Selection of best cipher system using fuzzy soft decision methodology

Ratan, Ram; Yadav, Arvind; Arya, Chaman Prakash

doi:10.47974/JDMSC-1853

Open Access Research Article

Selection of best cipher system using fuzzy soft decision methodology

^*Ram RatanCorresponding authorramratan_sag@hotmail.comScientific Analysis Group Defence Research and Development OrganizationDelhi, 110054, IndiaView full profile → , Arvind Yadavdrarvind@hrc.du.ac.inDepartment of Mathematics Hansraj College University of DelhiDelhi, 110007, IndiaView full profile → , Chaman Prakash Aryacarya28@gmail.comScientific Analysis Group Defence Research and Development OrganizationDelhi, 110054, IndiaView full profile →

* Corresponding author · click or hover a name for details

pp. 1087–1103Vol. 27Issue 3April 2024DOI: 10.47974/JDMSC-1853 Crossmark XML

Received:: 10 Aug 2022
Published Online:: 01 May 2024
Article type:: Research Article
Language:: EN
Article no.:: JDMSC-1853
Pages:: 1087–1103

Abstract

Selection of a most suitable cipher system among several such systems is an important problem of the customers which help to acquire a right cipher system for meeting the requirements of information security to safeguard the vital data. Any mistake in the selection of a right cipher system is very harmful as it may lead to compromise the security of vital information. In the paper, we propose a multi-criterion fuzzy soft decision making methodology to select one of the most suitable cipher system. Proposed methodology uses fuzzy soft set, fuzzy soft matrix, dominancy matrix and S-fuzzy set to compute score values and take a right decision. It exhibits out performance over existing methods as shown by explaining some examples. We apply proposed methodology in selecting a most suitable cipher system from a set of systems with respect to the choice of desired security attributes required by the customers.

Keywords

Cipher system Cryptography Information security Fuzzy soft set Multi-criterion decision

Subject Classifications

62H86

References

[1] Arvind and R. Ratan, Identifying traffic of same keys in cryptographic communications using fuzzy decision criteria and bit-plane measures, Int J Syst Assur Eng Manag, 11(2), 466-80, (2020).
[2] Emel Kizilkaya Aydogan, Cevriye Gencer and Saim Ayturk, Evaluation of a light machine gun using analytic network process, Defence Sci J, 59(3), 2731-283, (2009).
[3] Emin Aygun, Soft matrix product and soft cryptosystem, Filomat 32(19), 6519-6530, (2018).
[4] A. Bahramali, A. Houmansadr, R. Soltani, D. Goeckel and D. Towsley, Practical traffic analysis attacks on secure messaging. In the Proceedings of the Network and Distributed Systems Security (NDSS) Symposium 2020, https://dx.doi.org/10.14722/ndss.2020.24347.
[5] H. Beker and F. Piper, Cipher Systems: The Protection of Communications. Northwood Books, London, (1983).
[6] N, Cagman and S. Engnoglu, Fuzzy Soft Matrix Theory and its application in decision making, Iran J Fuzzy Syst, 9(1), 109-119, (2012).
[7] N. Cagman, S. Engnoglu and F. Citak, Fuzzy Soft Set Theory and Its Applications, Iran J Fuzzy Syst, 8(3), 137-147, (2011).
[8] N. Cagman and S. Engnoglu, Soft Set Matrix Theory and Its decision making, Comput Math Appl, 598 (10), 3308-3314, (2010).
[9] N. Cagman, S. Engnoglu and F. Citak, Soft Set theory and uni-int making, Eur J Oper Res, 207, 8484-855, (2010).
[10] D. Chen, E.C.C. Tsang, D.S. Yeung and X. Wang, The parametrization reduction of soft sets and its applications, Comput Math Appl 49, 757-763, (2005).
[11] M. Din, A.K. Bhateja and R. Ratan, Cryptanalysis of Geffe generator using genetic algorithm. In Proceedings of the SocProS 2013, AISC, Springer, 259, 509-515, (2014).
[12] A. Dainotti, A. Pescape and K.C. Claffy, Issues and future directions in traffic classification, IEEE Network, 26(1), 35-40, (2012).
[13] Feng Feng, Young BeaJun, Xiaoyan Liu and Lifeng Li, Adjustable approach to fuzzy soft set based decision making, J Comput Appl Math, 234, 10-20, (2010).
[14] X. Ge, B. Lu, F. Liu and X. Luo, Cryptanalyzing an image encryption algorithm with compound chaotic stream cipher based on perturbation, Nonlinear Dynam, 90(2), 1141-1150, (2017).
[15] M.K. Hasan and Mod. Yasin Ali, A Sultana and N.K. Mitra, Decision Making withe help of the repeated average method of fuzzy soft matrix, Int J Adv Math, 2019(1), 83-91, (2019).
[16] Seyyed Hossein, Jafari Petroudi, Zahra Nabati and Alireza Yaghobit, Some new results on fuzzy soft matrices, Turk J Fuzzy Syst, 8(1), 52-62, (2017).
[17] Junhua Hu, Li Pan, Yan Yang and Haiwei Chen, A group medical diagnosis model based on intuitionistic fuzzy soft sets, Appl Soft Comput, 77, 453-466, (2019).
[18] N.K. Jaiswal, Military Operations Research: Quantitative Decision Making, Kluwer Boston/Dordrecht/London (1997).
[19] A. Kerckhoffs, La cryptographhie militaire, Journal des Sciences Militaires. IX, 161-91, (1883).
[20] Murat KiriŞci, Medical decision making with respect to the fuzzy soft sets, J Interdiscipl Math, 23(4), 767-776, (2020).
[21] Zhi Kong, Liqun Gao, Lifu Wang and Steven Li,The normal parameter reduction of soft sets and its algorithm, Computer and Mathematics with Application, 56(12), 3029-3037, (2008).
[22] Zhi Kong, Liqun Gao and Lifu Wang, Comment on a fuzzy soft set theoretic approach to decision making problems, J Comput Appl Math, 223, 540-542, (2009).
[23] C. Li, D. Lin and J. LÜ, Cryptanalyzing an image-scrambling encryption algorithm of pixel bits, IEEE Multimedia, 3(3), 64-71, (2017).
[24] C. Li, Y. Zhang and E.Y. Xie, When an attacker meets a cipher-image in 2018: A year in review. J Inf Secur Appl, 48, (2019).
[25] C. Li, D. Lin, J. LÃ¼ and F. Hao, Cryptanalyzing an image encryption algorithm based on autoblocking and electrocardiography, IEEE MultiMedia, 25(4), 46-56, (2018).
[26] P.K. Maji, R. Biswas and A.R. Roy, An Application of soft sets in decision making problem, Comput Math Appl, 44(8-9), 1077-1083, (2002).
[27] P.K. Maji, R. Biswas and A.R. Roy, Fuzzy soft sets, J Fuzzy Appl Math, 9, 589-602, (2001).
[28] A. Menezes, S. Vanstone and P. Van Oorschot, Handbook of Applied Cryptography. CRC Press, Boca Raton, (1996).
[29] D. Molodtsov, Soft set theory-first result, Comput Math Appl, 37, 19-31, (1999).
[30] Wenjun Pan and Jianming Zhan, Two novel products of IFP-intuitionistic fuzzy soft sets and corresponding decision making methods, Journal of Discrete Mathematical Sciences and Cryptography, 21(3), 631-646, (2018).
[31] Z. Pawlak, Rough sets: Theoretic aspects of reasoning about data. Kluwer Academic Publishers, Boston, (1991).
[32] Xindong Peng and Harish Garg, Algorithm for interval-valued fuzzy soft sets in emergency decision making based on WDBA and CODAS with new information measure, Computers and Industrial Engineering, 119, 439-452, (2018).
[33] Xingdong Peng and Yong Yang, Algorithm for interval-valued fuzzy soft sets in stochastic multi-criteria decision making based on regret theory and prospect theory with combined weight, Appl Soft Comput, 54, 415-430, (2017).
[34] R. Ratan, Key independent decryption of graphically encrypted images. In Proceedings of the PAISI 2010, LNCS, Springer, 6122, 88-97, (2010).
[35] R. Ratan, Key independent retrieval of chaotic encrypted images. In Proceedings of the PReMI 2009, LNCS, Springer, 5909, 483-488, (2009).
[36] R. Ratan, Applications of Genetic Algorithms in Cryptology. In Proceedings of the SocProS 2013, AISC, Springer, 258, 821-831, (2014).
[37] R. Ratan and Arvind, Cryptanalysis of an image cipher using multi-entropy measures and the countermeasures, Defence Sci J, 74(4), 425-439 (2020).
[38] R. Ratan and Arvind, Security analysis of bitplane level image encryption schemes, Defence Sci J, 71(2), 209-221 (2021).
[39] R. Ratan and Arvind, Key independent image deciphering using neighbourhood similarity characteristics and divide-and-conquer attack, Recent Patents on Engineering, 15(4), 34-44 (2021).
[40] R. Ratan and Arvind, Bitplane specific measures and its applications in analysis of image ciphers, Advances in Signal Processing and Intelligent Recognition Systems, CCIS, Springer, 968, 282-297 (2019).
[41] A.R. Roy and P.K. Maji, A fuzzy soft set theoretic approach to decision making problems, J Comput Appl Math, 203(2), 212-218, (2007).
[42] C.E. Shannon, Communication theory of secrecy systems, Bell System Technical Journal, 28(4) 656-715, (1949).
[43] W. Stallings, Cryptography and Network Security. Prentice Hall, Englewood Cliffs, (2003).
[44] Zhifu Tao, Xi Liu, Huayou Chen, Jinpei Liu and Fei Guan, Linguistic Z-number fuzzy soft sets and its application on multiple attribute group decision making problems, Int J Intell Syst, 35, 105-124, (2020).
[45] Yong Yang, Chencheng Liang, Shiwei Ji and Tingting Liu, Adjustable soft disernibility matrix based on picture fuzzy soft sets and applications in decision making, J Intell Fuzzy Syst, 29(4), 1711-1722, (2015).
[46] D. Yong and S. Cheng, Evaluating the main battle tank using fuzzy number arithmetic operation, Defence Sci J, 56(2), 251-257, (2006).
[47] L.A. Zadeh, Fuzzy sets, Information and Control, 8(3), 338-353, (1965).
[48] A.H. Zarkri, H.M. Hussen, L.Y. Erwi and E. Al-Sharif, Application of soft sets to diagnose the educational obstacles for students, Journal of Innovative Technology and Education, 3(1), 61-70, (2016).
[49] Jianming Zhan and Jose Carlos R Alcantud, A survey of parameter reduction of soft sets and corresponding algorithms, Artificial Intelligence Review, 52(3), 1839-1872, (2019).
[50] H.J. Zimmermann, Fuzzy Sets, Decision Making and Expert Systems. Kluwer, Boston, (1987).

Views: 158Downloads: 6Citations: 0