Case note: Digital forensic challenges through synthetic CSAM in video games

Digital forensics in smart environments is an emerging field that deals with the investigation and analysis of digital evidence in smart devices and environments. As smart environments continue to evolve, digital forensic investigators face new challenges in retrieving, preserving, and analyzing digital evidence. At the same time, recent advancements in digital forensic tools and techniques offer promising solutions to overcome these challenges. In this survey, we examine recent advancements and challenges in digital forensics within smart environments. Specifically, we review the current state-of-the-art techniques and tools for digital forensics in smart environments and discuss their strengths and limitations. We also identify the major challenges that digital forensic investigators face in smart environments and propose potential solutions to overcome these challenges. Our survey provides a comprehensive overview of recent advancements and challenges in digital forensics in the age of smart environments, and aims to inform future research in this area.

Challenges in Digital Forensics-- Analysis Based on Equipment, Technology, Resources and Ethics

Researchers and analysts are rapidly going through with large even terabyte- and petabyte-sized data sets when carrying digital investigation, which is becoming one of the major challenges in digital forensics. With invariably rising network bandwidth, it can be highly difficult to operate and store network traffic. To have a control over this, new algorithmic approach and computational methods are needed; even though Big Data is a challenge for forensic researchers, it effectively helps them in investigating patterns to prevent or detect and resolve crime. This chapter brings up care toward challenges in forensic investigation related to Big Data and possible ways to help a forensic investigator figure out large data sets in order to carry out forensic analysis and investigation. World is intent across big social events which even raises a concern toward criminal activities involved there in and there by bounding across Big Data. There are many practical applications where one can process large amount of data, and this data comes moreover in unstructured form. Right from various events that are considered about big communities, there are various real-life postulates where large quantity of data is produced and processed which is required to be mined (Hambrick et al., J Anxiety Disord 18:825–839, 2004). Big Data analytics has provided a striking growth that has shown up as a result of the accessibility of large sum of data that is fitting across a varied range of application domains all so in the region of science, business, and government. This chapter has also paid attention toward different aspects of commerce with analytics mentioning Big Data in social events.

Skimming is a form of cybercrime that continues to grow with the increasing use of digital banking technology. This method involves stealing customer card data through special devices installed on ATMs or payment terminals, resulting in significant financial losses. This article discusses law enforcement against skimming, focusing on two main aspects: digital forensic challenges and evidence in court. The research method used is a juridical-normative approach with a literature review, which includes analysis of laws and regulations, legal literature, and actual cases related to skimming. Furthermore, a case study approach is used to examine the application of digital evidence in the judicial process. The results show that investigators face difficulties in identifying electronic traces, analyzing evidence, and ensuring the authenticity of digital data that is vulnerable to manipulation. Another challenge lies in providing evidence in court, where judges and law enforcement officials often have limited technical understanding of digital forensics. However, judicial practice shows that digital evidence is admissible if obtained legally and supported by adequate forensic expertise. Thus, law enforcement against skimming requires synergy between regulations, technology, and the competence of law enforcement officials. Collaboration between digital forensic experts and law enforcement is key in addressing skimming as a cybercrime.

New dimensions to computer misdemeanors such as information leakages, masquerading, electronic fraud, deformation of corporate cultures and identities through fallacious electronic publicities are alarming across the globe. Hence, corporate organizations are facing serious challenges in coming up with security frameworks that will adequately safeguard their assets and liabilities on a daily basis. Unfortunately, corporate assets have several inherent vulnerabilities while available forensic computer scientists, forensic accountants, laws and litigation that will restrict illegal activities over the web are weak because of the discrepancies in the regulatory activities of different countries to cite a few. Thus, this paper presents a critical review of emerging challenges in auditing digital logs. The review provides useful guidelines that can be used to improve computer usage across the globe and to ultimately lessen the success rate of computer related frauds in corporate organizations.

Experimental design challenges in digital forensics

A concise summary of the research scope, significance, and key objectives, highlighting the increasing ubiquity of wearable devices and their potential as sources of digital evidence. Emphasize the challenges in privacy, security, and forensic analysis and propose contributions to forensic methodologies.

The Action COST DigForAsp is composed of more than 250 specialists and researchers from 36 countries, which is focused on searching for and consolidating of synergies in order to face the challenges in digital forensics, improve processes and obtain more efficient results, throughout the application of Artificial Intelligence and Automatic Reasoning tools. DigForASP aims to create one of the largest European intergovernmental networks for the coordination of European scientific and technical research in Digital Forensic, under the support of the European Cooperation Program in Science and Technology (COST), funded by the European Commission, which seeks to strengthen scientific and technical research in Europe by financing the establishment of collaborative networks between researchers. In this talk, the description of digital forensic and the specific goals of the Action will be presented. Moreover, we will also pay attention to current challenges and achievements.

Various terms have been used to describe the intersection between computing technology and violations of the law-including computer crime, electronic crime, and cybercrime. While there remains little agreement on terminology, most experts agree that the use of electronic devices to commit crime has increased dramatically and is now commonplace. It is the role of the digital investigator to bring cybercriminals to justice. Cybercrime however differs from traditional crime and presents a variety of unique challenges including the variety of electronic devices available, amount of data produced by these devices, the absence of standard practices and guidelines for analyzing that data, the lack qualified personnel to perform investigations and the lack of resources to provide on-going training. This paper examines these challenges

Insider threat detection and investigation are major challenges in digital forensics. Unlike external attackers, insiders have privileges to access resources in their organizations and violations of normal behavior are difficult to detect.

Identifying the underlying type of a file given only a file fragment is a big challenge in digital forensics. Many methods have been applied to file type identification; however the identification accuracies of most of file types are still very low, especially for files having complex structures because their contents are compound data built from different data types. In this paper, we propose a new approach based on the deflate-encoded data detection, entropy-based clustering, and the use of machine learning techniques to identify deflate-encoded file fragments. Experiments on the popular compound file type showed high identification accuracy for the proposed method.KeywordsFile fragment classificationCompressed file fragment classificationSVMShannon entropy

The advent of cloud computing has brought new challenges to digital forensics. To address these challenges, new approaches in conducting digital forensic are required. In this paper, challenges that are faced by digital forensic investigator when faced with cloud based incident scenes are presented. The presented challenges are obtained from survey articles that explore outstanding and future challenges in digital forensics in general. In this paper we zoom in into cloud forensics as it is the main focus of the paper. Based on the challenges brought to light by the considered survey articles, we present requirements that should be met by digital forensic systems that aim to investigate cloud environments. Existing architectures and implementations of digital forensic systems are evaluated based on these requirements. Through this evaluation, gaps that are left out by the evaluated architectures are brought to light.

Challenges for IoT-based forensic investigations include the increasing amount of objects of forensic interest, relevance of identified and collected devices, blurry network boundaries, and edgeless networks. As we look ahead to a world of expanding ubiquitous computing, the challenge of forensic processes such as data acquisition (logical and physical) and extraction and analysis of data grows in this space. Containing an IoT breach is increasingly challenging - evidence is no longer restricted to a PC or mobile device, but can be found in vehicles, RFID cards, and smart devices. Through the combination of cloud-native forensics with client-side forensics (forensics for companion devices), we can study and develop the connection to support practical digital investigations and tackle emerging challenges in digital forensics. With the IoT bringing investigative complexity, this enhances challenges for the Internet of Anything (IoA) era. IoA brings anything and everything "online" in a connectedness that generates an explosion of connected devices, from fridges, cars and drones, to smart swarms, smart grids and intelligent buildings. Research to identify methods for performing IoT-based digital forensic analysis is essential. The long-term goal is the development of digital forensic standards that can be used as part of overall IoT and IoA security and aid IoT-based investigations.

Computer forensics is a digital forensic division that basically deals with crimes that have been committed across various computing devices such as networks, computers, digital storage media etc. It mainly refers to a set of different methodological procedures and techniques to identify, gather, preserve, extract, interpret, document, and present the evidences from the computing equipment in such a manner that the discovered evidence/equipment is acceptable in the court of law. This chapter inspects the origin of science and scientific methods to shape the core premises for setting up measures to evaluate digital forensic as a science and hence justifying the use of digital forensic tools and their feasibility towards cybercrime. This chapter also describes the working framework of different sectors of digital forensics and their challenges while analyzing cybercrime cases. Described controlled frameworks have the potential to minimize the error and challenges in digital forensics and their various categories.

The fragmentation of the Android system and constant app updates create significant challenges in digital forensics. The urgency of this study is to empirically verify whether upgrading forensic tools, specifically from Cellebrite Physical Analyzer (CPA) v7.62 to v7.73, provides significant decoding value to prevent the loss of critical evidence. This study compares the effectiveness of both CPA versions on File System Extraction from OPPO (ColorOS) and Infinix (XOS) devices. Identical extraction images were processed by both CPA versions, and the results were analyzed quantitatively. The results show that CPA v7.73 is collectively superior, finding more artifacts. The most dramatic improvement occurs on Infinix (XOS) (35.69%), with crucial discoveries such as +7,296 additional Contacts and +368 Call Logs, demonstrating the success of the v7.73 decoder in overcoming the unique XOS database. On OPPO devices, improvements focused on communication with +966 additional WhatsApp Messages. This study concludes that CPA v7.73 is indispensable in forensic practice, as failure of older versions in recovering core artifacts can lead to substantial loss of evidence and affect the validity of investigations.