A Novel Forensic Readiness Framework Applicable to the Drone Forensics Field

Alotaibi, Fahad Mazaed; Al-Dhaqm, Arafat; Al‐Otaibi, Yasser D.

doi:10.1155/2022/8002963

Cited by 16 publications

(11 citation statements)

References 37 publications

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“…Recently, many researchers have introduced their work in the DRFI field. These include, (Alotaibi et al, 2022b), the authors introduced a new framework for drone forensic readiness. They address several issues in the DRFI field, despite the fact that their framework hasn't been put into practice (Al-Dhaqm et al, 2021a;Alotaibi et al, 2022b;Atkinson et al, 2021;Lan and Lee, 2022;Husnjak et al, 2022;Parghi et al, 2022).…”

Section: Methodsmentioning

confidence: 99%

Semantic Forensic Investigation Framework for Drone Field

Ameerbakhsh¹

2023

Journal of Computer Science

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The application of Unmanned Aerial Vehicles (UAVs) is extensive, with uses ranging from smart agriculture to photography, maintaining infrastructure, and disaster recovery. However, incidents involving unmanned aerial vehicles are increasing daily due to their widespread use in smart technologies. Therefore, this study focuses on the ground of drone forensic investigation to capture and investigate incidents involving unmanned aerial vehicles. To find drone incidents and identify the perpetrators, forensic drone investigation is used, such as determining when the drone incident occurred, what type of drone incident it was, and the exact moment the drone incident occurred. Several forensic models and frameworks for drones have been proposed to identify, capture and analyze various cybercrimes committed by drones. However, these works deal with drones from a technical standpoint; thus, a semantic forensic framework for unmanned aerial vehicles is required to facilitate the investigation process among domain investigators. Therefore, the objective of this study is to use the design science method to develop a semantic forensic investigation framework for drones. The designed framework includes three main abstract processes: (1) Preparation, (2) Gathering and preservation, and (3) Analysis and documentation. The qualitative technique was used to validate the designed framework (Comparison against other models). The designed framework is compared with other models to ensure that it is logical, complete, and useful in comparison to another drone forensic investigation domain models. The designed framework enables domain practitioners to easily create solution models based on their requirements. It proposed a modeling process that uses modeling rules to generate solution models.

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Section: Methodsmentioning

confidence: 99%

Semantic Forensic Investigation Framework for Drone Field

Ameerbakhsh¹

2023

Journal of Computer Science

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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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“…The Incident Response: This stage in DRFM is used to respond to drone incidents. A typical set of components in a drone system should identify when the drone is under attack from any devices like a system, laptop, mobile phone, router, radio controller, or other components [42,43]. These all devices or components have digital evidence related to drone investigation.…”

Section: Stage 1: Identification Stagementioning

confidence: 99%

“…Examining the Acquired Data: The data acquired and preserved in the previous stage should be examined to check and verify the authenticity of the data [42]. Examiner should rehash the hashed value of the received data and check the consistency of the data.…”

mentioning

confidence: 99%

Towards Development of a High Abstract Model for Drone Forensic Domain

et al. 2022

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Drone Forensics (DRF) is one of the subdomains of digital forensics, which aims to capture and analyse the drone’s incidents. It is a diverse, unclear, and complex domain due to various drone field standards, operating systems, and infrastructure-based networks. Several DRF models and frameworks have been designed based on different investigation processes and activities and for the specific drones’ scenarios. These models make the domain more complex and unorganized among domain forensic practitioners. Therefore, there is a lack of a generic model for managing, sharing, and reusing the processes and activities of the DRF domain. This paper aims to develop A Drone Forensic Metamodel (DRFM) for the DRF domain using the metamodeling development process. The metamodeling development process is used for constructing and validating a metamodel and ensuring that the metamodel is complete and consistent. The developed DRFM consists of three main stages: (1) identification stage, (2) acquisition and preservation stage, and (3) examination and data analysis stage. It is used to structure and organize DRF domain knowledge, which facilitates managing, organizing, sharing, and reusing DRF domain knowledge among domain forensic practitioners. That aims to identify, recognize, extract and match different DRF processes, concepts, activities, and tasks from other DRF models in a developed DRFM. Thus, allowing domain practitioners to derive/instantiate solution models easily. The consistency and applicability of the developed DRFM were validated using metamodel transformation (vertical transformation). The results indicated that the developed DRFM is consistent and coherent and enables domain forensic practitioners to instantiate new solution models easily by selecting and combining concept elements (attribute and operations) based on their model requirement.

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A Novel Forensic Readiness Framework Applicable to the Drone Forensics Field

Cited by 16 publications

References 37 publications

Semantic Forensic Investigation Framework for Drone Field

Semantic Forensic Investigation Framework for Drone Field

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

Towards Development of a High Abstract Model for Drone Forensic Domain

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