Given the application domains of soft set theory, such as decision-making processes, image processing, machine learning, and data mining, it is natural to consider that this theory could be utilized more effectively in encryption systems. A review of the literature reveals that soft set-based encryption systems have been explored in a limited number of studies. This study seeks to develop a new approach for soft sets in encryption systems by utilizing newly introduced algebraic and topological tools. In this system, parties will be able to generate encryption keys independently using soft sets they determine themselves rather than through prior mutual agreement. Additionally, the method of key generation and the size of the key space in the resulting encryption system provides a more secure and distinct alternative compared to existing soft set-based encryption systems.
Citation: Erdal Bayram, Gülşah Çelik, Mustafa Gezek. An advanced encryption system based on soft sets[J]. AIMS Mathematics, 2024, 9(11): 32232-32256. doi: 10.3934/math.20241547
Given the application domains of soft set theory, such as decision-making processes, image processing, machine learning, and data mining, it is natural to consider that this theory could be utilized more effectively in encryption systems. A review of the literature reveals that soft set-based encryption systems have been explored in a limited number of studies. This study seeks to develop a new approach for soft sets in encryption systems by utilizing newly introduced algebraic and topological tools. In this system, parties will be able to generate encryption keys independently using soft sets they determine themselves rather than through prior mutual agreement. Additionally, the method of key generation and the size of the key space in the resulting encryption system provides a more secure and distinct alternative compared to existing soft set-based encryption systems.
[1] | D. Molodtsov, Soft set theory-first results, Comput. Math. Appl., 37 (1999), 19–31. https://doi.org/10.1016/S0898-1221(99)00056-5 doi: 10.1016/S0898-1221(99)00056-5 |
[2] | M. Yazdi, E. Zarei, S. Adumene, R. Abbassi, P. Rahnamayiezekavat, Uncertainty modeling in risk assessment of digitalized process systems, Meth. Chem. Proc. Safety, 6 (2022), 389–416. https://doi.org/10.1016/bs.mcps.2022.04.005 doi: 10.1016/bs.mcps.2022.04.005 |
[3] | H. Li, M. Yazdi, Stochastic game theory approach to solve system safety and reliability decision-making problem under uncertainty, In: Advanced Decision-Making Methods and Applications in System Safety and Reliability Problems. Studies in Systems, Decision and Control, Springer, 211 (2022). https://doi.org/10.1007/978-3-031-07430-1_8 |
[4] | E. Zarei, M. Yazdi, R. Moradi, A. BahooToroody, Expert judgment and uncertainty in sociotechnical systems analysis, In: in Safety Causation Analysis in Sociotechnical Systems: Advanced Models and Techniques. Studies in Systems, Decision and Control, Springer, 541 (2024). https://doi.org/10.1007/978-3-031-62470-4_18 |
[5] | P. K. Maji, R. Biswas, A. J. Roy, Soft set theory, Comput. Math. Appl., 45 (2003), 555–562. https://doi.org/10.1016/S0898-1221(03)00016-6 doi: 10.1016/S0898-1221(03)00016-6 |
[6] | M. I. Ali, F. Feng, X. Liu, W. K. Min, M. Shabir, On some new operations in soft set theory, Comput. Math. Appl., 57 (2009), 1547–1553. https://doi.org/10.1016/j.camwa.2008.11.009 doi: 10.1016/j.camwa.2008.11.009 |
[7] | J. C. R. Alcantud, A. Z. Khameneh, G. Santos-Garcia, M. Akram, A systematic literature review of soft set theory, Neural Comput. Applic., 36 (2024), 8951–8975. https://doi.org/10.1007/s00521-024-09552-x doi: 10.1007/s00521-024-09552-x |
[8] | N. Çağman, S. Karataş, S. Enginoğlu, Soft topology, Comput. Math. Appl., 62 (2011), 351–358. https://doi.org/10.1016/j.camwa.2011.05.016 doi: 10.1016/j.camwa.2011.05.016 |
[9] | M. Shabir, M. Naz, On soft topological spaces, Comput. Math. Appl., 61 (2011), 1786–1799. https://doi.org/10.1016/j.camwa.2011.02.006 doi: 10.1016/j.camwa.2011.02.006 |
[10] | S. Nazmul, S. K. Samanta, Neighbourhood properties of soft topological spaces, Ann. Fuzzy Math. Inform., 6 (2013), 1–15. |
[11] | S. Hussain, B. Ahmad, Some properties of soft topological spaces, Comput. Math. Appl., 62 (2011), 4058–4067. https://doi.org/10.1016/j.camwa.2011.09.051 doi: 10.1016/j.camwa.2011.09.051 |
[12] | W. K. Min, A note on soft topological spaces, Comput. Math. Appl., 61 (2011), 3524–3528. https://doi.org/10.1016/j.camwa.2011.08.068 doi: 10.1016/j.camwa.2011.08.068 |
[13] | M. Terepeta, On separating axioms and similarity of soft topological spaces, Soft Comput., 23 (2019), 1049–1057. https://doi.org/10.1007/s00500-017-2824-z doi: 10.1007/s00500-017-2824-z |
[14] | T. M. Al-shami, M. E. El-Shafei, Partial belong relation on soft separation axioms and decision-making problem, two birds with one stone, Soft Comput., 24 (2020), 5377–5387. https://doi.org/10.1007/s00500-019-04295-7 doi: 10.1007/s00500-019-04295-7 |
[15] | H. Hazra, P. Majumdar, S. K. Samanta, Soft topology, Fuzzy Inform. Eng., 4 (2012), 105–115. https://doi.org/10.1007/s12543-012-0104-2 doi: 10.1007/s12543-012-0104-2 |
[16] | A. Aygünoğlu, H. Aygün, Some notes on soft topological spaces, Neural Comput. Applic., 21 (2012), 113–119. https://doi.org/10.1007/s00521-011-0722-3 doi: 10.1007/s00521-011-0722-3 |
[17] | I. Zorlutuna, M. Akdag, W. K. Min, S. Atmaca, Remarks on soft topological spaces, Ann. Fuzzy Math. Inform., 3 (2012), 171–185. |
[18] | S. Das, S. K. Samanta, Soft metric, Ann. Fuzzy Math. Inform., 6 (2013), 77–94. |
[19] | T. M. Al-shami, L. D. R. Kočinac, The equivalence between the enriched and extended soft topologies, Appl. Comput. Math., 18 (2019), 149–162. |
[20] | J. C. R. Alcantud, Soft open bases and a novel construction of soft topologies from bases for topologies, Mathematics, 8 (2020), 672. https://doi.org/10.3390/math8050672 doi: 10.3390/math8050672 |
[21] | J. C. R. Alcantud, An operational characterization of soft topologies by crisp topologies, Mathematics, 9 (2021), 1656. https://doi.org/10.3390/math9141656 doi: 10.3390/math9141656 |
[22] | M. Matejdes, Methodological remarks on soft topology, Soft Comput., 25 (2021), 4149–4156. https://doi.org/10.1007/s00500-021-05587-7 doi: 10.1007/s00500-021-05587-7 |
[23] | G. Ali, M. Akram, Decision-making method based on fuzzy N-soft expert sets, Arabian J. Sci. Eng., 45 (2020), 10381–10400. https://doi.org/10.1007/s13369-020-04733-x doi: 10.1007/s13369-020-04733-x |
[24] | A. Adeel, M. Akram, N. Çağman, Decision-making analysis based on hesitant fuzzy N-soft ELECTRE-I approach, Soft Comput., 26 (2022), 11849–11863. https://doi.org/10.1007/s00500-022-06981-5 doi: 10.1007/s00500-022-06981-5 |
[25] | J. C. R. Alcantud, G. Santos-Garcia, M. Akram, A novel methodology for multi-agent decision-making based on N-soft sets, Soft Comput., 2023. https://doi.org/10.1007/s00500-023-08522-0 |
[26] | A. Kerckhoffs, La cryptographie militaire, J. Sci. Milit., 9 (1883), 5–38. |
[27] | R. L. Rivest, A. Shamir, L. Adleman, A method for obtaining digital signatures and public-key cryptosystems, Commun. ACM, 21 (1978), 120–126. https://doi.org/10.1145/359340.359342 doi: 10.1145/359340.359342 |
[28] | W. Diffie, M. E. Hellman, Multiuser cryptographic techniques, In: AFIPS National Computer Conference, New York, 1976. https://doi.org/10.1145/1499799.1499815 |
[29] | M. O. Rabin, Digitalized signatures and public key functions as intractable as factorisation, In: MIT/LCS/TR-212 MIT Laboratory for Computer Science, 1979. |
[30] | H. Aktaş, M. Kalkan, An application of the crystography, J. Math. Comput. Sci., 11 (2014), 147–158. http://dx.doi.org/10.22436/jmcs.011.02.07 doi: 10.22436/jmcs.011.02.07 |
[31] | N. Çağman, S. Enginoğlu, Soft matrix theory and its decision making, Comput. Math. Appl., 59 (2010), 3308–3314. https://doi.org/10.1016/j.camwa.2010.03.015 doi: 10.1016/j.camwa.2010.03.015 |
[32] | F. Feng, J. Cho, W. Pedrycz, H. Fujita, T. Herawan, Soft set based association rule mining, Knowledge-Based Syst., 111 (2016), 268–282. https://doi.org/10.1016/j.knosys.2016.08.020 doi: 10.1016/j.knosys.2016.08.020 |
[33] | M. Kalkan, Z. Zararsız, Kriptografi, steganografi ve kodlama teorisinin grup teorisi ile ilişkisinin incelenmesi ve bazı uygulamaların geliştirilmesi, Ph.D thesis, Nevşehir Hacıbektaş University, 2021. |
[34] | Z. Liu, J. C. R. Alcantud, K. Qin, L. Xiong, The soft sets and fuzzy sets-based neural networks and application, IEEE Access, 111 (2020), 268–282. https://doi.org/10.1109/ACCESS.2020.2976731 doi: 10.1109/ACCESS.2020.2976731 |
[35] | B. K. Tripathy, T. R. Sooraj, R. K. Mohanty, Rough set and soft set models in image processing, In: Intelligent Multimedia Data Analysis, Berlin, Boston, De Gruyter, 2019, 123–144. https://doi.org/10.1515/9783110552072-006 |
[36] | E. Aygün, Soft matrix product and soft cryptosystem, Filomat, 32 (2019), 6519–6530. https://doi.org/10.2298/FIL1819519A doi: 10.2298/FIL1819519A |
[37] | E. Aygün, AES encryption and a cryptosystem obtained with soft set Ⅱ, Cumhur. Sci. J., 40 (2019), 69–78. https://doi.org/10.17776/csj.416395 doi: 10.17776/csj.416395 |
[38] | B. Paik, S. K. Mondal, Introduction to soft cryptosystem and its application, Wirel. Pers. Commun., 125 (2022), 1801–1826. https://doi.org/10.1007/s11277-022-09635-9 doi: 10.1007/s11277-022-09635-9 |
[39] | İ. Yılmaz, Esnek kümeler ve vernam şifreleme üzerine, MSc. thesis, Erciyes University, 2023. |
[40] | M. Matsui, Linear cryptanalysis method for DES cipher, Lect. Notes Comput. Sci., 765 (1994), 386–397. |
[41] | D. R. Stinson, Cryptography theory and practice, Boca Raton: Chapman & Hall/CRC, 2006. |