A New Image Encryption Algorithm Based on DNA State Machine for UAV Data Encryption
Drone-based surveillance has become widespread due to its flexibility and ability to access hazardous areas, particularly in industrial complexes. As digital camera capabilities improve, more visual information can be stored in high-resolution images, resulting in larger image sizes. Therefore, algo...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-01-01
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| Series: | Drones |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-446X/7/1/38 |
| _version_ | 1797443628267732992 |
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| author | Moatsum Alawida Je Sen Teh Wafa’ Hamdan Alshoura |
| author_facet | Moatsum Alawida Je Sen Teh Wafa’ Hamdan Alshoura |
| author_sort | Moatsum Alawida |
| collection | DOAJ |
| description | Drone-based surveillance has become widespread due to its flexibility and ability to access hazardous areas, particularly in industrial complexes. As digital camera capabilities improve, more visual information can be stored in high-resolution images, resulting in larger image sizes. Therefore, algorithms for encrypting digital images sent from drones must be both secure and highly efficient. This paper presents a novel algorithm based on DNA computing and a finite state machine (FSM). DNA and FSM are combined to design a key schedule with high flexibility and statistical randomness. The image encryption algorithm is designed to achieve both confusion and diffusion properties simultaneously. The DNA bases themselves provide diffusion, while the random integers extracted from the DNA bases contribute to confusion. The proposed algorithm underwent a thorough set of statistical analyses to demonstrate its security. Experimental findings show that the proposed algorithm can resist many well-known attacks and encrypt large-sized images at a higher throughput compared to other algorithms. High experimental results for the proposed algorithm include correlation coefficients of 0.0001 and Shannon entropy of 7.999. Overall, the proposed image encryption algorithm meets the requirements for use in drone-based surveillance applications. |
| first_indexed | 2024-03-09T12:59:48Z |
| format | Article |
| id | doaj.art-66353dc2093a4a179274a0a01f18f874 |
| institution | Directory Open Access Journal |
| issn | 2504-446X |
| language | English |
| last_indexed | 2024-03-09T12:59:48Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj.art-66353dc2093a4a179274a0a01f18f8742023-11-30T21:55:25ZengMDPI AGDrones2504-446X2023-01-01713810.3390/drones7010038A New Image Encryption Algorithm Based on DNA State Machine for UAV Data EncryptionMoatsum Alawida0Je Sen Teh1Wafa’ Hamdan Alshoura2Department of Computer Sciences, Abu Dhabi University, Abu Dhabi 59911, United Arab EmiratesSchool of Computer Sciences, Universiti Sains Malaysia, George Town 11800, MalaysiaSchool of Computer Sciences, Universiti Sains Malaysia, George Town 11800, MalaysiaDrone-based surveillance has become widespread due to its flexibility and ability to access hazardous areas, particularly in industrial complexes. As digital camera capabilities improve, more visual information can be stored in high-resolution images, resulting in larger image sizes. Therefore, algorithms for encrypting digital images sent from drones must be both secure and highly efficient. This paper presents a novel algorithm based on DNA computing and a finite state machine (FSM). DNA and FSM are combined to design a key schedule with high flexibility and statistical randomness. The image encryption algorithm is designed to achieve both confusion and diffusion properties simultaneously. The DNA bases themselves provide diffusion, while the random integers extracted from the DNA bases contribute to confusion. The proposed algorithm underwent a thorough set of statistical analyses to demonstrate its security. Experimental findings show that the proposed algorithm can resist many well-known attacks and encrypt large-sized images at a higher throughput compared to other algorithms. High experimental results for the proposed algorithm include correlation coefficients of 0.0001 and Shannon entropy of 7.999. Overall, the proposed image encryption algorithm meets the requirements for use in drone-based surveillance applications.https://www.mdpi.com/2504-446X/7/1/38drone securitydrone-based surveillanceDNAfinite state machineimage encryptionkey scheduling |
| spellingShingle | Moatsum Alawida Je Sen Teh Wafa’ Hamdan Alshoura A New Image Encryption Algorithm Based on DNA State Machine for UAV Data Encryption Drones drone security drone-based surveillance DNA finite state machine image encryption key scheduling |
| title | A New Image Encryption Algorithm Based on DNA State Machine for UAV Data Encryption |
| title_full | A New Image Encryption Algorithm Based on DNA State Machine for UAV Data Encryption |
| title_fullStr | A New Image Encryption Algorithm Based on DNA State Machine for UAV Data Encryption |
| title_full_unstemmed | A New Image Encryption Algorithm Based on DNA State Machine for UAV Data Encryption |
| title_short | A New Image Encryption Algorithm Based on DNA State Machine for UAV Data Encryption |
| title_sort | new image encryption algorithm based on dna state machine for uav data encryption |
| topic | drone security drone-based surveillance DNA finite state machine image encryption key scheduling |
| url | https://www.mdpi.com/2504-446X/7/1/38 |
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