Electromagnetic Watermarking: exploiting IEMI effects for forensic tracking of UAVs

Esteves, José Lopes

doi:10.1109/emceurope.2019.8872027

Cited by 8 publications

(5 citation statements)

References 17 publications

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“…The Federal Aviation Administration (FAA) has two categories of Unmanned Aerial Systems (UAS) that it can use to update the requirements for UAS. Based on previously published research, it was confirmed that more study is needed on incident responses and forensic analysis frameworks specifically designed for use with remotely piloted aerial systems 28 2019 Esteves (2019) invented the "electromagnetic watermarking" technique to take advantage of the effects of IEMI on UAVs used for civilian purposes to better facilitate forensic tracking 29 2019 Mei (2019) For a better understanding of how forensics frameworks are applied when conducting forensic inspections on drones, the researchers polled a large number of DRF investigators and aircraft accident investigators. The gathered information was examined using the Chi square independence test.…”

Section: Methodsmentioning

confidence: 92%

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: 92%

Semantic Forensic Investigation Framework for Drone Field

Ameerbakhsh¹

2023

Journal of Computer Science

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“…e electromagnetic watermarking concept was introduced in [30] as a technique that exploits the IEMI impacts for embedding a watermark into civilian UAVs with the aim of performing forensic tracking.…”

Section: Related Workmentioning

confidence: 99%

A Novel Forensic Readiness Framework Applicable to the Drone Forensics Field

Alotaibi

Al-Dhaqm

Al‐Otaibi

2022

Computational Intelligence and Neuroscience

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The Drone Forensics (DRFs) field is a branch of digital forensics, which involves the identification, capture, preservation, reconstruction, analysis, and documentation of drone incidents. Several models have been proposed in the literature for the DRF field, which generally discusses DRF from a reactive forensic perspective; however, the proactive forensic perspective is missing. Therefore, this paper proposes a novel forensic readiness framework called Drone Forensics Readiness Framework (DRFRF) using the design science method. It consists of two stages: (i) proactive forensic stage and (ii) reactive forensic stage. It considers centralized logging of all events of all the applicants within the drone device in preparation for an examination. It will speed up gathering data when an investigation is needed, permitting the forensic investigators to handle the examination and analysis directly. Additionally, digital forensics analysts can increase the possible use of digital evidence while decreasing the charge of performing forensic readiness. Thus, both the time and cost required to perform forensic readiness could be saved. The completeness, logicalness, and usefulness of DRFRF were compared to those of other models already existing in the DRF domain. The results showed the novelty and efficiency of DRFRF and its applicability to the situations before and after drone incidents.

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“…They also discussed the lack of incident responses for forensic analysis. In [28], an electromagnetic watermarking concept is used as a method for UAVs and forensic tracking. In [29], the UAVs accident investigation was done for DRF, and a forensic framework was examined.…”

Section: Related Workmentioning

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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Electromagnetic Watermarking: exploiting IEMI effects for forensic tracking of UAVs

Cited by 8 publications

References 17 publications

Semantic Forensic Investigation Framework for Drone Field

Semantic Forensic Investigation Framework for Drone Field

A Novel Forensic Readiness Framework Applicable to the Drone Forensics Field

Towards Development of a High Abstract Model for Drone Forensic Domain

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