# An Efficient Framework for Secure Communication in Internet of Drone Networks Using Deep Computing
## 1 Introduction  
The Internet of Drones (IoD) is an emerging paradigm for unmanned aerial vehicle (UAV) networking that allows controlled coordination and communication of numerous drones under a unified framework [1]. The IoD is an evolving technology that encompasses the conventional Internet of Things (IoT) frameworks and additionally includes the unique mobility, communication, and computing limitations of drone systems [2]. The current market survey estimates the global market for drones to be USD 63.6 billion as of 2025, growing at a compound annual rate of more than 25% [3], underscoring, again, the need to develop secure and efficient IoD infrastructures. Drones have become unavoidable across various application fields such as precision agriculture [4], disaster relief [5], military reconnaissance [6], package delivery [7], border protection [8], and city surveillance [9]. Drones have become vital tools in many industries, with real-world deployment providing compelling proof of their worth [10]. In the field of precision agriculture, for example, monitoring using UAVs has enhanced crop yields by up to 15% and decreased pesticide applications by 30% [11]. In disaster relief efforts, drones cut search and rescue times by more than 40% during the 2015 Nepalese earthquake response [12]. The market for commercial drone delivery alone is projected to exceed USD 5.6 billion by 2026, with morethan 1.3 million deliveries already made worldwide by firms such as Zipline and Amazon Prime Air (2019). This extensive usage is due to technological innovations in the miniaturization of sensors, increased battery life, better processing power, and extended wireless connectivity options (2019). Today's drones incorporate advanced sensing technologies such as high-definition cameras, LiDAR, thermal cameras, and multispectral sensors, producing unprecedented levels of real-time information that facilitate advanced decision-making processes (2019). Security vulnerabilities have already resulted in real-world incidents: in 2019, a GPS spoofing attack diverted multiple UAVs in a commercial testbed, resulting in loss of drones worth more than USD 200,000 (2019). Furthermore, in a simulated man-in-the-middle attack on a drone swarm control network, researchers proved that up to 80% of the drones might be hijacked in 90 s (2019). The intrinsic nature of IoD systems poses distinctive security threats to those using conventional IoT networks (2019), such as resource limitations, since drones usually have limited computational capabilities, power sources, and storage capacities, calling for lightweight security measures (2019); dynamic network topologies (2020), with the high mobility of drones resulting in perpetually varying network topologies, making it difficult to integrate static security measures (2019); real-time requirements (2020), as some critical applications require minimal latency in data processing and transmission, putting high-performance requirements on security measures (2020); wireless vulnerabilities, such as the use of wireless communications making drone networks susceptible to jamming, eavesdropping, and man-in-the-middle attacks (2020); and physical accessibility, with drones deployed in open environments being more exposed to capture and hardware attacks (2020). Current security solutions for IoD systems have generally relied on encryption methods (2020), blockchain (2020), and legacy authentication schemes (2020). Although these methods deal with some security issues (2020), they usually have huge computational overheads that contradict the real-time constraints and limited resources of drone systems (2020). Furthermore, legacy security protocols also tend to overlook the specific mobility characteristics and communication constraints of drone networks (2020). Several authentication frameworks have been suggested for IoD environments in particular. [PERSON] et al. (2020) suggested a mutual authentication scheme based on elliptic curve cryptography, which is secure but consumingly computational.