digital forensic evidence and chain of custody of cybercrimes. Cybercriminals are adopting new strategies to launch cyberattacks within modified and ever changing digital ecosystems, this article proposes that digital investigations must continually readapt to tackle cybercrimes and prosecute cybercriminals, working in international collaboration networks, sharing prevention knowledge and lessons learned. The authors also introduce a compact cyber forensics model for diverse technological ecosystems called Cyber Forensics Model in Digital Ecosystems (CFMDE). Transferring the knowledge, international collaboration, best practices and adopting new digital forensic tools, methodologies and techniques will be hereinafter paramount to obtain digital evidence, enforce organizational cybersecurity policies, mitigate security threats, fight anti-forensics practices and indict cybercriminals. The global Digital Forensics community ought to constantly update current practices to deal with cybercriminality and foreseeing how to prepare to new technological environments where change is always constant.

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Jafari, Fakeeha, and Rabail Shafique Satti. "Comparative Analysis of Digital Forensic Models." Journal of Advances in Computer Networks 3, no. 1 (2015): 82–86. http://dx.doi.org/10.7763/jacn.2015.v3.146.

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Hikmatyar, Firmansyah Gustav, and Bambang Sugiantoro. "Digital Forensic Analysis on Android Smartphones for Handling Cybercrime Cases." IJID (International Journal on Informatics for Development) 7, no. 2 (January 7, 2019): 19. http://dx.doi.org/10.14421/ijid.2018.07204.

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As the times progressed, forensic science has developed rapidly. The science of forensics extends to new areas of technology ranging from digital forensics, computer forensics and mobile forensics. Mobile forensics in analyzing and collecting data is obtained from various resources, such as operating systems, communication lines and also various storage media. The most popular mobile operating system of the day is a smartphone based on android operating system. With android technology, criminals can use that technology as a crime medium ranging from overriding crime ideas, crime targets and crime scenarios. In this Final Project use forensic mobile application to get data residing in cell phone actors, in the form of text, sound, picture and video that have or not yet deleted in smartphone. In this study, a model for investigating the crime scene is the author using the Generic Computer Forensic Investigation Model (GCFIM). On the GCFIM model the investigator may be able to return to the previous stage because of the possibility of a changeable situation (both physical and digital), the investigation tools used, the crime tools used, and the level of investigative expertise. In this research also added weighting method of word TF-IDF, where this method can help to find keyword in digital evidence in the form of word / text.

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Faiz, Muhammad Nur, Rusydi Umar, and Anton Yudhana. "Implementasi Live Forensics untuk Perbandingan Browser pada Keamanan Email." JISKA (Jurnal Informatika Sunan Kalijaga) 1, no. 3 (March 30, 2017): 108. http://dx.doi.org/10.14421/jiska.2017.13-02.

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Digital Forensics become one popular term because Currently many violations of cyber crime. Digital techniques Computer Forensics performed or with analyze digital device, whether the device is a media Actors or as a media victim. Digital Forensic Analysis Being divided into two, traditional / dead and alive. Forensic analysis traditionally involves digital data Deposited permanent Operates in Irish, while live forensic analysis involves analysis of data Namely temporary in Random Access Memory or Deposited hearts transport equipment in the Network. Singer proposes journal Forensic analysis of life in the latest operation system windows 10. That study focused IN case several email security browsers Sales Operations manager of Google Chrome, Mozilla Firefox, and Microsoft Internet Explorer Edge. In addition, although many digital forensics type software applications not free, goal on research objectives compares browser security information so it will be more minimize abuse email.

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Mualfah, Desti, and Rizdqi Akbar Ramadhan. "Analisis Forensik Metadata Kamera CCTV Sebagai Alat Bukti Digital." Digital Zone: Jurnal Teknologi Informasi dan Komunikasi 11, no. 2 (November 7, 2020): 257–67. http://dx.doi.org/10.31849/digitalzone.v11i2.5174.

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Kejahatan konvensial yang terekam kamera CCTV (Closed Circuit Televison) semakin banyak ditemukan di masyarakat, setiap pelaku kejahatan yang terbukti melakukan tindak pidana tertentu akan dihukum sesuai dengan peraturan perundang-undangan. Kamera CCTV memiliki peran penting dalam keamanan, banyak diantaranya hasil tangkapan rekaman kamera CCTV dijadikan sebagai alat bukti digital. Tantangannya adalah bagaimana teknik yang diperlukan untuk penanganan khusus investigasi digital forensik dalam mencari bukti ditgital rekaman kamera CCTV menggunakan metode live forensik, yaitu ketika barang bukti dalam keadan aktif berdasarkan pedoman SNI 27037:2014 sesuai acuan kerangka kerja Common Phases of Computer Forensics Investigation Models untuk di implementasikan ke dalam dokumen Chain of Custody. Hasil penelitian ini berupa hasil analisis video rekaman kamera CCTV tentang karakteristik bukti digital dan informasi metadata yang digunakan untuk memberikan penjelasan komprehensif secara terstruktur serta acuan pengelolaan informasi data yang didapat dari hasil investigasi digital forensik yang dapat dipertanggungjawabkan dalam persidangan. Kata kunci: Bukti Digital, Live Forensik, Metadata, Kamera CCTV, Chain of Custody. Abstract Conventional crimes that are recorded on CCTV (Closed Circuit Television) cameras are increasingly being found in society, every crime that commits certain crimes will be in accordance with statutory regulations. CCTV cameras have an important role in security, many of which are recorded by CCTV cameras used as digital evidence. The challenge is how the techniques required for special handling, digital forensics in searching for digital evidence of CCTV camera footage using the live forensic method, namely when the evidence is in an active state based on the latest SNI 27037: 2014 according to the framework reference Common Phases of Computer Forensics Investigation Models for in implement it into the Chain of Custody document. These results of this research are in the form of analysis of CCTV camera video recordings about the characteristics of digital evidence and metadata information used to provide a structured comprehensive explanation and reference data management information obtained from the results of digital forensic investigations that can be accounted for in court. Keywords: Digital Evidence, Live Forensic, Metadata, CCTV Camera, Chain of Custady.

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Dumchykov, M. "THE PROCESSES OF DIGITIZATION AND FORENSICS: A RETROSPECTIVE ANALYSIS." Criminalistics and Forensics, no. 65 (May 18, 2020): 100–108. http://dx.doi.org/10.33994/kndise.2020.65.10.

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The article deals with some aspects of digitalization of forensic activity, such as improving the efficiency of search and cognitive activity of an investigator using digital technologies, and effective organization of such activity. Use of computer hardware, software, various computer and digital technologies and scripting to investigate crimes. The definitions of “digital trace” and “virtual trace” demonstrate the complexity of these issues. Certain dynamic movement of criminal activity in the information environment is analyzed. Defines the concept of virtual trace as a specific trace of certain actions in the information space of computer devices and their network systems. In considering the definition of the concept of virtual trace, the views of scientists such as V.A. Meshcheriakov, V.V. Poliakov and Smushkin A.V. The aspects of consideration of forensic digitization are identified, among which the main ones are: – use of digital technologies to increase the effectiveness of search and cognitive activity of the investigator, effective organization of this activity at the present level, optimization of interaction of different bodies, institutions in the investigation of crimes. – the use of information and communication technologies to investigate crimes. – solving didactic tasks in the field of training, retraining, advanced training of investigators, criminal investigators, forensic experts, improvement of their qualification, exchange of experience. The further question of the development of forensic science in the field of information society is investigated. It is determined in what form the information forensics will exist, namely: A new section of classic forensics that focuses on working with digital and virtual footprints. The new science of “digital or virtual forensics”. 3. Independent forensic science within the framework of the general theory of forensic science, which integrates the development of virtual traces, the use of new technical means of finding, fixing, research, use in proving forensically relevant information, technologies that ensure the effectiveness of the investigator.

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Zuhriyanto, Ikhsan, Anton Yudhana, and Imam Riadi. "Comparative analysis of Forensic Tools on Twitter applications using the DFRWS method." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 4, no. 5 (October 30, 2020): 829–36. http://dx.doi.org/10.29207/resti.v4i5.2152.

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Current crime is increasing, one of which is the crime of using social media, although no crime does not leave digital evidence. Twitter application is a social media that is widely used by its users. Acts of crime such as fraud, insults, hate speech, and other crimes lately use many social media applications, especially Twitter. This research was conducted to find forensic evidence on the social media Twitter application that is accessed using a smartphone application using the Digital Forensics Research Workshop (DFRWS) method. These digital forensic stages include identification, preservation, collection, examination, analysis, and presentation in finding digital evidence of crime using the MOBILedit Forensic Express software and Belkasoft Evidence Center. Digital evidence sought on smartphones can be found using case scenarios and 16 variables that have been created so that digital proof in the form of smartphone specifications, Twitter accounts, application versions, conversations in the way of messages and status. This study's results indicate that MOBILedit Forensic Express digital forensic software is better with an accuracy rate of 85.75% while Belkasoft Evidence Center is 43.75%.

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Vadlamudi, Divya, Dr K. Thirupathi Rao, Pellakuri Vidyullatha, and B. AjasekharReddy. "Analysis on digital forensics challenges and anti-forensics techniques in cloud computing." International Journal of Engineering & Technology 7, no. 2.7 (March 18, 2018): 1072. http://dx.doi.org/10.14419/ijet.v7i2.7.12230.

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In the modern life, there is a rapid increase in the usage of the technology. One reason of increasing the technology is usage of cloud. The mobile devices or any other technological devices mainly depend on cloud. The cloud can be accessible from anywhere. Cloud forensic process had introduced to help the investigators to find the evidence when the criminal attacks the cloud and to maintain the integrity and security for the data stored in the cloud. The increasing in the criminal attacks in cloud, made the investigators to find the latest methods for the forensic investigation process. Similarly in the same way the criminals also discover new ways to hide the source of evidences. This causes damage to the investigation process and is called anti-forensics. To hide the sources anti-forensic techniques are used and research must be done against the anti-forensics techniques in cloud environment. In this paper we focused mainly on detailed study on various challenges in cloud forensic and anti-forensic techniques.

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Lee, Jae-Ung, and Woo-Young Soh. "Comparative analysis on integrated digital forensic tools for digital forensic investigation." IOP Conference Series: Materials Science and Engineering 834 (June 23, 2020): 012034. http://dx.doi.org/10.1088/1757-899x/834/1/012034.

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Shree, Barkha, and Parneeta Dhaliwal. "Behavioural Evidence Analysis." International Journal of Digital Crime and Forensics 13, no. 5 (September 2021): 20–42. http://dx.doi.org/10.4018/ijdcf.20210901.oa2.

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Recent developments in digital forensics (DF) have emphasized that along with inspection of digital evidence, the study of behavioural clues based on behavioural evidence analysis (BEA) is vital for accurate and complete criminal investigation. This paper reviews the existing BEA approaches and process models and concludes the lack of standardisation in the BEA process. The research comprehends that existing BEA methodologies are restricted to specific characteristics of the forensic domain in question. To address these limitations, the paper proposes a standardised approach detailing the step-by-step implementation of BEA in the DF process. The proposed model presents a homogenous technique that can be practically applied to real-life cases. This standard BEA framework classifies digital evidence into categories to decipher associated offender characteristics. Unlike existing models, this new approach collects evidence from diverse sources and leaves no aspect unattended while probing criminal behavioural cues, thus facilitating its applicability across varied forensic domains.

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Hani Roslee, Nurul Adhlina, and Nurul Hidayah Bt Ab Rahman. "A Visualization Approach to Analyze Android Smartphone Data." JOIV : International Journal on Informatics Visualization 2, no. 3-2 (June 6, 2018): 184. http://dx.doi.org/10.30630/joiv.2.3-2.137.

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This study aims to design and develop an interactive system that can visualize evidence collected from Android smartphone data. This project is developing to support forensic investigator in investigating the security incidents particularly involving Android smartphone forensic data. The used of smartphone in crime was widely recognized. Several types of personnel information are stored in their smartphones. When the investigator analyses the image data of the smartphone, the investigator can know the behaviour of the smartphone’s owner and his social relationship with other people. The analysis of smartphone forensic data is cover in mobile device forensic. Mobile device forensics is a branch of digital forensics relating to recovery of digital evidence from a mobile device under forensically sound condition. The digital investigation model used in this project is the model proposed by United States National Institute of Justice (NIJ) which consists four phases, which are collection phase, examination phase, analysis phase and presentation phase. This project related with analysis phase and presentation phase only. This paper introduces Visroid, a new tool that provides a suite of visualization for Android smartphone data.

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Jiang, Jian Guo, Bo Yang, Sen Lin, Ming Xing Zhang, and Kun Ying Liu. "A Practical Approach for Digital Forensic Triage." Applied Mechanics and Materials 742 (March 2015): 437–44. http://dx.doi.org/10.4028/www.scientific.net/amm.742.437.

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In order to uncover truths to serve justice, case-related data collected from a digital investigation requires substantial resources to analyze, especially in time-critical situations. At present, however, digital forensics has not evolved to meet this ever-increasing demand. Digital forensic triage is a promising solution, as it is designed to maximize the use of resources according to a system of priorities, and hence the efficiency and effectiveness of forensic examinations can be increased. Nevertheless, the lack of concrete methods limits efforts to implement triage. This paper presents a practical approach that is designed to build a prioritizing solution. In this work a new process model is derived based on the presented approach, and it is particularly suited to scenarios where forensic examiners do not have enough time and resources to conduct a full examination and analysis. An example is described to demonstrate how this approach can be used to meet the requirements of network forensic investigations.

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Bashir, Muhammad, and M. Khan. "Triage in Live Digital Forensic Analysis." International Journal of Forensic Computer Science 8, no. 1 (July 2, 2013): 35–44. http://dx.doi.org/10.5769/j201301005.

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Carrier, Brian D. "Risks of live digital forensic analysis." Communications of the ACM 49, no. 2 (February 2006): 56–61. http://dx.doi.org/10.1145/1113034.1113069.

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Huamaní, Enrique Lee. "High performance computer analysis for indexing emails in digital forensic analysis (Computer Forensics)." International Journal of Advanced Trends in Computer Science and Engineering 9, no. 4 (August 25, 2020): 5867–71. http://dx.doi.org/10.30534/ijatcse/2020/247942020.

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Nizam, Syafiqah Hanisah Shahrol, Nurul Hidayah Ab Rahman, and Niken Dwi Wahyu Cahyani. "Keyword Indexing And Searching Tool (KIST): A Tool to Assist the Forensics Analysis of WhatsApp Chat." International Journal on Information and Communication Technology (IJoICT) 6, no. 1 (June 20, 2020): 23. http://dx.doi.org/10.21108/ijoict.2020.61.481.

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Digital forensics is a field that concerned with finding and presenting evidence sourced from digital devices, such as computers and mobile phones. Most of the forensic analysis software is proprietary, and eventually, specialized analysis software is developed in both the private and public sectors. This paper presents an alternative of forensic analysis tools for digital forensics, which specifically to analyze evidence through keyword indexing and searching. Keyword Indexing and Searching Tool (KIST) is proposed to analyze evidence of interest from WhatsApp chat text files using keyword searching techniques and based on incident types. The tool was developed by adopting the Prototyping model as its methodology. KIST includes modules such as add, edit, remove, display the indexed files, and to add WhatsApp chat text files. Subsequently, the tool is tested using functionality testing and user testing. Functionality testing shows all key functions are working as intended, while users testing indicates the majority of respondents are agree that the tool is able to index and search keyword and display forensic analysis results.

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Lempereur, Brett, Madjid Merabti, and Qi Shi. "Pypette." International Journal of Digital Crime and Forensics 4, no. 4 (October 2012): 31–46. http://dx.doi.org/10.4018/jdcf.2012100103.

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Live digital forensics presents unique challenges with respect to maintaining forensic soundness, but also offers the ability to examine information that is unavailable to quiescent analysis. Any perturbation of a live operating system by a forensic examiner will have far-reaching effects on the state of the system being analysed. Numerous approaches to live digital forensic evidence acquisition have been proposed in the literature, but relatively little attention has been paid to the problem of identifying how the effects of these approaches, and their improvements over other techniques, can be evaluated and quantified. In this paper, the authors present Pypette, a novel platform enabling the automated, repeatable analysis of live digital forensic acquisition techniques.

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Mahendra, Kadek Dwi Oka, and I. Komang Ari Mogi. "Digital Forensic Analysis Of Michat Application On Android As Digital Proof In Handling Online Prostitution Cases." JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) 9, no. 3 (February 18, 2021): 381. http://dx.doi.org/10.24843/jlk.2021.v09.i03.p09.

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Smartphone technology and the Internet are very popular lately, especially with various features, one of which is instant messaging. But behind it all, instant messaging like MiChat is very vulnerable to becoming a crime, one of which is Online Prostitution. To follow up on Online Prostitution activities, it is necessary to carry out mobile forensics to find evidence which is then given to be given to the authorities. This study uses the MiChat application as an online prostitution media, and uses the National Institute of Justice (NIJ) method which has five basic stages is, preparation, collection, examination, analysis, and reporting. This research uses MOBILedit Forensic Express, and SysTools SQLite Viewer.

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Wang, Yan, Qindong Sun, Dongzhu Rong, Shancang Li, and Li Da Xu. "Image Source Identification Using Convolutional Neural Networks in IoT Environment." Wireless Communications and Mobile Computing 2021 (September 10, 2021): 1–12. http://dx.doi.org/10.1155/2021/5804665.

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Digital image forensics is a key branch of digital forensics that based on forensic analysis of image authenticity and image content. The advances in new techniques, such as smart devices, Internet of Things (IoT), artificial images, and social networks, make forensic image analysis play an increasing role in a wide range of criminal case investigation. This work focuses on image source identification by analysing both the fingerprints of digital devices and images in IoT environment. A new convolutional neural network (CNN) method is proposed to identify the source devices that token an image in social IoT environment. The experimental results show that the proposed method can effectively identify the source devices with high accuracy.

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Joseph, Paul, and Jasmine Norman. "Systematic Memory Forensic Analysis of Ransomware using Digital Forensic Tools." International Journal of Natural Computing Research 9, no. 2 (April 2020): 61–81. http://dx.doi.org/10.4018/ijncr.2020040105.

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Cybercrimes catastrophically caused great financial loss in the year 2018 as powerful obfuscated malware known as ransomware continued to be a continual threat to governments and organizations. Advanced malwares capable of system encryption with sophisticated obscure keys left organizations paying the ransom that hackers demand. Since every individual is vulnerable to this assault, cyber forensics play a vital role either in educating society or combating the attacks. As cyber forensics is classified into many subdomains, memory forensics is the domain that leads in curbing these types of attacks. This article gives insight on importance of memory forensics and provides widespread analysis on working of ransomware, recognizes the workflow, provides the ways to overcome this attack. Furthermore, this article implements user defined rules by integrating into powerful search tools known as YARA to detect and prevent the ransomware attacks.

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Voznyuk, M. A., and Yu A. Denisov. "Forensic Diagnostics of the Circumstances of Digital Video and Audio Production: Analytical Review." Theory and Practice of Forensic Science 12, no. 1 (March 30, 2017): 48–71. http://dx.doi.org/10.30764/64/1819-2785-2017-12-1-48-71.

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The analytical review examines the issues of forensic investigation into the circumstances of production of digital video and audio recordings. The paper presents the organization and lines of inquiry in forensic analysis of video and audio evidence, computer forensics, forensic linguistics, and psychological evaluation established in the system of forensic science organizations of the Russian Ministry of Justice by 2013–2016. The analysis covers the issues of independent or integrated application of the listed types of special knowledge in order to meet the discipline-specific and comprehensive objectives of determining the circumstances of video/audio production. General strategies and types of forensic diagnostics of production circumstances are discussed without too much emphasis on the methodological minutiae of every stage of the investigation.

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N. Patil, Dinesh. "Digital Forensic Analysis of Ubuntu File System." International Journal of Cyber-Security and Digital Forensics 5, no. 4 (2016): 175–86. http://dx.doi.org/10.17781/p002213.

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Inglot, Bartosz, and Lu Liu. "Enhanced Timeline Analysis for Digital Forensic Investigations." Information Security Journal: A Global Perspective 23, no. 1-2 (January 2, 2014): 32–44. http://dx.doi.org/10.1080/19393555.2014.897401.

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Casey, Eoghan. "Focused digital evidence analysis and forensic distinguishers." Digital Investigation 18 (September 2016): A1—A3. http://dx.doi.org/10.1016/j.diin.2016.08.004.

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Wang, Jian, Zhen Min Tang, and Xian Li Jin. "An OCL-Based Formal Model for Cloud Forensics." Advanced Materials Research 989-994 (July 2014): 1513–16. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.1513.

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Cloud Computing is gaining acceptance and increasing in popularity. However, digital forensics within Cloud becomes difficult. This paper proposes an extensible semantic model using OCL (Object Constraint Language) for cloud digital forensics data. We give a brief introduction to Trusted Digital Forensics, and then detail the modeling process using OCL and FODA (Feature Oriented Domain Analysis). Therefore, a feature tree can be built with semantic logical relation in order to get the overall semantic description of features in the forensic domain of digital data.

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H Bhat, Veena, Prasanth G. Rao, Abhilash R. V, P. Deepa Shenoy, Venugopal K. R., and L. M. Patnaik. "A Data Mining Approach for Data Generation and Analysis for Digital Forensic Application." International Journal of Engineering and Technology 2, no. 3 (2010): 313–19. http://dx.doi.org/10.7763/ijet.2010.v2.140.

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Kao, Da-Yu. "Forensic Exchange Analysis of Contact Artifacts on Data Hiding Timestamps." Applied Sciences 10, no. 13 (July 7, 2020): 4686. http://dx.doi.org/10.3390/app10134686.

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When computer systems are increasingly important for our daily activities, cybercrime has created challenges for the criminal justice system. Data can be hidden in ADS (Alternate Data Stream) without hindering performance. This feature has been exploited by malware authors, criminals, terrorists, and intelligence agents to erase, tamper, or conceal secrets. However, ADS problems are much ignored in digital forensics. Rare researches illustrated the contact artifacts of ADS timestamps. This paper performs a sequence of experiments from an inherited variety and provides an in-depth overview of timestamp transfer on data hiding operations. It utilizes files or folders as original media and uses the timestamp rules as an investigative approach for the forensic exchange analysis of file sets. This paper also explores timestamp rules using case examples, which allow practical applications of crime scene reconstruction to real-world contexts. The experiment results demonstrate the effectiveness of temporal attributes, help digital forensic practitioners to uncover hidden relations, and trace the contact artifacts among crime scenes, victims, and suspects/criminals.

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Salamh, Fahad E., Umit Karabiyik, Marcus K. Rogers, and Eric T. Matson. "A Comparative UAV Forensic Analysis: Static and Live Digital Evidence Traceability Challenges." Drones 5, no. 2 (May 21, 2021): 42. http://dx.doi.org/10.3390/drones5020042.

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The raising accessibility of Unmanned Aerial Vehicles (UAVs), colloquially known as drones, is rapidly increasing. Recent studies have discussed challenges that may come in tow with the growing use of this technology. These studies note that in-depth examination is required, especially when addressing challenges that carry a high volume of software data between sensors, actuators, and control commands. This work underlines static and live digital evidence traceability challenges to further enhance the UAV incident response plan. To study the live UAV forensic traceability issues, we apply the ‘purple-teaming’ exercise on small UAVs while conducting UAV forensic examination to determine technical challenges related to data integrity and repeatability. In addition, this research highlights current static technical challenges that could pose more challenges in justifying the discovered digital evidence. Additionally, this study discusses potential drone anti-forensic techniques and their association with the type of use, environment, attack vector, and level of expertise. To this end, we propose the UAV Kill Chain and categorize the impact and complexity of all highlighted challenges based on the conducted examination and the presented scientific contribution in this work. To the best of our knowledge, there has not been any contribution that incorporates ‘Purple-Teaming’ tactics to evaluate UAV-related research in cybersecurity and digital forensics. This work also proposes a categorization model that classifies the discovered UAV static and live digital evidence challenges based on their complexity and impact levels.

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Umar, Rusydi, Anton Yudhana, and Muhammad Nur Faiz. "Experimental Analysis of Web Browser Sessions Using Live Forensics Method." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 5 (October 1, 2018): 2951. http://dx.doi.org/10.11591/ijece.v8i5.pp2951-2958.

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In today's digital era almost every aspect of life requires the internet, one way to access the internet is through a web browser. For security reasons, one developed is private mode. Unfortunately, some users using this feature do it for cybercrime. The use of this feature is to minimize the discovery of digital evidence. The standard investigative techniques of NIST need to be developed to uncover an ever-varied cybercrime. Live Forensics is an investigative development model for obtaining evidence of computer usage. This research provides a solution in forensic investigation effectively and efficiently by using live forensics. This paper proposes a framework for web browser analysis. Live Forensics allows investigators to obtain data from RAM that contains computer usage sessions.

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Akremi, Aymen, Mohamed-Foued Sriti, Hassen Sallay, and Mohsen Rouached. "Ontology-Based Smart Sound Digital Forensics Analysis for Web Services." International Journal of Web Services Research 16, no. 1 (January 2019): 70–92. http://dx.doi.org/10.4018/ijwsr.2019010104.

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The big data generated by today Web services makes very fastidious and time-consuming the investigators logs management and analysis tasks. This is due partly to the lack of an efficient web service dedicated log data representation. We introduce, in this paper, an extensible standard based semantic ontology representation of Web service log data to identify hidden information and extract eventual scenario of Cyber-attacks in the web logs. The proposed ontology supports the Web service specification and it satisfies the forensics and admissibility requirements. Through a friendly graphical user interface, the investigator can define validation rules and queries and execute them using a logical reasoner over the proposed ontology to get some comprehensive forensic report ready to present to the court. We also showed how the proposed ontology can facilitate the investigator analysis task, reduce required time, and enhance the forensics process comprehensiveness.

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Meister, Sam, and Alexandra Chassanoff. "Integrating Digital Forensics Techniques into Curatorial Tasks: A Case Study." International Journal of Digital Curation 9, no. 2 (September 9, 2014): 6–16. http://dx.doi.org/10.2218/ijdc.v9i2.325.

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In this paper, we investigate how digital forensics tools can support digital curation tasks around the acquisition, processing, management and analysis of born-digital materials. Using a real world born-digital collection as our use case, we describe how BitCurator, a digital forensics open source software environment, supports fundamental curatorial activities such as secure data transfer, assurance of authenticity and integrity, and the identification and elimination of private and/or sensitive information. We also introduce a workflow diagram that articulates the processing steps for institutions processing born-digital materials. Finally, we review possibilities for further integration, development and use of digital forensic tools.

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Salamh, Fahad E., Umit Karabiyik, and Marcus K. Rogers. "RPAS Forensic Validation Analysis Towards a Technical Investigation Process: A Case Study of Yuneec Typhoon H." Sensors 19, no. 15 (July 24, 2019): 3246. http://dx.doi.org/10.3390/s19153246.

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The rapid pace of invention in technology and the evolution of network communication has produced a new lifestyle with variety of opportunities and challenges. Remotely Piloted Aerial Systems (RPAS) technology, which includes drones, is one example of a recently invented technology that requires the collection of a solid body of defensible and admissible evidence to help eliminate potential real-world threats posed by their use. With the advent of smartphones, there has been an increase in digital forensic investigation processes developed to assist specialized digital forensic investigators in presenting forensically sound evidence in the courts of law. Therefore, it is necessary to apply digital forensic techniques and procedures to different types of RPASs in order to create a line of defense against new challenges, such as aerial-related incidents, introduced by the use of these technologies. Drone operations by bad actors are rapidly increasing and these actors are constantly developing new approaches. These criminal operations include invasion of privacy, drug smuggling, and terrorist activities. Additionally, drone crashes and incidents raise significant concerns. In this paper, we propose a technical forensic process consisting of ten technical phases for the analysis of RPAS forensic artifacts, which can reduce the complexity of the identification and investigation of drones. Using the proposed technical process, we analyze drone images using the Computer Forensics Reference Datasets (CFReDS) and present results for the Typhoon H aerial vehicle manufactured by Yuneec, Inc. Furthermore, this paper explores the availability and value of digital evidence that would allow a more practical digital investigation to be able to build an evidence-based experience. Therefore, we particularly focus on developing a technical drone investigation process that can be applied to various types of drones.

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Montasari, Reza, Richard Hill, Victoria Carpenter, and Farshad Montaseri. "Digital Forensic Investigation of Social Media, Acquisition and Analysis of Digital Evidence." International Journal of Strategic Engineering 2, no. 1 (January 2019): 52–60. http://dx.doi.org/10.4018/ijose.2019010105.

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Various social networking sites (SNSs), widely referred to as social media, provide services such as email, blogging, instant messaging and photo sharing for social and commercial interactions. SNSs are facilitating new forms of social interaction, dialogue, exchange and collaboration. They allow millions of users and organisations worldwide to exchange ideas, post updates and comments or participate in activities and events, while sharing their wider interests. At the same time, such a phenomenon has led to an upsurge in significant criminal activities by perpetrators who are becoming increasingly sophisticated in their attempts to deploy technology to circumvent detection. Digital forensic Examiners (DFEs) often face serious challenges in relation to data acquisition. Therefore, this article aims to analyse the significance of SNSs in DFIs and challenges that DFEs often encounter when acquiring evidence from SNSs. Furthermore, this article describes the steps of the digital forensic investigation process that must be taken to acquire digital evidence that is both authentic and forensically sound.

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Ghannam, Hussein Abed. "Forensic Analysis of Artifacts of Giant Instant Messaging “WhatsApp” in Android Smartphone." Journal of Applied Information, Communication and Technology 5, no. 2 (October 28, 2018): 73–83. http://dx.doi.org/10.33555/ejaict.v5i2.55.

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WhatsApp is a giant mobile instant message IM application with over 1billion users. The huge usage of IM like WhatsApp through giant smart phone “Android” makes the digital forensic researchers to study deeply. The artefacts left behind in the smartphone play very important role in any electronic crime, or any terror attack. “WhatsApp” as a biggest IM in the globe is considered to be very important resource for information gathering about any digital crime. Recently, end-to-end encryption and many other important features were added and no device forensic analysis or network forensic analysis studies have been performed to the time of writing this paper. This paper explains how can we able to extract the Crypt Key of “WhatsApp” to decrypt the databases and extract precious artefacts resides in the android system without rooting the device. Artefacts that extracted from the last version of WhatsApp have been analysed and correlate to give new valuable evidentiary traces that help in investigating. Many hardware and software tools for mobile and forensics are used to collect as much digital evidence as possible from persistent storage on android device. Some of these tools are commercial like UFED Cellebrite and Andriller, and other are open source tools such as autopsy, adb, WhatCrypt. All of these tools that forensically sound accompanied this research to discover a lot of artefacts resides in android internal storage in WhatsApp application.

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Jin, Park Chan. "Personal Information Analysis Using Digital Forensic on Cloud." Advanced Science Letters 22, no. 9 (September 1, 2016): 2252–56. http://dx.doi.org/10.1166/asl.2016.7837.

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Souvignet, T., and J. Frinken. "Differential Power Analysis as a digital forensic tool." Forensic Science International 230, no. 1-3 (July 2013): 127–36. http://dx.doi.org/10.1016/j.forsciint.2013.03.040.

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Petrov, S. M. "Forensic Analysis of Time Markers of Digital Recordings." Theory and Practice of Forensic Science 16, no. 1 (April 23, 2021): 69–77. http://dx.doi.org/10.30764/1819-2785-2021-1-69-77.

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The article presents the results of summarizing expert practice on the examination of the features of digital video and sound recordings, which make it possible to determine the time of file creation and date of the recorded events. The author introduces the concept of “time marker” and proposes the classification of time markers in the file name, time attributes, and metadata by form and source of origin. The basic principles of time representation by various file systems are stated. The relationships between different time markers for original records and records made in other ways are analyzed. The article provides examples of using time markers to diagnose the method of making a record.Various types of time markers that are part of the recorded signal are considered. It is shown which of the recorded events can act as time markers. The author also analyses the possibility of dating using astronomical events. Differences between absolute and relative dating are considered concerning the study of audio and video files. Conclusions are drawn about the significance of the study of time markers for diagnosing the method of making a signalogram, performing relative or absolute dating of recorded events, or technological processes of making a signalogram.

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Eskidere, Ömer. "Source Digital Voice Recorder Identification by Wavelet Analysis." International Journal on Artificial Intelligence Tools 25, no. 03 (June 2016): 1650016. http://dx.doi.org/10.1142/s0218213016500160.

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Identification of the speech signal origin is an important issue since it may play a vital role for criminal and forensic investigations. Yet, in the media forensics field, source digital voice recorder (DVR) identification has not been given much attention. In this paper we study the effect of subband based features obtained using uniform wavelet packet decomposition and Teager energy operator on the DVR model and brand identification performance. In order to assess the effects of these features on the proposed system, one-class classifiers (OCCs) with two reference multi-class classifiers were carried out. The performance of the DVR identification system is tested on a custom database of twelve portable DVRs of six different brands. The results showed that the proposed system can effectively identify the correct DVR brands/models with a high accuracy. Moreover, it was observed that the combination of the traditional speech features with subband Teager energy cepstral parameters (STEC) and short time frame energy as a feature improved recognition accuracy under both silent and noisy recording conditions.

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Akremi, Aymen, Hassen Sallay, Mohsen Rouached, and Rafik Bouaziz. "Applying Digital Forensics to Service Oriented Architecture." International Journal of Web Services Research 17, no. 1 (January 2020): 17–42. http://dx.doi.org/10.4018/ijwsr.2020010102.

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Digital forensics is an emerging research field involving critical technologies for obtaining evidence in digital crime investigations. Several methodologies, tools, and techniques have been developed to deal with the acquisition, preservation, examination, analysis, and presentation of digital evidence from different sources. However, new emerging infrastructures such as service-oriented architecture has brought new serious challenges for digital forensic research to ensure that evidence will be neutral, comprehensive, and reliable in such complex environment is a challenging research task. To address this issue, the authors propose in this article a generic conceptual model for digital forensics methodologies to enable their application in a service-oriented architecture. Challenges and requirements to construct a forensically sound evidence management framework for these environments are also discussed. Finally, the authors show how digital forensics standards and recommendations can be mapped to service-oriented architecture.

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Haryanto, Eri, and Imam Riadi. "Forensik Internet Of Things pada Device Level berbasis Embedded System." Jurnal Teknologi Informasi dan Ilmu Komputer 6, no. 6 (December 2, 2019): 703. http://dx.doi.org/10.25126/jtiik.2019661828.

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Perangkat Internet of Things (IoT) merupakan perangkat cerdas yang memiliki interkoneksi dengan jaringan internet global. Investigasi kasus yang menyangkut perangkat IoT akan menjadi tantangan tersendiri bagi investigator forensik. Keberagaman jenis perangkat dan teknologi akan memunculkan tantangan baru bagi investigator forensik. Dalam penelitian ini dititikberatkan forensik di level internal device perangkat IoT. Belum banyak bahkan belum penulis temukan penelitian sejenis yang fokus dalam analisis forensik perangkat IoT pada level device. Penelitian yang sudah dilakukan sebelumnya lebih banyak pada level jaringan dan level cloud server perangkat IoT. Pada penelitian ini dibangun environment perangkat IoT berupa prototype smart home sebagai media penelitian dan kajian tentang forensik level device. Pada penelitian ini digunakan analisis model forensik yang meliputi collection, examination, analysis, dan reporting dalam investigasi forensik untuk menemukan bukti digital. Penelitian ini berhasil mengungkap benar-benar ada serangan berupa injeksi malware terhadap perangkat IoT yang memiliki sistem operasi Raspbian, Fedberry dan Ubuntu Mate. Pengungkapan fakta kasus mengalami kesulitan pada perangkat IoT yang memiliki sistem operasi Kali Linux. Ditemukan 1 IP Address komputer penyerang yang diduga kuat menanamkan malware dan mengganggu sistem kerja perangkat IoT.AbstractThe Internet of Things (IoT) is an smart device that has interconnection with global internet networks. Investigating cases involving IoT devices will be a challenge for forensic investigators. The diversity of types of equipment and technology will create new challenges for forensic investigators. In this study focused on forensics at the IoT device's internal device level, there have not been many similar research that focuses on forensic analysis of IoT devices at the device level. Previous research has been done more at the network level and cloud level of IoT device's. In this study an IoT environment was built a smart home prototype as a object for research and studies on forensic level devices. This study, using forensic model analysis which includes collection, examination, analysis, and reporting in finding digital evidence. This study successfully revealed that there was really an attack in the form of malware injection against IoT devices that have Raspbian, Fedberry and Ubuntu Mate operating systems. Disclosure of the fact that the case has difficulties with IoT devices that have the Kali Linux operating system. Found 1 IP Address of an attacker's computer that is allegedly strongly infusing malware and interfering with the work system of IoT devices.

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Li, Xiu Zhi, Bao Ling Qin, Huan Qiu, and Song Min Jia. "Sparse L_p-Norm Based ICP for 3D Registration." Applied Mechanics and Materials 742 (March 2015): 433–36. http://dx.doi.org/10.4028/www.scientific.net/amm.742.433.

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In order to uncover truths to serve justice, case-related data collected from a digital investigation requires substantial resources to analyze, especially in time-critical situations. At present, however, digital forensics has not evolved to meet this ever-increasing demand. Digital forensic triage is a promising solution, as it is designed to maximize the use of resources according to a system of priorities, and hence the efficiency and effectiveness of forensic examinations can be increased. Nevertheless, the lack of concrete methods limits efforts to implement triage. This paper presents a practical approach that is designed to build a prioritizing solution. In this work a newprocess model is derived based on the presented approach, and it is particularly suited to scenarios where forensic examiners do not have enough time and resources to conduct a full examination and analysis. An example is described to demonstrate how this approach can be used to meet the requirements of network forensic investigations.

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Benancio, Lizbardo Orellano, Ricardo Muñoz Canales, Paolo Rodriguez Leon, and Enrique Lee Huamaní. "Integrity and Authenticity of Digital Images by Digital Forensic Analysis of Metadata." International Journal of Emerging Technology and Advanced Engineering 11, no. 9 (September 20, 2021): 38–45. http://dx.doi.org/10.46338/ijetae0921_05.

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Abstract—During various court hearings, the thesis that every authentic digital file has precise metadata of its creation date was questioned.In this way, the problem was raised which indicates, if the metadata of a digital file (Image) whose label records the date of creation by the recording device of a digital image file are accurate and reliable.For this reason, during the forensic analysis carried out in this work, a record of the metadata of five (05) digital image files from known sources is shown and where their characteristics have been detailed, in addition a record of the metadata of the images used that were later manipulated with image editing software with which metadata comparisons were made to show the labels that suffered modifications in their content.Finally, the obtaining of HASH code with the SHA - 256 algorithm is shown, for digital assurance, of the edited and original files whose comparison allows observing the changes in the content at a binary level. Keywords—Crime; Cybercrime; Digital Image; HASH; Metadata

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Keim, Yansi, Yung Han Yoon, and Umit Karabiyik. "Digital Forensics Analysis of Ubuntu Touch on PinePhone." Electronics 10, no. 3 (February 1, 2021): 343. http://dx.doi.org/10.3390/electronics10030343.

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New smartphones made by small companies enter the technology market everyday. These new devices introduce new challenges for mobile forensic investigators as these devices end up becoming pertinent evidence during an investigation. One such device is the PinePhone from Pine Microsystems (Pine64). These new devices are sometimes also shipped with OSes that are developed by open source communities and are otherwise never seen by investigators. Ubuntu Touch is one of these OSes and is currently being developed for deployment on the PinePhone. There is little research behind both the device and OS on what methodology an investigator should follow to reliably and accurately extract data. This results in potentially flawed methodologies being used before any testing can occur and contributes to the backlog of devices that need to be processed. Therefore, in this paper, the first forensic analysis of the PinePhone device with Ubuntu Touch OS is performed using Autopsy, an open source tool, to establish a framework that can be used to examine and analyze devices running the Ubuntu Touch OS. The findings include analysis of artifacts that could impact user privacy and data security, organization structure of file storage, app storage, OS, etc. Moreover, locations within the device that stores call logs, SMS messages, images, and videos are reported. Interesting findings include forensic artifacts, which could be useful to investigators in understanding user activity and attribution. This research will provide a roadmap to the digital forensic investigators to efficiently and effectively conduct their investigations where they have Ubuntu Touch OS and/or PinePhone as the evidence source.

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Jankun-Kelly, T. J., David Wilson, Andrew S. Stamps, Josh Franck, Jeffery Carver, and J. Edward Swan. "Visual Analysis for Textual Relationships in Digital Forensic Evidence." Information Visualization 10, no. 2 (April 2011): 134–44. http://dx.doi.org/10.1057/ivs.2010.15.

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We present a visual analytics framework for exploring the textual relationships in computer forensics. Based on a task analysis study performed with practitioners, our tool addresses the inefficiency of searching for related text documents on a hard drive. Our framework searches both allocated and unallocated sectors for text and performs some pre-analysis processing; this information is then presented via a visualization that displays both the frequency of relevant terms and their location on the disk. We also present a case study that demonstrates our framework's operation, and we report on an informal evaluation conducted with forensics analysts from the Mississippi State Attorney General's Office and National Forensics Training Center.

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Riadi, Imam, Rusydi Umar, and Arizona Firdonsyah. "Forensic Tools Performance Analysis on Android-based Blackberry Messenger using NIST Measurements." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 5 (October 1, 2018): 3991. http://dx.doi.org/10.11591/ijece.v8i5.pp3991-4003.

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Blackberry Messenger is one of the popularly used instant messaging applications on Android with user’s amount that increase significantly each year. The increase off Blackberry Messenger users might lead to application misuse, such as for commiting digital crimes. To conduct investigation involving smartphone devices, the investigators need to use forensic tools. Therefore, a research on current forensic tool’s performance in order to handle digital crime cases involving Android smartphones and Blackberry Messenger in particular need to be done. This research focuses on evaluating and comparing three forensic tools to obtain digital evidence from Blackberry Messenger on Android smartphones using parameter from National Institute of Standard Technology and Blackberry Messenger’s acquired digital evidences. The result shows that from comparative analysis conducted, Andriller gives 25% performance value, Oxygen Forensic Suite gives 100% performance value, and Autopsy 4.1.1 gives 0% performance value. Related to National Institute of Standard Technology parameter criterias, Andriller has performance value of 47.61%. Oxygen Forensic Suite has performance value of 61.90%. Autopsy 4.1.1 has performance value of 9.52%.

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Ferreira, Sara, Mário Antunes, and Manuel E. Correia. "A Dataset of Photos and Videos for Digital Forensics Analysis Using Machine Learning Processing." Data 6, no. 8 (August 5, 2021): 87. http://dx.doi.org/10.3390/data6080087.

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Deepfake and manipulated digital photos and videos are being increasingly used in a myriad of cybercrimes. Ransomware, the dissemination of fake news, and digital kidnapping-related crimes are the most recurrent, in which tampered multimedia content has been the primordial disseminating vehicle. Digital forensic analysis tools are being widely used by criminal investigations to automate the identification of digital evidence in seized electronic equipment. The number of files to be processed and the complexity of the crimes under analysis have highlighted the need to employ efficient digital forensics techniques grounded on state-of-the-art technologies. Machine Learning (ML) researchers have been challenged to apply techniques and methods to improve the automatic detection of manipulated multimedia content. However, the implementation of such methods have not yet been massively incorporated into digital forensic tools, mostly due to the lack of realistic and well-structured datasets of photos and videos. The diversity and richness of the datasets are crucial to benchmark the ML models and to evaluate their appropriateness to be applied in real-world digital forensics applications. An example is the development of third-party modules for the widely used Autopsy digital forensic application. This paper presents a dataset obtained by extracting a set of simple features from genuine and manipulated photos and videos, which are part of state-of-the-art existing datasets. The resulting dataset is balanced, and each entry comprises a label and a vector of numeric values corresponding to the features extracted through a Discrete Fourier Transform (DFT). The dataset is available in a GitHub repository, and the total amount of photos and video frames is 40,588 and 12,400, respectively. The dataset was validated and benchmarked with deep learning Convolutional Neural Networks (CNN) and Support Vector Machines (SVM) methods; however, a plethora of other existing ones can be applied. Generically, the results show a better F1-score for CNN when comparing with SVM, both for photos and videos processing. CNN achieved an F1-score of 0.9968 and 0.8415 for photos and videos, respectively. Regarding SVM, the results obtained with 5-fold cross-validation are 0.9953 and 0.7955, respectively, for photos and videos processing. A set of methods written in Python is available for the researchers, namely to preprocess and extract the features from the original photos and videos files and to build the training and testing sets. Additional methods are also available to convert the original PKL files into CSV and TXT, which gives more flexibility for the ML researchers to use the dataset on existing ML frameworks and tools.

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Hariyadi, Dedy, Hendro Wijayanto, and Indah Daila Sari. "PAZIIM DIGITAL EVIDENCE ANALYSIS APPLICATION ON ANDROID SMARTPHONES WITH A LOGICAL ACQUISITION APPROACH." Cyber Security dan Forensik Digital 2, no. 2 (November 28, 2019): 52–56. http://dx.doi.org/10.14421/csecurity.2019.2.2.1603.

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The use of social media in Indonesia has increased very rapidly in 2018 compared to the previous year. This makes a lot of social media made by the children of the nation appear, one of which is Paziim. Socializing on the internet is very easy to leak personal data. There are three aspects that can be utilized on online social networks (OSN) in the disclosure of private data to the public, namely the strength of the relationship (strong or weak), the type of relationship and the characteristics of one's habits. Mobile forensics is needed to analyze digital evidence on social media applications installed on Android smartphones. Indonesia through the National Standardization Agency (BSN) also issued standards related to digital forensics. Standards which are derived from ISO / IEC regulate Security Techniques - Guidelines for the Identification, Collection, Acquisition and Preservation of Digital Evidence. This standardization is known as SNI ISO / IEC 27037: 2014. From the results of cell phone forensic analysis on the Paziim application, the results found the username, coordinates, device models, and operators used by users in SQLite Web_Data and OneSignal.xml files

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B. Meshram, Bandu. "Digital Forensic Analysis of Hard Disk for Evidence Collection." International Journal of Cyber-Security and Digital Forensics 7, no. 2 (2018): 100–110. http://dx.doi.org/10.17781/p002372.

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Lee, Aeri. "Intelligent Digital Forensic Analysis Method for CYBER CRIME INVESTIGATION." J-Institute 1, no. 2 (December 30, 2016): 8–13. http://dx.doi.org/10.22471/police.2016.1.2.08.

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Journal articles on the topic 'Digital forensic analysis'

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