Abstract
An image encryption algorithm has been proposed that satisfies the data encryption and compression requirements. The most important stage of encryption algorithms is reliable, unpredictable and random key generation. In our proposed method, an optimization-based key generator is used for the key generation algorithm used in the encryption part of the data. The random number generator method based on the disposable strip principle we use provides unconditional trust by generating different random keys each time. The statistical achievements of the optimization-based key generator also show themselves in the field of image encryption. Its success in image coding has been examined with analysis methods such as The number of changing pixel rate (NPCR), the unified averaged changed intensity (UACI) and histogram analysis. The successful results show that the proposed key generation is a secure key generator that can also be used in the field of image encryption. Therefore, it has been seen that optimization-based random number generator can be used in many other cryptographic fields.
References
- Asif, M. ve Baig, R., (2009). "Solving NP-complete problem using ACO algorithm," 2009 International Conference on Emerging Technologies, pp. 13-16, doi: 10.1109/ICET.2009.5353209.
- Burhan, Y., Artuger, F. ve Ozkaynak, F., (2019). "A Novel Hybrid Image Encryption Algorithm Based on Data Compression and Chaotic Key Planning Algorithms," 2019 7th International Symposium on Digital Forensics and Security (ISDFS), pp. 1-5, doi: 10.1109/ISDFS.2019.8757530.
- Eröz, E., Tanyıldızı, E. ve F. Özkaynak, (2021). "Determination of Suitable Configuration Parameters for Linear Feedback Shift Register using Binary Bat Optimization Algorithm," IEEE EUROCON 2021 - 19th International Conference on Smart Technologies, pp. 348-351, doi: 10.1109/EUROCON52738.2021.9535616.
- Garipcan, A. M. ve Erdem, E., (2019). Implementation and Performance Analysis of True Random Number Generator on FPGA Environment by Using Non-periodic Chaotic Signals Obtained from Chaotic Maps. Arab J Sci Eng 44, 9427–9441. https://doi.org/10.1007/s13369-019-04027-x
- Garipcan A. M. ve Erdem E., (2020). A TRNG using chaotic entropy pool as a post-processing technique: analysis, design and FPGA implementation. Analog Integr Circ Sig Process 103, 391–410. https://doi.org/10.1007/s10470-020-01605-0
- Kennedy, J. ve Eberhart, R. C., (1997). A discrete binary version of the particle swarm algorithm. In: IEEE international conference on computational cybernetics and simulation, pp 4104–4108.
- Mirjalili, S., Mirjalili, S.M. ve Yang, X.S., (2014). Binary bat algorithm, Neural Comput. Appl. 25, 663–681.
- Özkaynak, F, (2017). Role of NPCR and UACI tests in security problems of chaos based image encryption algorithms and possible solution proposals, 2017 International Conference on Computer Science and Engineering.
- Rashedi, E., Nezamabadi-pour H. ve Saryazdi S., (2009). BGSA: binary gravitational search algorithm. Nat Comput 9:727–745.
- Robshaw, M. ve Billet, O., editors. (2008). New Stream Cipher Designs: The eSTREAM Finalists, volume 4986 of LNCS. Springer.
- Schindler, W., (2009). “Random number generators for cryptographic applications”, C.K. Koc (ed.): Cryptographic Engineering. Springer, Signals and Communication Theory, Berlin, DOI: 10.1007/978- 0-387-71817-0_2.
- Sheveleva, A. M. ve Belyaev, S. A., (2021). "Development of the Software for Solving the Knapsack Problem by Solving the Traveling Salesman Problem," 2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus), pp. 652-656, doi: 10.1109/ElConRus51938.2021.9396448.
- Stipčević, M. ve Koç, Ç. K., (2014). “True random number generators”, in Koç Ç. K. (eds) Open Problems in Mathematics and Computational Science. Springer, Cham. DOI: 10.1007/978-3-319-106830_12.
- Paar, C. ve Pelzl, J., (2010). Understanding Cryptography A Textbook for Student and Practitioners, Springer.
Optimizasyon Algoritmaları ile Üretilen Kriptolojik Anahtarları Temel Alan Görüntü Şifreleme Algoritması
Abstract
Veri şifreleme ve sıkıştırma gereksinimlerini sağlayan bir görüntü şifreleme algoritması önerilmiştir. Şifreleme algoritmalarının en önemli aşaması güvenilir, tahmin edilemez ve rastgele anahtar üretme işlemidir. Önerdiğimiz yöntemde, verilerin şifreleme kısmında kullanılan anahtar üretim algoritması için optimizasyon temelli bir anahtar üreteci kullanılmıştır. Kullandığımız tek kullanımlık şerit prensibine dayanan rastgele sayı üreteci yöntem, her seferinde farklı rastgele anahtar üreterek koşulsuz güven sağlamaktadır. Optimizasyon temelli anahtar üretecinin elde ettiği istatistiksel başarılar görüntü şifreleme alanında da kendini göstermektedir. Değişken piksel hızı sayısı (NPCR), birleşik ortalama değişen yoğunluk (UACI) ve histogramı analizi gibi analiz yöntemleri ile görüntü şifreleme alanlarında başarısı incelenmiştir. Elde edilen başarılı sonuçlar, önerilen anahtar üretiminin görüntü şifreleme alanında da kullanılabilir güvenli bir anahtar üreteci olduğu ortaya koyulmuştur. Dolayısıyla kriptografik diğer pek çok alanda da optimizasyon temelli rastgele sayı üretecinin kullanılabileceği görülmüştür.
References
- Asif, M. ve Baig, R., (2009). "Solving NP-complete problem using ACO algorithm," 2009 International Conference on Emerging Technologies, pp. 13-16, doi: 10.1109/ICET.2009.5353209.
- Burhan, Y., Artuger, F. ve Ozkaynak, F., (2019). "A Novel Hybrid Image Encryption Algorithm Based on Data Compression and Chaotic Key Planning Algorithms," 2019 7th International Symposium on Digital Forensics and Security (ISDFS), pp. 1-5, doi: 10.1109/ISDFS.2019.8757530.
- Eröz, E., Tanyıldızı, E. ve F. Özkaynak, (2021). "Determination of Suitable Configuration Parameters for Linear Feedback Shift Register using Binary Bat Optimization Algorithm," IEEE EUROCON 2021 - 19th International Conference on Smart Technologies, pp. 348-351, doi: 10.1109/EUROCON52738.2021.9535616.
- Garipcan, A. M. ve Erdem, E., (2019). Implementation and Performance Analysis of True Random Number Generator on FPGA Environment by Using Non-periodic Chaotic Signals Obtained from Chaotic Maps. Arab J Sci Eng 44, 9427–9441. https://doi.org/10.1007/s13369-019-04027-x
- Garipcan A. M. ve Erdem E., (2020). A TRNG using chaotic entropy pool as a post-processing technique: analysis, design and FPGA implementation. Analog Integr Circ Sig Process 103, 391–410. https://doi.org/10.1007/s10470-020-01605-0
- Kennedy, J. ve Eberhart, R. C., (1997). A discrete binary version of the particle swarm algorithm. In: IEEE international conference on computational cybernetics and simulation, pp 4104–4108.
- Mirjalili, S., Mirjalili, S.M. ve Yang, X.S., (2014). Binary bat algorithm, Neural Comput. Appl. 25, 663–681.
- Özkaynak, F, (2017). Role of NPCR and UACI tests in security problems of chaos based image encryption algorithms and possible solution proposals, 2017 International Conference on Computer Science and Engineering.
- Rashedi, E., Nezamabadi-pour H. ve Saryazdi S., (2009). BGSA: binary gravitational search algorithm. Nat Comput 9:727–745.
- Robshaw, M. ve Billet, O., editors. (2008). New Stream Cipher Designs: The eSTREAM Finalists, volume 4986 of LNCS. Springer.
- Schindler, W., (2009). “Random number generators for cryptographic applications”, C.K. Koc (ed.): Cryptographic Engineering. Springer, Signals and Communication Theory, Berlin, DOI: 10.1007/978- 0-387-71817-0_2.
- Sheveleva, A. M. ve Belyaev, S. A., (2021). "Development of the Software for Solving the Knapsack Problem by Solving the Traveling Salesman Problem," 2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus), pp. 652-656, doi: 10.1109/ElConRus51938.2021.9396448.
- Stipčević, M. ve Koç, Ç. K., (2014). “True random number generators”, in Koç Ç. K. (eds) Open Problems in Mathematics and Computational Science. Springer, Cham. DOI: 10.1007/978-3-319-106830_12.
- Paar, C. ve Pelzl, J., (2010). Understanding Cryptography A Textbook for Student and Practitioners, Springer.
Details
| Primary Language | Turkish |
|---|---|
| Subjects | Engineering |
| Journal Section | Articles |
| Authors | |
| Early Pub Date | June 23, 2023 |
| Publication Date | June 30, 2023 |
| Submission Date | September 30, 2022 |
| Acceptance Date | November 10, 2022 |
| Published in Issue | Year 2023 Volume: 9 Issue: 1 |
