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Securing High-Resolution Images From Unmanned Aerial Vehicles With DNA Encoding and Bit-Plane Extraction Method

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Unmanned aerial vehicles (UAVs) are getting more popular for deployment in surveillance related operations owing to their flexibility and ability to reach hazardous areas. Moreover, the quality of digital cameras… Click to show full abstract

Unmanned aerial vehicles (UAVs) are getting more popular for deployment in surveillance related operations owing to their flexibility and ability to reach hazardous areas. Moreover, the quality of digital cameras is getting better, and they can capture and store more visual information in high-resolution images. Unfortunately, due to the resource-constrained nature of UAVs, storing such large images can exhaust memory and related resources; whereas, the transmission of these images over the public link can pose several security threats. Securing these critical images during transmission from unauthorized access can be achieved through the use of efficient encryption techniques. This article proposes a novel encryption scheme incorporating both confusion and diffusion for encrypting both grey-scale and color images. In the proposed- encryption scheme, the image blocks are rearranged using a combination of random permutation, rotation, DNA encoding and zigzag pattern. Next, a bit-plane extraction method is used to obtain eight different bit-planes, including the most and least significant ones, from the scrambled image. These extracted bit-planes are then processed using confusion and diffusion techniques with a secret key, which is created using a hyper-chaotic map. The proposed method for encrypting the images taken by unmanned ariel vehicles is evaluated by examining its security level and time complexity using evaluation metrics such as correlation, entropy, energy, histogram analysis, keyspace and key sensitivity. The results and analysis demonstrated that the proposed encryption algorithm is able to effectively secure digital images. Additionally, the proposed work is also found to be superior to existing methods when compared using statistical security metrics.

Keywords: bit; resolution images; high resolution; method; aerial vehicles; unmanned aerial

Journal Title: IEEE Access
Year Published: 2023

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