Digital forensic readiness in operational cloud leveraging <scp>ISO</scp>/<scp>IEC</scp> 27043 guidelines on security monitoring

Makura, Sheunesu M.; Venter, Hein S.; Kebande, Victor R.; Karie, Nickson M.; Ikuesan, Richard Adeyemi; Alawadi, Sadi

doi:10.1002/spy2.149

Cited by 11 publications

(6 citation statements)

References 24 publications

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“…Various studies have been reported that investigate and recognize cybercrime [22,[31][32][33][34][35][36][37][38][39][40], data cracks [23,[41][42][43][44][45][46][47][48][49][50], and other digital risks [24,25,[41][42][43][44][45][46][47][48][49][50][51][52][53][54][55][56][57][58].…”

Section: A Related Workmentioning

confidence: 99%

A Cybersecurity Awareness Model for the Protection of Saudi Students from Social Media Attacks

Alotibi

2024

Eng. Technol. Appl. Sci. Res.

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Social engineering addresses a broad category of techniques aiming to persuade someone to reveal data or perform actions for criminal purposes, such as disclosing personal information about a particular target. Cybersecurity awareness is required to raise people’s understanding of how these social engineering techniques are being used and so their capacity to exploit them. To accomplish this objective, primary focus is given to educating and training individuals on how to recognize such incidents and respond to them effectively. To protect people against social engineering threats, various cybersecurity models and approaches have been proposed. There are, however, a few differences between these models, since they are developed for specific purposes. Thus, the main objective of this study is to develop a cybersecurity awareness model specifically designed for Saudi students to protect them from social engineering attacks. The design science methodology was utilized in this study. The proposed model consists of four main stages: education and training, developing policies and guidelines, improving Saudi schools’ security, as well as monitoring and evaluation. The model introduced can ensure the safety and privacy of students, teachers, and staff across different social platforms.

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Section: A Related Workmentioning

confidence: 99%

A Cybersecurity Awareness Model for the Protection of Saudi Students from Social Media Attacks

Alotibi

2024

Eng. Technol. Appl. Sci. Res.

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“…On the other hand, several models and frameworks have been proposed in the literature for drone and digital forensics to solve the challenges and issues of drone forensics [73][74][75][76][77][78][79][80][81][82].…”

Section: Machine Learning Techniques Used In the Drone Forensics Fieldmentioning

confidence: 99%

A Comprehensive Collection and Analysis Model for the Drone Forensics Field

Alotaibi

Al-Dhaqm

Al‐Otaibi

et al. 2022

Sensors

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Unmanned aerial vehicles (UAVs) are adaptable and rapid mobile boards that can be applied to several purposes, especially in smart cities. These involve traffic observation, environmental monitoring, and public safety. The need to realize effective drone forensic processes has mainly been reinforced by drone-based evidence. Drone-based evidence collection and preservation entails accumulating and collecting digital evidence from the drone of the victim for subsequent analysis and presentation. Digital evidence must, however, be collected and analyzed in a forensically sound manner using the appropriate collection and analysis methodologies and tools to preserve the integrity of the evidence. For this purpose, various collection and analysis models have been proposed for drone forensics based on the existing literature; several models are inclined towards specific scenarios and drone systems. As a result, the literature lacks a suitable and standardized drone-based collection and analysis model devoid of commonalities, which can solve future problems that may arise in the drone forensics field. Therefore, this paper has three contributions: (a) studies the machine learning existing in the literature in the context of handling drone data to discover criminal actions, (b) highlights the existing forensic models proposed for drone forensics, and (c) proposes a novel comprehensive collection and analysis forensic model (CCAFM) applicable to the drone forensics field using the design science research approach. The proposed CCAFM consists of three main processes: (1) acquisition and preservation, (2) reconstruction and analysis, and (3) post-investigation process. CCAFM contextually leverages the initially proposed models herein incorporated in this study. CCAFM allows digital forensic investigators to collect, protect, rebuild, and examine volatile and nonvolatile items from the suspected drone based on scientific forensic techniques. Therefore, it enables sharing of knowledge on drone forensic investigation among practitioners working in the forensics domain.

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“…By definition, DFR has the capability of the system to efficiently gather the available relevant DE to be used in a court of law [43,47], hence minimizing investigation costs [48,49]. And DFR is the integrated management model to identify the cause of the incident and to have digital forensic evidence ready when needed for investigation [9,50].…”

Section: B Digital Forensic Readinessmentioning

confidence: 99%

“…The investigative processes class consists of in a forensic procedure. The concurrent processes class is the set of processes that run throughout all the 4 process classes in the digital investigation process [49,73].…”

Section: ) Digital Investigation Process Classesmentioning

confidence: 99%

“…This section will briefly explain how it can be deployed by the financial company. The forensic readiness manager should conduct the forensic investigation to uncover what happened or the root cause of the problem when the electronic financial incident [49], such as data corruption, leakage, alteration, and other attacks, occurs. Figure 9 shows the sequential diagram for K-FFRaaS model.…”

Section: Digital Forensics Investigationmentioning

confidence: 99%

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K-FFRaaS: A Generic Model for Financial Forensic Readiness as a Service in Korea

Lee

Kim

2021

IEEE Access

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While Korean financial companies are currently providing electronic financial services by establishing the high-level information technology and security system in accordance with the Electronic Financial Supervision Regulations (EFSR), they are rarely equipped with digital forensic readiness (DFR) to maximize the capability to collect critical digital evidence (DE). So, there is a limit to identifying the root cause of financial incidents and securing admissible DE. In this paper, there, the authors present Financial Forensic Readiness as a Service in Korea (K-FFRaaS), as DFR of financial companies to secure the admissible DE. Based on ISO/IEC 27043:2015 international standard, K-FFRaaS consists of 3 processes groups, namely: Planning processes group, Implementation processes group, and Assessment processes group. Planning processes group is the processes group to prepare the organization to be forensically ready before potential incidents happen. Implementation processes group is the stage to carry out the processes defined in the planning group. Assessment processes group consists of activities that evaluate whether the result of the implementation process group is consistent with the objective of K-FFRaaS. The contribution of this research is to present that the financial company can adopt the systematic management procedure for mitigating the causes of incidents, store admissible DE, and present scientific evidence to a court of law through K-FFRaaS.

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Digital forensic readiness in operational cloud leveraging ISO/IEC 27043 guidelines on security monitoring

Cited by 11 publications

References 24 publications

A Cybersecurity Awareness Model for the Protection of Saudi Students from Social Media Attacks

A Cybersecurity Awareness Model for the Protection of Saudi Students from Social Media Attacks

A Comprehensive Collection and Analysis Model for the Drone Forensics Field

K-FFRaaS: A Generic Model for Financial Forensic Readiness as a Service in Korea

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