Evidence map›Paper›PMID 40676102›Full record

ArticleScientific reports2025

Securing face images in UAV networks using chaos and DNA cryptography approach.

Saba Inam, Shamsa Kanwal, Eaman Amin, Omar Cheikhrouhou, Monia Hamdi

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Saba InamDepartment of Mathematical Sciences, Fatima Jinnah Women University, The Mall, Rawalpindi, Pakistan. saba.inam@fjwu.edu.pk.
Shamsa KanwalDepartment of Mathematical Sciences, Fatima Jinnah Women University, The Mall, Rawalpindi, Pakistan.
Eaman AminDepartment of Mathematical Sciences, Fatima Jinnah Women University, The Mall, Rawalpindi, Pakistan.
Omar CheikhrouhouCES Laboratory, ENIS, University of Sfax, Sfax, 3038, Tunisia.
Monia HamdiDepartment of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In future applications of UAVs, the frequent transmission of image data raises significant security concerns, particularly regarding the privacy of facial information. Existing methods for protecting such data are often inadequate, especially in the context of UAVs, which require both high security and efficiency. To address these challenges, this paper proposes a face encryption scheme utilizing a 4D hyperchaotic Chen system and DNA cryptography. First, edge recognition face detection technology is employed to detect facial features, with the corresponding matrix selected for encryption. The eigenvalues of the selected matrix are then extracted and hashed using the SHA-256 hash algorithm to enhance security, generating plain image associated chaotic sequences. These sequences are used for Multi-Dimensional cryptic transformation. By employing plaintext-associated hyperchaotic sequences, ciphertext feedback method and dynamic DNA chain encryption, the proposed face encryption scheme significantly strengthens resistance against cryptographic attacks. Simulations were conducted using MATLAB and the resulting performance evaluation metrics were compared with the current state-of-the-art (SOTA) schemes. Experimental outcomes and security analysis confirm that this face encryption scheme provides robust security and high efficiency, as evidenced by key performance metrics specifically an information entropy value of 7.9992, MSE of 8908.61, PSNR of 8.9619, SSIM of 0.00091, NPCR of 99.7163%, UACI of 33.5671%, demonstrating the robustness of our encryption algorithm against differential attacks, and a key space of[Formula: see text], ensuring resistance against brute-force attacks. Thus, the proposed face encryption scheme offers excellent performance and holds promising potential for ensuring face privacy by preventing unauthorized access to facial information.

Indexed as

Computer SecurityFaceImage Processing, Computer-AssistedAlgorithmsDNAHumansDNAChaotic systemDNA encodingFace detectionImage encryptionPrivacy-preservingSecurity analysisSHA-256

Identifiers

PMID40676102
PMCPMC12271356

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.