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The main purpose of anti-forensic computer techniques, in the broadest sense, is to hinder the investigation of a computer attack by eliminating traces and preventing the collection of data contained in a computer system. Nowadays, cyber-attacks are becoming more and more frequent and sophisticated, so it is necessary to understand the techniques used by hackers to be able to carry out a correct forensic analysis leading to the identification of the perpetrators. Despite its importance, this is a poorly represented area in the scientific literature. The disparity of the existing works, together with the small number of articles, makes it challenging to find one’s way around the vast world of computer forensics. This article presents a comprehensive review of the existing scientific literature on anti-forensic techniques, mainly DFIR (digital forensics incident response), organizing the studies according to their subject matter and orientation. It also presents key ideas that contribute to the understanding of this field of forensic science and details the shortcomings identified after reviewing the state of the art.

With the rapid development of information technology, fundamental changes have taken place in the way people work. However, computer crime has also become the main type of cases in the Internet era. Therefore, computer forensics technology has become an important research content of computer crime evidence collection. Firstly, this paper analyzes the relationship between computer forensics and data recovery. Then, this paper analyzes the steps of computer forensics. Finally, this paper analyzes the application of anti-forensics technology and computer forensics technology.

Practical Digital Forensics: A Guide for Windows and Linux Users is a comprehensive resource for novice and experienced digital forensics investigators. This guide offers detailed step-by-step instructions, case studies, and real-world examples to help readers conduct investigations on both Windows and Linux operating systems. It covers essential topics such as configuring a forensic lab, live system analysis, file system and registry analysis, network forensics, and anti-forensic techniques. The book is designed to equip professionals with the skills to extract and analyze digital evidence, all while navigating the complexities of modern cybercrime and digital investigations. Key Features:- Forensic principles for both Linux and Windows environments.- Detailed instructions on file system forensics, volatile data acquisition, and network traffic analysis.- Advanced techniques for web browser and registry forensics.- Addresses anti-forensics tactics and reporting strategies.- Includes real-world examples and practical case studies. Readership: Digital forensics professionals, law enforcement, cybersecurity analysts, legal practitioners, IT administrators, students, and corporate investigators.

Due to the advancement of technology, cybercrime has increased considerably, making digital forensics essential for any organisation. One of the most critical challenges is to analyse and classify the information on devices, identifying the relevant and valuable data for a specific purpose. This phase of the forensic process is one of the most complex and time-consuming, and requires expert analysts to avoid overlooking data relevant to the investigation. Although tools exist today that can automate this process, they will depend on how tightly their parameters are tuned to the case study, and many lack support for complex scenarios where language barriers play an important role. Recent advances in machine learning allow the creation of new architectures to significantly increase the performance of information analysis and perform the intelligent search process automatically, reducing analysis time and identifying relationships between files based on initial parameters. In this paper, we present a bibliographic review of artificial intelligence algorithms that allow an exhaustive analysis of multimedia information contained in removable devices in a forensic process, using natural language processing and natural language understanding techniques for the automatic classification of documents in seized devices. Finally, some of the open challenges technology developers face when generating tools that use artificial intelligence techniques to analyse the information contained in documents on seized devices are reviewed.

Rapid technological advancement can have a substantial impact on the process of digital forensic investigation and presents numerous challenges to the investigator. With these challenges, it is imperative to have a standard framework for the digital forensic investigation to be implemented within most incidents. This induces a great stride to formulate a nonspecific framework that may be applied to most digital investigation procedures. The Next Generation Digital Forensic Investigation Model (NGDFIM) formalizes the framework to facilitates the practitioners in the investigation process. This framework could potentially generate more evidence during the incidence response through on-site triage as compared to conventional investigations process. Moreover, the framework diminishes the analysis time and provides the suspect with privacy protection by incorporating custom content imaging.

In a unique and systematic way, this book discusses the security and privacy aspects of the cloud, and the relevant cloud forensics.Cloud computing is an emerging yet revolutionary technology that has been changing the way people live and work.

Blockchain technology has gained significant attention in recent years for its potential to revolutionize various sectors, including finance, supply chain management, and digital forensics. While blockchain’s decentralization enhances security, it complicates the identification and tracking of illegal activities, making it challenging to link blockchain addresses to real-world identities. Also, although immutability protects against tampering, it introduces challenges for forensic investigations as it prevents the modification or deletion of evidence, even if it is fraudulent. Hence, this paper provides a systematic literature review and examination of state-of-the-art studies in blockchain forensics to offer a comprehensive understanding of the topic. This paper provides a comprehensive investigation of the fundamental principles of blockchain forensics, exploring various techniques and applications for conducting digital forensic investigations in blockchain. Based on the selected search strategy, 46 articles (out of 672) were chosen for closer examination. The contributions of these articles were discussed and summarized, highlighting their strengths and limitations. This paper examines the selected papers to identify diverse digital forensic frameworks and methodologies used in blockchain forensics, as well as how blockchain-based forensic solutions have enhanced forensic investigations. In addition, this paper discusses the common applications of blockchain-based forensic frameworks and examines the associated legal and regulatory challenges encountered in conducting a forensic investigation within blockchain systems. Open issues and future research directions of blockchain forensics were also discussed. This paper provides significant value for researchers, digital forensic practitioners, and investigators by providing a comprehensive and up-to-date review of existing research and identifying key challenges and opportunities related to blockchain forensics.

Computer forensic techniques are important for the prevention, detection, and investigation of electronic crime. Computer forensic investigators need computer forensic tools to produce reliable results that meet legal requirements and are acceptable in the courts. Most of these tools are closed-source, making the software a black-box for testing purposes. This paper illustrates a different black box testing method for experimenting computer forensic tools based on functional scenarios.

Cloud computing technology is rapidly becoming ubiquitous and indispensable. However, its widespread adoption also exposes organizations and individuals to a broad spectrum of potential threats. Despite the multiple advantages the cloud offers, organizations remain cautious about migrating their data and applications to the cloud due to fears of data breaches and security compromises. In light of these concerns, this study has conducted an in-depth examination of a variety of articles to enhance the comprehension of the challenges related to safeguarding and fortifying data within the cloud environment. Furthermore, the research has scrutinized several well-documented data breaches, analyzing the financial consequences they inflicted. Additionally, it scrutinizes the distinctions between conventional digital forensics and the forensic procedures specific to cloud computing. As a result of this investigation, the study has concluded by proposing potential opportunities for further research in this critical domain. By doing so, it contributes to our collective understanding of the complex panorama of cloud data protection and security, while acknowledging the evolving nature of technology and the need for ongoing exploration and innovation in this field. This study also helps in understanding the compound annual growth rate (CAGR) of cloud digital forensics, which is found to be quite high at ≈16.53% from 2023 to 2031. Moreover, its market is expected to reach ≈USD 36.9 billion by the year 2031; presently, it is ≈USD 11.21 billion, which shows that there are great opportunities for investment in this area. This study also strategically addresses emerging challenges in cloud digital forensics, providing a comprehensive approach to navigating and overcoming the complexities associated with the evolving landscape of cloud computing.

Smart technologies, such as the Internet of Things (IoT), cloud computing, and artificial intelligence (AI), are being adopted in cities and transforming them into smart cities. In smart cities, various network technologies, such as the Internet and IoT, are combined to exchange real-time information, making the everyday lives of their residents more convenient. However, there is a lack of systematic research on cybersecurity and cyber forensics in smart cities. This paper presents a comprehensive review and survey of cybersecurity and cyber forensics for smart cities. We analysed 154 papers that were published from 2015 to 2022 and proposed a new framework based on a decade of related research papers. We identified four major areas and eleven sub-areas for smart cities. We found that smart homes and the IoT were the most active research areas within the cybersecurity field. Additionally, we found that research on cyber forensics for smart cities was relatively limited compared to that on cybersecurity. Since 2020, there have been many studies on the IoT (which is a technological component of smart cities) that have utilized machine learning and deep learning. Due to the transmission of large-scale data through IoT devices in smart cities, ML and DL are expected to continue playing critical roles in smart city research.