A lightweight noise-tolerant encryption scheme for secure communication: An unmanned aerial vehicle application

Shafique, Arslan; Mehmood, Abid; Elhadef, Mourad; Khan, Kashif Hesham

doi:10.1371/journal.pone.0273661

Cited by 13 publications

(9 citation statements)

References 77 publications

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“…The smaller the MSE, the higher the similarity between the two. The calculation formula for MSE can be found in [36]. To more intuitively test the robustness of the voice encryption scheme proposed in this paper, as shown in figure 13, we plotted the line graph of MSE as the noise embedding strength K varies, as shown in figure 14, we plotted the line graph of MSE as the percentage of shearing area changes.…”

Section: Mean Squared Error Analysismentioning

confidence: 99%

Optical voice encryption based on speckle-illuminated fourier ptychography and plaintext-related chaotic random phase mask

Li,

Xu,

Wang

et al. 2024

Phys. Scr.

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In this paper, we propose an optical voice encryption scheme based on speckle-illuminated Fourier ptychography (FP) and plaintext-related chaotic random phase mask (CRPM). In this proposed encryption scheme, the plaintext-related CRPMs are generated by chaotic Lozi map and secure hash algorithm (SHA-256). During the encryption process, the voice signal to be encrypted is first converted into a two-dimensional (2D) voice map. Then, with the help of CRPMs and speckle-illuminated FP, the voice map is encrypted into a series of noise-like low-resolution images. During the decryption process, the original voice signal can be recovered from the series of noise-like low-resolution images via Fourier ptychographic phase retrieval algorithm and the CRPMs. To the best of our knowledge, it is the first time to use the Fourier ptychography and chaotic random phase mask to implement the optical encryption of the voice signal. In addition, in this proposed encryption scheme, the chaotic parameters can replace the whole random phase masks as the secret keys, which makes the management and transmission of the secret keys become more convenient. Moreover, since the plaintext-related chaotic parameter keys can be updated dynamically, the security of the proposed encryption scheme can be further improved. The feasibility, security and robustness of the proposed encryption scheme are further analyzed by numerical simulations.

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Section: Mean Squared Error Analysismentioning

confidence: 99%

Optical voice encryption based on speckle-illuminated fourier ptychography and plaintext-related chaotic random phase mask

Li,

Xu,

Wang

et al. 2024

Phys. Scr.

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“…A secure drone monitoring framework refers to a set of protocols, systems, and tools that ensure the safe and secure operation of drones used for surveillance purposes. This framework would include elements such as encryption for sensitive data, secure communication channels for transmitting the data, and robust security measures to protect against hacking or unauthorized access [46]- [48]. Additionally, the framework might include guidelines for drone operation, such as specific flying patterns or altitude restrictions, to ensure the safety of both the drone and those in the area being surveyed.…”

Section: Secure and Safe Drone Monitoring Architecturementioning

confidence: 99%

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

et al. 2023

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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 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.INDEX TERMS Unmanned aerial vehicles, chaos theory, cyberattacks, DNA encoding

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“…Similarly to MSE, a lower MAE indicates a higher quality reconstructed image 41 – 43 The MAE is defined as follows: MAE=1M×N∑i=0M−1∑j=0N−1|Pij−Cij|.…”

Section: Experimental Analysis Of the Proposed Algorithmmentioning

confidence: 99%

Hybrid image encryption algorithm based on compressive sensing, gray wolf optimization, and chaos

Abdul-Kareem,

Mahmoud Al-Jawher

2023

J. Electron. Imag.

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Growing reliance on digital communications has necessitated development of dependable and secure technologies to ensure that the transmission and reception of images over the Internet do not pose a risk to the data of individuals and governments. We propose developing a hybrid image encryption and compression algorithm by combining compressive sensing, the gray wolf algorithm, and multidimensional chaotic systems. It aims to generate a highly secure encrypted image while conserving transmission and storage resources. This algorithm overlaps several stages designed to protect vital images while minimizing size. First, the image is converted to the frequency domain using the discrete wavelet transform. Then, the discrete wavelet transform coefficients are scrambled globally using the Waleed-Ali Map and the gray wolf algorithm. Second, the confused image is measured by a parameters-controlled matrix to reduce transmission costs. The final encrypted image is obtained after performing the diffusion operation with a bitstream derived from the Nahrain chaotic map. The average peak signal-to-noise ratio score was 53.1995, and the average mean squared error score was 0.6130, demonstrating that the plaintext and decrypted images are identical. The average correlation coefficient score was −0.010095; the average entropy analysis was 7.9987; and the average number of pixel change rate and unified average changing intensity analyses were 99.60 and 33.52, respectively. The experimental results demonstrate the algorithm's efficiency and robustness, as well as the high quality of the reconstructed image.

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A lightweight noise-tolerant encryption scheme for secure communication: An unmanned aerial vehicle application

Cited by 13 publications

References 77 publications

Optical voice encryption based on speckle-illuminated fourier ptychography and plaintext-related chaotic random phase mask

Optical voice encryption based on speckle-illuminated fourier ptychography and plaintext-related chaotic random phase mask

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

Hybrid image encryption algorithm based on compressive sensing, gray wolf optimization, and chaos

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