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Unmanned aerial vehicles (UAVs) or Drones technology has a huge potential for supporting different efficient solutions for the smart applications in our world. The applications include smart things, smart transportation, smart cities, smart healthcare, smart personal care, smart house, smart industries, and so on. Due to the sensitive applications of UAVs, the security has become a major concern, and therefore, efficient techniques are required to protect captured data from hackers and the fictitious activities from illegitimate users. Machine learning (ML) techniques play a vital role in improving UAVs' security intelligently, while blockchain is recent technology for decentralized UAVs and security. Furthermore, watermarking guarantees digital media to be authenticated, protected, and copyright. Therefore, we provide a comprehensive survey of optimal techniques, which are used for securing UAVs applications in terms of blockchain, ML, and watermarking. Furthermore, we introduce each technique with the advantages and suitably used for securing UAVs collaboration applications. This survey contributes to a better understanding of the blockchain, ML, and watermarking techniques for securing UAVs and sheds new light on challenges and opportunities on subject applications.
Unmanned aerial vehicles (UAVs) or Drones technology has a huge potential for supporting different efficient solutions for the smart applications in our world. The applications include smart things, smart transportation, smart cities, smart healthcare, smart personal care, smart house, smart industries, and so on. Due to the sensitive applications of UAVs, the security has become a major concern, and therefore, efficient techniques are required to protect captured data from hackers and the fictitious activities from illegitimate users. Machine learning (ML) techniques play a vital role in improving UAVs' security intelligently, while blockchain is recent technology for decentralized UAVs and security. Furthermore, watermarking guarantees digital media to be authenticated, protected, and copyright. Therefore, we provide a comprehensive survey of optimal techniques, which are used for securing UAVs applications in terms of blockchain, ML, and watermarking. Furthermore, we introduce each technique with the advantages and suitably used for securing UAVs collaboration applications. This survey contributes to a better understanding of the blockchain, ML, and watermarking techniques for securing UAVs and sheds new light on challenges and opportunities on subject applications.
The watermarking technique is an active subject in current research used as a solution for copyright protection in multimedia documents. In this paper, we propose the first hardware invisible robust video watermarking application based on motion estimation. Since the designers of this application face many challenges, two types of architecture are performed: static and dynamic/partial reconfigurable architecture. The proposed architecture is adapted to HEVC encoded video. Two protection techniques are linked up: the digital watermarking to insert a watermark in the video, and the scrambling technique for overall video protection. The watermark embedding is treated in the horizontal and vertical components of even motion vectors. Eventually, the entire vectors are scrambled. The used watermark is a binary sequence where only one bit is inserted into the horizontal and the vertical components of motion vectors. The recommended architecture applies for slow and fast video sequence, where we use a motion estimator reconfigured according to the macro-block video movement. We also utilize a pipeline structure and a clock gating module to increase computing power and reduce power consumption. Experimental results show that the suggested static and dynamic/partial reconfigurable architecture guarantees material efficiency and superior performance in terms of frequency and power consumption.
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