# ECU-IoFT: A Dataset for Analysing Cyber-Attacks on Internet of Flying Things  
[PERSON]  
School of Science, Edith Cowan University, Perth 6027, Australia; [EMAIL_ADDRESS] (D.C.); [EMAIL_ADDRESS] (B.S. ); [EMAIL_ADDRESS] (A.A.) Correspondence: [EMAIL_ADDRESS]  
David Cox  
School of Science, Edith Cowan University, Perth 6027, Australia; [EMAIL_ADDRESS] (D.C.); [EMAIL_ADDRESS] (B.S. ); [EMAIL_ADDRESS] (A.A.) Correspondence: [EMAIL_ADDRESS] (A.A.) These authors contributed equally to this work. [PERSON]  
The Internet of Things (IoT) has shifted from an up-and-coming technology concept to a heavily utilised technology. IoT embeds everyday devices with small, low-powered computers and wireless networks to add \"Smart\" functionality to a regular item, allowing for inter-connectivity between devices, the cloud, and enabling automation [1]. A domain where IoT has significantly grown is within the Internet of Flying Things (IoFT). The adoption of IoT devices often referred to as drones or the more accurate terminology unmanned air vehicles (UAV), has significantly increased within government, enterprise, and personal use over the past years [2]. In 2018, The Australian Government Civil Aviation Safety Authority (CASA) estimated that over 150,000 UAVs were in operation within Australia [3]. This increase in UAV use is due to UAV's increased capabilities and endurance, the ease of flight and the minimal training required for flying, and the reduced operational cost compared to traditional aviation mediums such as helicopters and small planes [4]. Government agencies and private sector businesses are utilising UAVs for cinematography, crisis management, environmental and maritime research, traffic monitoring and for courier deliveries [2, 5]. With this increase in adaptation of UAV's, educators are embedding UAV's (drones) within their STEM (science, technology, engineering and mathematics) programs [6]. The lack of cybersecurity awareness surrounding IoT within the educational context (staff, students and parents) can contribute to vulnerabilities to IoT Devices. Notable attack vectors targeting UAV's (but not limited to) include denial-of-service (control signals and GPS), Man-in-the-middle attacks and exploited Application Programmable Interface(API) [7]. The consequences of such attacks not only contribute to the loss of assets or cause reputational damage but, more importantly, could place children and teens in physical harm or breach their privacy [2]. Appropriate security cannot be implemented while attacks against IoFT platforms remain undocumented. UAVs will present as a target to cyber-attackers [2]; hence, it is essential that a deeper understanding of cyber-vulnerabilities relating to IoFT is pursued. Researchers require data into cyber-attacks launched against IoFT devices in order to develop behaviour signatures that can be used to identify, mitigate and develop countermeasures [8]. Table 1 shows that there is a significant lack of real world data in the context of IoFT and Drones. While there are emulated datasets available for intrusion detection systems (IDS), these are not going to be effective in real-world scenarios, and hence in this paper, we have tried to develop a dataset portraying realistic scenarios. Although many risks to commercial UAVs have been documented, many of these are attacks are documented in a theoretical context [7]. This paper aims to investigate the risks associated with the usage of drones in education domain. In addition, to understand the cyberattacks better in IoFT, a dataset has been developed, and allowing further research to establish cyber defences for UAVs. The dataset is named ECU-IoFT as the contributors are all from Edith Cowan University and it has been a general practice by the research community to name the datasets based on the institution, i.e., DARPA, UNSW, etc. The key objectives and contributions of the paper are as follows:  
* Cyber vulnerability analysis of an off-the-shelf low-cost drone used in educational purpose. * Risk associated of using vulnerable drones.