A Framework for Concurrent Contact-Tracing and Digital Evidence Analysis in Heterogeneous Environments

Baror, Stacey O.; Venter, Hein S.; Kebande, Victor R.

doi:10.1007/978-3-030-66840-2_90

Cited by 2 publications

(2 citation statements)

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“…Various models and frameworks have been proposed in DRF, based on the following four aspects: forensic, nonforensic, forensic framework, and forensic analysis applications [24][25][26]. In [8][9], the ways to ensure the best recovery of evidence related to drone incidents were discussed.…”

Section: Related Workmentioning

confidence: 99%

A Conceptual Digital Forensic Investigation Model Applicable to the Drone Forensics Field

Alotaibi,

Al-Dhaqm,

Al-Otaibi

2023

Eng. Technol. Appl. Sci. Res.

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Although there is a considerable amount of studies in drone forensics that describe numerous practical and technical perspectives, there is a lack of a comprehensive investigation framework. This study used design science research methodology to design a conceptual model for the comprehensive investigation of Unmanned Aerial Vehicles (UAVs) under forensic conditions. This model can identify, capture, preserve, analyze, and document UAV incidents. The proposed model consists of four stages: preparation, data collection, analysis, and documentation. In the preparation stage, data are collected and analyzed about UAV-related resources, including the origin and model of the aircraft, any software or hardware installed onboard, and the legal framework and regulations in place. The data collection stage involves the completion of the collection process, where participants gather parts of the UAV and the data needed, such as the flight controller, flight log, and memory cards. The analysis stage involves analyzing the collected evidence. Lastly, the documentation stage involves documenting relevant evidence, analysis results, and any conclusions derived. This model provides a comprehensive process to forensically investigate UAV incidents and provides an efficient and effective approach to the analysis of UAV evidence, ensuring that evidence was collected and analyzed according to accepted forensic techniques. The proposed model can be applied to any UAV type and legal framework.

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Section: Related Workmentioning

confidence: 99%

A Conceptual Digital Forensic Investigation Model Applicable to the Drone Forensics Field

Alotaibi,

Al-Dhaqm,

Al-Otaibi

2023

Eng. Technol. Appl. Sci. Res.

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“…This study explicitly emphasises the need for collecting only data with relevant attributes that can easily be used to profile adversaries. For example, facial recognition, specific proportions, coordinates and contacts by digital devices as highlighted by Baror et al, [34].…”

Section: Crwd Model: High-level Viewmentioning

confidence: 99%

Conceptual Model for Crowd-Sourcing Digital Forensic Evidence

Baror

Venter

Kebande

2022

Lecture Notes in Networks and Systems

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scourge has made it challenging to combat digital crimes due to the complexity of attributing potential security incidents to perpetrators. Existing literature does not accurately pinpoint relevant models/frameworks that can be leveraged for crowd-sourcing digital forensic evidence. This paper suggests using feature engineering approaches for crowd-sourcing digital evidence to profile potential security incidents, for example, in a COVID-19 scenario. The authors have proposed a conceptual Crowd-sourcing (CRWD) model with three main components: Forensic data collection, feature engineering and application of machine learning approaches, and also assessment with standardized reporting. This contribution is significantly poised to solve future investigative capabilities for forensic practitioners and computer security researchers.

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A Framework for Concurrent Contact-Tracing and Digital Evidence Analysis in Heterogeneous Environments

Cited by 2 publications

References 32 publications

A Conceptual Digital Forensic Investigation Model Applicable to the Drone Forensics Field

A Conceptual Digital Forensic Investigation Model Applicable to the Drone Forensics Field

Conceptual Model for Crowd-Sourcing Digital Forensic Evidence

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