## 2 Related Work  
This section presents a comprehensive overview of the most relevant studies in the literature. These studies consider the general requirements of digital forensics and focus on cloud computing, which is the dominant service delivery architecture today. The authors of [9] analyzed the legal challenges of digital and cloud forensics, such as _(i)_ \"data territoriality--the loss of location challenge\", _(ii)_ \"the challenge of cloud content ownership\", and _(iii)_ \"the challenge of user authentication and data preservation\", and presented judicial opinions on cloud forensics from the European and USA legal framework. [PERSON] et al. [7] proposed a conceptual digital forensics model for deploying forensic applications over a service-oriented architecture. The authors provided a useful categorization of digital forensics and analyzed a forensic model that includes assets, attributes, threats, metrics, and solutions. Furthermore, they discussed the requirements of digital forensics Web applications within a service-oriented architecture. Several surveys present challenges and features of the digital forensics landscape. The authors of [19] provided an analytical study of digital forensics regarding database, mobile, network, and IoT subdomains, and discussed future directions, including _(i)_ the development of metamodeling languages for the digital forensics domain, _(ii)_ the formulation of data representation and structured queries, _(iii)_ the standardization of domain-specific ontologies, and _(iv)_ the integration and harmonization of different domain frameworks into a unified one. Similarly, [PERSON] et al. [2] presented challenges of the digital forensics domain. On top of that, this survey discussed various forensic frameworks and processing models that include all steps of a digital investigation, from evidence acquisition to reporting and presentation. Finally, it discussed future trends in forensic readiness and standards, immutability, ethics in criminal investigation, and explainability. [PERSON] et al. [1] focused on cloud digital forensics by presenting procedures and tools to ensure the integrity of collected evidence, and discussed the main challenges based on the steps of the forensic procedure, including identification, collection, analysis, and presentation. Finally, regarding competition investigation, the survey of [20] presents a set of data screening tools that can evaluate the behavior of market and companies to detect cartels. The authors presented an in-depth analysis and classification of the existing studies, which include probabilistic, network, Machine Learning (ML), and various other methods. Since digital forensics is a vital part of various types of investigations, different forensic procedures are utilized. The investigators leverage AI-based applications to process large datasets automatically. [PERSON] et al. [10] focused on AI-powered applications for mobile forensics. They evaluated commercial software tools, enhanced with ML functionalities, and discussed the ethical and technical challenges of AI in digital investigations. The authors of [3] described an architecture for covering aspects of data management and processing in the lawful interception ecosystem over 5G infrastructure. They proposed the adoption of several promising technologies, such as quantum ML and authentication, 5G network slicing management, and Radio Access Network (RAN) orchestration. Finally, [PERSON] et al. [21] proposed a cloud-based framework for dealing with large datasets. Based on Hadoop, this framework includes various forensic applications and facilitates investigators in creating customized workflows and defining their requirements in XML configuration files. The framework allows for the selection of the appropriate applications, generates the corresponding map-reduce drivers and sets up the workflow in the cloud infrastructure automatically. Cloud resource orchestration and virtualization are well-studied research problems.