Image encryption algorithm flow chart.
<div><p>Images are important information carriers in our lives, and images should be secure when transmitted and stored. Image encryption algorithms based on chaos theory emerge in endlessly. Based on previous various chaotic image fast encryption algorithms, this paper proposes a color...
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| منشور في: |
2025
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| _version_ | 1852023286276292608 |
|---|---|
| author | Ye Tao (326899) |
| author2 | Wenhua Cui (2315944) Shanshan Wang (283009) Yayun Wang (370584) |
| author2_role | author author author |
| author_facet | Ye Tao (326899) Wenhua Cui (2315944) Shanshan Wang (283009) Yayun Wang (370584) |
| author_role | author |
| dc.creator.none.fl_str_mv | Ye Tao (326899) Wenhua Cui (2315944) Shanshan Wang (283009) Yayun Wang (370584) |
| dc.date.none.fl_str_mv | 2025-01-24T18:47:42Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0310279.g021 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/Image_encryption_algorithm_flow_chart_/28274356 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified traditional chinese fan chaos theory emerge big data era important information carriers two chaotic mappings multiple subsequent pixels pixel changes position div >< p average information entropy color images based image encryption algorithm information loss three pixels color images chaotic sequence average uaci average npcr sine operations paper proposes noise attack many experiments main purpose lyapunov index image encryption greatly improves exhaustion attack encryption process differential attack decryption speed common attacks also resist |
| dc.title.none.fl_str_mv | Image encryption algorithm flow chart. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <div><p>Images are important information carriers in our lives, and images should be secure when transmitted and stored. Image encryption algorithms based on chaos theory emerge in endlessly. Based on previous various chaotic image fast encryption algorithms, this paper proposes a color image sector fast encryption algorithm based on one-dimensional composite sinusoidal chaotic mapping. The main purpose of this algorithm is to improve the encryption and decryption speed of color images and improve the efficiency of image encryption in the big data era. First, four basic chaos maps are combined in pairs and added with sine operations. Six one-dimensional composite sinusoidal chaos maps (CSCM) were obtained. Secondly, select the two best chaotic mappings LCS and SCS. The randomness of these two chaotic mappings was verified through Lyapunov index and NIST SP 800–22 randomness tests. Thirdly, the encryption process is carried out according to the shape of a traditional Chinese fan, and the diffusion and scrambling of each pixel of the image are performed in parallel. This greatly improves encryption speed. When diffusing, changing the value of one pixel can affect the values of multiple subsequent pixels. When scrambling, each pixel changes position with the three pixels before it according to the chaotic sequence. Finally, through many experiments, it is proved that the image encryption algorithm not only greatly improves the encryption and decryption speed, but also improves various indexes. The key space reached 2<sup>192</sup>, the average information entropy was 7.9994, the average NPCR was 99.6172, and the average UACI was 33.4646. The algorithm can also resist some common attacks and accidents, such as exhaustion attack, differential attack, noise attack, information loss and so on.</p></div> |
| eu_rights_str_mv | openAccess |
| id | Manara_7e5bc79c68136645fa09e8d8edc2affa |
| identifier_str_mv | 10.1371/journal.pone.0310279.g021 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/28274356 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Image encryption algorithm flow chart.Ye Tao (326899)Wenhua Cui (2315944)Shanshan Wang (283009)Yayun Wang (370584)Space ScienceEnvironmental Sciences not elsewhere classifiedBiological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedChemical Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedtraditional chinese fanchaos theory emergebig data eraimportant information carrierstwo chaotic mappingsmultiple subsequent pixelspixel changes positiondiv >< paverage information entropycolor images basedimage encryption algorithminformation lossthree pixelscolor imageschaotic sequenceaverage uaciaverage npcrsine operationspaper proposesnoise attackmany experimentsmain purposelyapunov indeximage encryptiongreatly improvesexhaustion attackencryption processdifferential attackdecryption speedcommon attacksalso resist<div><p>Images are important information carriers in our lives, and images should be secure when transmitted and stored. Image encryption algorithms based on chaos theory emerge in endlessly. Based on previous various chaotic image fast encryption algorithms, this paper proposes a color image sector fast encryption algorithm based on one-dimensional composite sinusoidal chaotic mapping. The main purpose of this algorithm is to improve the encryption and decryption speed of color images and improve the efficiency of image encryption in the big data era. First, four basic chaos maps are combined in pairs and added with sine operations. Six one-dimensional composite sinusoidal chaos maps (CSCM) were obtained. Secondly, select the two best chaotic mappings LCS and SCS. The randomness of these two chaotic mappings was verified through Lyapunov index and NIST SP 800–22 randomness tests. Thirdly, the encryption process is carried out according to the shape of a traditional Chinese fan, and the diffusion and scrambling of each pixel of the image are performed in parallel. This greatly improves encryption speed. When diffusing, changing the value of one pixel can affect the values of multiple subsequent pixels. When scrambling, each pixel changes position with the three pixels before it according to the chaotic sequence. Finally, through many experiments, it is proved that the image encryption algorithm not only greatly improves the encryption and decryption speed, but also improves various indexes. The key space reached 2<sup>192</sup>, the average information entropy was 7.9994, the average NPCR was 99.6172, and the average UACI was 33.4646. The algorithm can also resist some common attacks and accidents, such as exhaustion attack, differential attack, noise attack, information loss and so on.</p></div>2025-01-24T18:47:42ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0310279.g021https://figshare.com/articles/figure/Image_encryption_algorithm_flow_chart_/28274356CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/282743562025-01-24T18:47:42Z |
| spellingShingle | Image encryption algorithm flow chart. Ye Tao (326899) Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified traditional chinese fan chaos theory emerge big data era important information carriers two chaotic mappings multiple subsequent pixels pixel changes position div >< p average information entropy color images based image encryption algorithm information loss three pixels color images chaotic sequence average uaci average npcr sine operations paper proposes noise attack many experiments main purpose lyapunov index image encryption greatly improves exhaustion attack encryption process differential attack decryption speed common attacks also resist |
| status_str | publishedVersion |
| title | Image encryption algorithm flow chart. |
| title_full | Image encryption algorithm flow chart. |
| title_fullStr | Image encryption algorithm flow chart. |
| title_full_unstemmed | Image encryption algorithm flow chart. |
| title_short | Image encryption algorithm flow chart. |
| title_sort | Image encryption algorithm flow chart. |
| topic | Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified traditional chinese fan chaos theory emerge big data era important information carriers two chaotic mappings multiple subsequent pixels pixel changes position div >< p average information entropy color images based image encryption algorithm information loss three pixels color images chaotic sequence average uaci average npcr sine operations paper proposes noise attack many experiments main purpose lyapunov index image encryption greatly improves exhaustion attack encryption process differential attack decryption speed common attacks also resist |