RPAS Forensic Validation Analysis Towards a Technical Investigation Process: A Case Study of Yuneec Typhoon H

The rapid pace of invention in technology and the evolution of network communication has produced a new lifestyle with variety of opportunities and challenges. Remotely Piloted Aerial Systems (RPAS) technology, which includes drones, is one example of a recently invented technology that requires the collection of a solid body of defensible and admissible evidence to help eliminate potential real-world threats posed by their use. With the advent of smartphones, there has been an increase in digital forensic investigation processes developed to assist specialized digital forensic investigators in presenting forensically sound evidence in the courts of law. Therefore, it is necessary to apply digital forensic techniques and procedures to different types of RPASs in order to create a line of defense against new challenges, such as aerial-related incidents, introduced by the use of these technologies. Drone operations by bad actors are rapidly increasing and these actors are constantly developing new approaches. These criminal operations include invasion of privacy, drug smuggling, and terrorist activities. Additionally, drone crashes and incidents raise significant concerns. In this paper, we propose a technical forensic process consisting of ten technical phases for the analysis of RPAS forensic artifacts, which can reduce the complexity of the identification and investigation of drones. Using the proposed technical process, we analyze drone images using the Computer Forensics Reference Datasets (CFReDS) and present results for the Typhoon H aerial vehicle manufactured by Yuneec, Inc. Furthermore, this paper explores the availability and value of digital evidence that would allow a more practical digital investigation to be able to build an evidence-based experience. Therefore, we particularly focus on developing a technical drone investigation process that can be applied to various types of drones.

[1]  Eric T. Matson,et al.  Drone forensic framework: Sensor and data identification and verification , 2017, 2017 IEEE Sensors Applications Symposium (SAS).

[2]  Graeme Horsman,et al.  Unmanned aerial vehicles: A preliminary analysis of forensic challenges , 2016, Digit. Investig..

[3]  Frank Breitinger,et al.  DROP (DRone Open source Parser) your drone: Forensic analysis of the DJI Phantom III , 2017, Digit. Investig..

[4]  Faouzi Kamoun,et al.  Drone Forensics: Challenges and New Insights , 2018, 2018 9th IFIP International Conference on New Technologies, Mobility and Security (NTMS).

[5]  M. A. Hannan Bin Azhar,et al.  Drone Forensic Analysis Using Open Source Tools , 2018, J. Digit. Forensics Secur. Law.

[6]  Kim-Kwang Raymond Choo,et al.  Unmanned Aerial Vehicle Forensic Investigation Process: Dji Phantom 3 Drone As A Case Study , 2018, ArXiv.

[7]  Umit Karabiyik,et al.  Drone Disrupted Denial of Service Attack (3DOS): Towards an Incident Response and Forensic Analysis of Remotely Piloted Aerial Systems (RPASs) , 2019, 2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC).

[8]  Athanasios V. Vasilakos,et al.  Security of the Internet of Things: perspectives and challenges , 2014, Wireless Networks.

[9]  Xiaolei Dong,et al.  Security and Privacy for Cloud-Based IoT: Challenges , 2017, IEEE Communications Magazine.

[10]  Shusen Yang,et al.  A survey on the ietf protocol suite for the internet of things: standards, challenges, and opportunities , 2013, IEEE Wireless Communications.

[11]  Athanasios V. Vasilakos,et al.  A survey on trust management for Internet of Things , 2014, J. Netw. Comput. Appl..