Mapping digital forensic application requirement specification to an international standard

Kebande, Victor R.; Baror, Stacey O.; Parizi, Reza M.; Choo, Kim Kwang Raymond; Venter, Hein S.

doi:10.1016/j.fsir.2020.100137

Cited by 6 publications

(5 citation statements)

References 13 publications

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“…Also, the intention of CFRaaS-FSM is to be able to conceptually show how integrating these events to FSM could provide an easy way of conducting digital forensic processes in the cloud environment from the perspective of a FSM. As a result, the events that have been used in the CFRaaS-FSM representation simply portrays some of the activities that emanates from the CFRaaS model that was initially suggested by Kebande et al, 22,23 Kebande and Venter. 12 On the same note, the FSM's representation has been leveraged to explicitly depict from a generic perspective, how a cloud forensic investigation process could be modeled based on initially created steps/subprocesses.…”

Section: Discussionmentioning

confidence: 99%

“…21 Other pertinent research on cloud forensics has mainly focused on presenting holistic ontology-driven perspectives on cloud forensic aspects where readiness is employed as a service based on the simplicity of concepts, relationships and semantics of the potential evidence that can be used for investigation purposes. 22,23 Notably, a taxonomy of cloud forensic solutions has shown that cloud forensics has a focus on the incidents that emanates from the cloud infrastructures and activities that are concerned in criminal investigations and litigations. Basically, cloud forensics has become increasingly important in the recent past.…”

Section: Foundation Of Cloud Forensic Readinessmentioning

confidence: 99%

“…Figure 1 shows a high-level classification of CFRaaS events and processes, where a high-level CFRaaS consist of four distinct processes illustrated as layers: provider layer, virtualization layer, Digital Forensic Readiness (DFR) layer and Incident Response Procedure (IRP) layer, respectively. 22,23…”

Section: F I G U R E 1 Classification Of Cfraas Events By Mechanisms Of Interactionmentioning

confidence: 99%

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Finite state machine for cloud forensic readiness as a service (CFRaaS) events

Kebande

Choo

2021

Security and Privacy

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The importance of demonstrating the correctness of forensic analysis tools and automated incident management tools reinforces the need for a finite state machine (FSM) engine that can generate automated forensic processes. Hence, in this paper, we present an event-based FSM representation for Cloud Forensic Readiness as a Service (CFRaaS), where we also show how the FSM's predetermined states and transitions could be used to formulate an automated forensic process and generate a hypothesis for litigation purposes. Specifically, this proposition comprises a two-step level CFRaaS-FSM with possible transitions and states. This representation is useful because it can alert digital forensic investigators on how to deduce current and next state of attacks based on transitions and current states.

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Section: Discussionmentioning

confidence: 99%

Section: Foundation Of Cloud Forensic Readinessmentioning

confidence: 99%

Section: F I G U R E 1 Classification Of Cfraas Events By Mechanisms Of Interactionmentioning

confidence: 99%

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Finite state machine for cloud forensic readiness as a service (CFRaaS) events

Kebande

Choo

2021

Security and Privacy

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“…The cost of standardising processes and models can be very high due to the required time, resources, and expertise [35]. Nevertheless, the future operation of digital investigation research is more important than the cost of standardising it now.…”

Section: Lack Of Standardisationmentioning

confidence: 99%

Digital Forensics Challenges in Cyberspace: Overcoming Legitimacy and Privacy Issues Through Modularisation

Moses Ashawa,

Ali Mansour,

Jackie Riley

et al. 2023

Cloud Computing and Data Science

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The significance of the cloud environment is growing in the current digital world. It provides several advantages, such as reduced expenses, the ability to adjust to different needs, adaptability and enhanced cooperation. The field of digital forensic investigations has encountered substantial difficulties in reconciling the requirement for efficient data analysis with the increasing apprehensions regarding privacy in recent times. As investigators analyse digital evidence to unearth crucial information, they must also traverse an intricate network of privacy rules and regulations. Given the increasing prevalence of remote work and the necessity for businesses to be adaptable and quick to react to shifting market circumstances, the cloud infrastructure has become a crucial asset for organisations of various scales. Although the cloud offers benefits such as scalability, flexibility and enhanced collaboration, it presents difficulties in digital forensic investigations regarding data protection, ownership and jurisdictional boundaries. These concerns are becoming increasingly significant as more data is kept in the cloud. In this paper, we present three major challenges that are faced during cloud-based forensics investigation. We analyse the extent to which different data formats increase complexity in forensics investigations in cyberspace. This paper analyses three core challenges facing digital forensics in the cloud environment: legitimacy, complexity and an increase in data volume, looking at the implications these have on data liable for legal issues in court. These challenges contribute to the backlog in digital forensics investigations due to a lack of modularisation of the procedures. To address these concerns, modularisation model is proposed to offer a way to integrate traditional processing functions while ensuring strict adherence to privacy protocols. To overcome these challenges, we propose modularisation as a strategy for improving the future of digital forensic research's operational efficiency, overcoming the identified challenges faced during cloud-based investigations and demonstrating how organisations can mitigate potential risks associated with storing sensitive information in the cloud.

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“…In Forensic-Hydrology, a controlled physical model provides the appropriate instrument to create tests (probabilistic-scenarios) for an experimental analysis of failure or disaster simulation. For example, the rainfall-runoff process that causes severe damage in hydrological basins; at all times, it is desired that these tests could verify the results of mathematical models [52,53].…”

Section: Lab Forensicsmentioning

confidence: 99%

Methodological Guide to Forensic Hydrology

Gutiérrez-López

2022

Water

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In Latin America and the Caribbean (LAC) region, geophysical, meteorological and hydrological disasters are increasing every year. With significantly limited resources, these countries are naturally forced to absorb lessons from these disasters. One of the fundamental activities during this learning task remains the need to standardize the forensic reporting process. Like all academic disciplines, engineering is exceptional in its application to the forensic field. This feature makes it a unique input to the investigation of hydrological and environmental catastrophes. Based on the fundamental concepts of forensic investigation, ten principles for properly conducting forensic hydrology studies are proposed. The ten principles proposed are: (i) Principle of use, (ii) production, (iii) principle of exchange, (iv) recognition, (v) correspondence, (vi) reconstruction, (vii) principle of probability, (viii) uncertainty, (ix) principle of certainty, and (x) conclusion principle. A hypothetical case of urban infrastructure failure is used to explain, in detail, each of the proposed principles. This paper proposes a methodology to be considered as a reference point for a forensic hydrological analysis to be used at the LAC region.

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Mapping digital forensic application requirement specification to an international standard

Cited by 6 publications

References 13 publications

Finite state machine for cloud forensic readiness as a service (CFRaaS) events

Finite state machine for cloud forensic readiness as a service (CFRaaS) events

Digital Forensics Challenges in Cyberspace: Overcoming Legitimacy and Privacy Issues Through Modularisation

Methodological Guide to Forensic Hydrology

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