Technical Challenges And Directions For Digital Forensics

I. Introduction

Digital forensics (DF) is a critical aspect of modern law enforcement and criminal investigations, as more and more criminal activity involves the use of digital devices and networks. Digital evidence can take many different forms. It may materialize on digital electronic devices or computers that are just passive repositories of evidence documenting the action, or it may consist of information or meta-information located on computers or other devices that were used to support the activity or that were targeted by the activity. Digital forensics practitioners must be able to collect, preserve, and analyze electronic data in a manner that is admissible as evidence in a court of law. DF has gone a long way in a relatively short period of time, roughly two decades. Many criminal and civil investigations now include digital forensics.

While legislation recognizing the unique nature of computer crime was introduced in some parts of the world as early as the late 1970s, and while personal computers were widely adopted by residential users and industry in the 1980s, it was not until the 1990s that the influence of digital forensics was widely recognized. This corresponded with the initial deployment of purpose-built computer forensic tools in the early 1990s, as well as the widespread use - and misuse - of the Internet later in the 1990s. Since then, we've witnessed the expansion of mobile phones, and embedded computers in both residential and industrial settings. As a result, there is now a large volume of digital content that may represent electronic evidence of illegal or suspicious behavior under the applicable circumstances.

The format of this document is as follows: in Section II we portray the Challenges faced by Digital Forensic, The Future research is discussed in Section III. Finally, in Section IV, we bring this paper to a conclusion.

II. Challenges of Digital Forensic

The current status of DF has significant hurdles, both ethically and technologically. As the field of DF continues to evolve, its development is severely challenged by the growing popularity of digital devices and the heterogeneous hardware and software platforms being utilized [1]. For instance, the increasing variety of file formats and OSs hampers the development of standardized DF tools and processes [8].

Diversity of Digital Devices:

The diversity of digital devices presents a major challenge for digital forensics. Digital devices can range from traditional computers and mobile phones to wearable devices, IoT devices, and gaming consoles, among others. This diversity of devices poses several challenges for digital forensics, as each device may have unique characteristics and technical requirements that must be considered when collecting and analyzing evidence. One of the main challenges posed by the diversity of digital devices is the need to understand and account for the unique technical characteristics of each device. For example, different devices may use different operating systems, file systems, and data storage formats, which can impact the process of collecting and analyzing evidence. Additionally, the diversity of devices can make it difficult to develop a standard set of tools and techniques for collecting and analyzing evidence, as each device may require different methods and approaches.

Another challenge posed by the diversity of digital devices is the need to stay up-to-date on the latest technologies and trends. As new devices are developed and released, digital forensics practitioners must have the knowledge and skills to effectively collect and analyze evidence from these devices. This requires ongoing education and training, as well as the development of new tools and techniques to support the analysis of new and emerging digital devices.

The diversity of digital devices can also impact the accuracy and reliability of digital forensics results. For example, the way in which data is stored and processed on different devices can impact the authenticity and integrity of the evidence collected. In some cases, the use of encryption or other security measures may also make it difficult to access and analyze data stored on certain devices.

Data Volume:

The increasing volume of data generated and stored in digital devices presents a major challenge for digital forensics. With the growth of cloud computing, social media, and the Internet of Things (IoT), the amount of electronic data generated and stored has grown dramatically in recent years. This data volume has significant implications for the process of digital forensics, which involves collecting, preserving, and analyzing electronic evidence.

One of the key challenges posed by data volume is the difficulty of collecting and preserving all relevant evidence. With the sheer volume of data generated and stored, it is not always possible to capture all relevant evidence, especially when dealing with live systems and large cloud environments. This can result in a loss of important evidence that may be crucial to an investigation.

Another challenge posed by data volume is the difficulty of processing and analyzing all relevant data. The analysis of large data sets can be time-consuming and resource-intensive, and the sheer volume of data can make it difficult to identify relevant evidence and extract meaningful information. This can result in longer investigation times, increased costs, and a reduced ability to make accurate and timely decisions.

Anti-Forensics:

The techniques that criminals use, regardless of device type, vary but they share the same end purpose which is to hinder or slow down any digital forensic process [2]. This is in accordance with the definition proposed by Harris (2006) where he writes that anti-forensics are "methods used to prevent (or act against) the application of science […] enforced by police agencies”. This means that any method or technique used by an individual or organisation that in some way hinders any stage of a digital forensic process (DFP) is to be considered as antiforensics [5]. But Horsman and Errickson (2019) also add the insight that not all individuals or organisations that utilise methods that are to be considered as anti-forensics are necessary criminals. [3]This is true when it comes to protecting the privacy of individuals and organisations (Horsman and Errickson, 2019). By adopting the definition of anti-forensic techniques (AFT) suggested by Harris [6] and excluding the use-cases identified by [3] what is left are individuals and organisations that actively hinder investigations by law enforcement agencies. Recent researches show an increased adoption of CAF techniques into other typical attacks. The primary purposes of integrating CAF into other attacks are undetectability and deletion of evidence. Two major areas for this threatening integration are Malware and Botnets [10][11]. Malware and Botnets when armed with these techniques will make the investigative efforts labour and time intensive which can lead to overlooking critical evidence, if not abandoning the entire investigation.

Data Encryption:

Encryption is the process of encrypting your data using a set of keys. This is a perfectly legal practice that is employed by normal users, but invaders and illegal individuals also use it to hide their data and information from forensic experts. Because there are several free programmes accessible to encrypt data, this is a relatively typical challenge that forensic examiners encounter. It is sometimes simple to decrypt data encrypted by common tools, but decryption of data is very important and complex for a forensic examiner because there are a variety of encryption algorithms present, some of which are very complex, so it takes more time for a forensic examiner to identify and decode the algorithm.

Microsoft has developed a programme that greatly assists forensic examiners, although it has significant limits. The tool's name is MICROSOFT COMPUTER ONLINE FORENSICS EVIDENCE EXTRACTOR (MCOFEE). MCOFEE has a variety of alternatives, such as a password decryptor, internet history recovery, and data extraction. This tool, and numerous others like it, assist forensics examiners in minimizing this difficulty to some level, but it is not entirely sufficient.

III. Concept of Future Research

As previously stated, there are considerable obstacles in the field of digital forensics. These problems, however, create opportunity for new research in digital forensics. These issues are utilised in the next part to drive future paradigms of additional study, recommending and prioritising important critical improvements.

A. New Tools, Techniques and Standards

One of the major issues that must be addressed in future study is the creation of new tools and ways to assess the volume of data and send prospective digital clues to the DFPs for further investigation. However, because to the lack of standards and computational requirements, designing and implementing such tools and approaches is a difficult undertaking. Similarly, DFPs can use cloud computing, for example, to simplify the most difficult procedures of a DFI, such as log analysis, data reduction, indexing, and carving. Furthermore, while processing information or utilizing outsourced storage and computation, analyzing sophisticated cyber-attacks needs a united and coordinated effort. For instance, the development of standard formats and abstractions require a collaborative approach to address the challenges of identification and extraction of digital artifacts common and uncommon locations in various types of digital devices [9]and their subsequent categorization and analysis. Furthermore, it is critical to create standards for case data, data abstractions, and "composable models" for DF processing in order to further DF research. Disk images, packet capture files, files, file signatures, and Extracted Named Entities are the five most commonly used abstractions. Due to the lack of common data abstractions and data formats, researchers are frequently forced to construct more pieces of a system before producing early findings. As a result, their progress is hampered. Therefore, new abstractions are needed to be developed in order to represent and compute with large amount of data [4].

B. Digital Forensic as a Service (DFaaS)

Digital Forensics as a Service (DFaaS) is a modernized version of the traditional forensics’ method. The adoption of DFaaS can help to minimize the backlog of DF cases. DFaaS solutions can solve storage, automation, and investigators' enquiries in instances for which they are liable. Furthermore, it supports effective resource management, enabling DFPs detectives to directly access data, and encourages simpler DFP collaboration. Although DFaaS already delivers several benefits, there are numerous improvements that may be made to the present paradigm to quicken the current process. Such enhancements can, for example, be made to DFaaS functionality, indexing capabilities, and the detection of incriminating material during the Collection Phase of a DFIP. However, it should be mentioned that DFaaS has certain downsides, one of which is latency in relation to the online platform. Furthermore, DFaaS relies on the upload bandwidth available during the physical storage of data acquired through the Collection Phase in a DFIP [7].

C. Distributed, HPC and Parallel Processing

Existing DF tools have insufficient processing speed for the average situation. This is because consumers have not been able to articulate explicit performance needs, and developers have not prioritised speed in terms of dependability and accuracy. Therefore, new methods are needed to be developed to enable data collection in such a way that facilities file-centric processing without disrupting optimal data throughput from the raw device [7][8]. Furthermore, the advantages of High-Performance Computing (HPC) should be addressed in order to reduce computational effort and user time. HPC approaches that take use of parallelism have not been thoroughly examined by DF researchers. HPC methods and technology might be employed for a variety of reasons, including expediting each phase of a digital forensic investigation process beyond the collection stage, such as storage, examination, reconstruction, and presentation and reporting, among others.

D. Encryption

One approach for dealing with encryption difficulties is to use RAM Forensic, which allows Digital Forensics Professionals (DFPs) to obtain the present state of a digital device in a way that disc inspection alone would not likely provide. This approach entails photographing the RAM with a programme like Belkasoft Live RAM Capturer and then extracting a binary decryption key from that RAM image. However, developing RAM Forensic tools is more difficult than creating disks tools. Data recorded on drives is permanent and will be read back in the future. However, data written to RAM can only be accessed by the application that is currently running. The author in [4] argues that as a result there is less desire “for programmers to document data structures rom one version of a program to another”. As a result, such difficulties might make tool creators' jobs more difficult. Furthermore, several encryption techniques are designed to withstand brute-force attacks. There are now various vulnerabilities available for DFPs to use in order to get around this functionality. DFPs, for example, may decode BitLocker volumes by finding the right Microsoft Account password. This may be accomplished by directly retrieving the corresponding escrow key from Microsoft Account. There are different tools and methods for obtaining the password, the explanation of which is outside the scope of this work. Another technique of exploitation is to use a program like Belkasoft Live RAM Capturer to picture the RAM and then extract a binary decryption key from that RAM image.

Conclusion

The field of DF is facing various challenges that are often difficult to overcome. As the new technologies are constantly being developed, LEAs are presented with numerous challenges that can have considerable socioeconomic impact on both global enterprises and individuals[8][1]. Evidence is no longer confined to a single host, but is instead disseminated over several or virtual places. Furthermore, the fast development of information and communication technologies (ICTs) generates a large amount of computable data, which creates considerable problems and security risks.

Furthermore, the manner in which data is disseminated, collected, and processed provide problems to digital forensics investigations due to the heterogeneous nature of IoT devices. Thus, in order to handle the various issues that DF faces while also capitalising on the potential it provides, the research community will need to rethink DF by, for example, revisiting existing principles and redesigning recognised workflows.

Digital forensics is a critical aspect of modern law enforcement and criminal investigations, but it is also a challenging field that presents a number of technical difficulties. This paper has provided an overview of some of the most significant technical challenges facing digital forensics practitioners, including the diversity of digital devices, the volume of data to be analyzed, the complexities of data encryption, the ease of data alteration, and the difficulties of data fragmentation. The field of digital forensics will continue to evolve as new technologies and practices emerge, and it will be important for practitioners to stay informed.

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