Drones' cyber-physical systems (CPS), which integrate computer, networking, and physical systems, can also be vulnerable to various security threats. As CPS often consists of a network of interdependent devices and systems, any one part may be the target of a cyberattack. By inserting malware into the software, exploiting vulnerabilities, or initiating cyber attacks, including denial-of-service attacks, cyber attackers can access the drone's control system unauthorised. Drones' onboard computers produce an immense amount of data, some of which may be very confidential. Data breaches and privacy violations can occur if this information is not encrypted or maintained securely.
Top1. Introduction
The scientific community has become quite interested in UAVs (unmanned aerial vehicles) due to their extensive use in military and civilian applications. The special qualities of UAVs have made several complicated applications feasible and affordable. It has recently become possible to combine communication and computational capabilities with the physical world thanks to the development of cyber-physical systems (CPS). Since the UAV system has all the required capabilities, including sensing, communication, control, and computation, to keep track of and manage physical processes, it can also be considered a CPS. The combination of physical damage and cyberattacks creates special difficulties for CPS safety. Although extensive research has been done to defend against physical or cyber attacks, the current strategies still need to defend against CCPA successfully.
Furthermore, there still needs to be a shared scientific understanding of robust CPS and supporting technologies against CCPA, making full verification of CPS against CCPA very difficult (Agatz, N., 2018, Akkamış, 2020). We suggest a theoretically supported and practically implementable framework for CPS security and fault tolerance with a lower level of complexity in terms of its software architecture. We focus on UAV platforms to highlight the difficulties and verify the theoretical frameworks in this integrated CPS framework. Sensors sample the autonomous UAVs' output signals during flight experiments. The flight control system makes control decisions based on sensed data. The aircraft's condition, including the angle of attack, must remain within a suitable stability envelope to ensure safety (Akram, R. N., 2017; Anbaroğlu, B., 2017). The generic fault and attack models under consideration include sensor faults caused by sensor faults, interference, or spoofing, complex controller software faults caused by software bugs or cyberattacks, and mechanical faults caused by physical faults or attacks and the resulting stability envelope faults. Figure 1 Overview of Drone Sensors.
Figure 1. Overview of drone sensors adopted key-industry-development
According to the research, the projected size of the global drone sensors market is anticipated to reach USD 2,342.1 million by the year 2028, with a compound annual growth rate (CAGR) of 25.08%. According to the report titled “Drone Sensors Market, 2020-2028” by Fortune Business InsightsTM, the market is expected to be significantly influenced by the growing utilization of drones during the COVID-19 pandemic.