Application of Tsallis entropy in defining a new generalized strong and weak secrecy

Document Type : Research Paper

Authors

1 Department of Statistics, Ferdowsi University of Mashhad, Mashhad, Iran

2 Department of Statistics, University of Birjand, Birjand, Iran

Abstract

In this paper, we explore the diverse applications and distinctive properties of Tsallis entropy by introducing generalized definitions of strong and weak secrecy. Tsallis entropy suggests that generalized weak secrecy and strong secrecy are commonly employed in information-theoretic security challenges. Additionally, we examine the interplay between Tsallis entropy and the criteria for strong and weak secrecy. The primary motivation behind this study is to elucidate the concept of “generalized weak secrecy,” a widely utilized notion. Also, this research delves into the precise relationship between conditional entropy and the minimum adversarial error probability, illustrating how generalized weak security can be translated into practical guarantees. For static and memoryless sources, it is demonstrated that the vanishing of the leakage rate requires the adversarial error probability to reach its upper bound. Moreover, generalized strong security, characterized by the vanishing of the variational distance, results in the complete operational failure of the adversary. These findings underscore the critical role of Tsallis entropy in assessing the security of systems.

Keywords

Main Subjects


[1] Balogh, S. G., Palla, G., Pollner, P., & Czegel, D. (2020). Generalized entropies, density of states, and non-extensivity. Scienti c reports, 10(1), 15516. https://doi.org/10.1038/s41598-020-72421-9
[2] Beck, C. (2009). Generalised information and entropy measures in physics. Contemporary Physics, 50(4), 495-510. https://doi.org/10.1080/00107510902823517
[3] Cover, T. M., & Thomas, J. A. (1991). Elements of Information Theory. New York:Wiley-Interscience. https://doi.org/10.1002/0471200611
[4] Csiszar, I., & Korner, J. (1978). Broadcast channels with con dential messages. IEEE Transactions on Information Theory, 24(3), 339-348. https://doi.org/10.1109/TIT.1978.1055892
[5] Ebrahimi, M., & Mehrpooya, A. (2014). An application of geometry in algebra: uncertainty of hyper MV-algebras. In Proceedings of the 7th seminar on geometry & topology, Tehran (pp. 529-534). https://dorl.net/dor/20.1001.1.23453942.1393.0.0.8.8
[6] Erokhin, V. (1958). -entropy of a discrete random variable. Theory of Probability and Its Applications, 3(1), 97-100. https://doi.org/10.1137/1103009
[7] Furuichi, S. (2006). Information theoretical properties of Tsallis entropies. Journal of Mathematical Physics, 47(2), 023302. https://doi.org/10.1063/1.2165740
[8] Havrda, J., & Charvat, F. (1967). Quanti cation method of classi cation processes. Concept of structural  -entropy. Kybernetika, 3(1), 30-35. https://dml.cz/handle/10338.dmlcz/125229
[9] He, B., Zhou, X., & Swindlehurst, A. L. (2016). On secrecy metrics for physical layer security over quasi-static fading channels. IEEE Transactions on Wireless Communications, 15(10), 6913-6924. https://doi.org/10.1109/TWC.2016.2591518
[10] Ho, S. W., & Verdu, S. (2008, July). Conditional entropy and error probability. In 2008 IEEE International Symposium on Information Theory, 1622-1626. https://doi.org/10.1109/ISIT.2008.4595316
[11] Ho, S. W. (2009). On the interplay between Shannon's information measures and reliability criteria. In 2009 IEEE International Symposium on Information Theory, 154-158. https://doi.org/10.1109/ISIT.2009.5205597
[12] Ho, S. W., & Verdu, S. (2010). On the interplay between conditional entropy and error probability. IEEE Transactions on Information Theory, 56(12), 5930-5942. https://doi.org/10.1109/TIT.2010.2079130
[13] Ho, S. W., & Verdu, S. (2015). Convexity/concavity of Renyi entropy and  -mutual information. In 2015 IEEE International Symposium on Information Theory (ISIT), 745-749. https://doi.org/10.1109/ISIT.2015.7282577
[14] Hyadi, A., Rezki, Z., & Alouini, M. S. (2016). An overview of physical layer security in wireless communication systems with CSIT uncertainty. IEEE Access, 4, 6121-6132. https://doi.org/10.1109/ACCESS.2016.2607706
[15] Jamalzadeh, J., & Ghasemi, K. (2024). Tsallis entropy of fuzzy -algebras. International Journal of Nonlinear Analysis and Applications, 15(12), 385-395. https://doi.org/10.22075/ijnaa.2024.33021.4709
[16] Jurkowski, J. (2013). Quantum discord derived from Tsallis entropy. International Journal of Quantum Information, 11(01), 1350013. https://doi.org/10.1142/S0219749913500134
[17] Kurzyk, D., Pawela, L., & Pucha la, Z. (2018). Conditional entropic uncertainty relations for Tsallis entropies. Quantum Information Processing, 17(8), 1-12. https://doi.org/10.1007/s11128-018-2009-4
[18] Lai, L., Ho, H. W., & Poor, H. V. (2008). Privacy-security tradeo s in biometric security systems. In 2008 46th Annual Allerton Conference on Communication, Control, and Computing, 268-273. https://doi.org/10.1109/LLERTON.2008.4797572
[19] Marshall, A. W., Olkin, I., & Arnold, B. C. (1979). Inequalities: theory of majorization and its applications. New York: Academic Press. https://doi.org/10.1016/C2010-0-64839-5
[20] Maurer, U., & Wolf, S. (2000, May). Information-theoretic key agreement: from weak to strong secrecy for free. In International Conference on the Theory and Applications of Cryptographic Techniques, 351-368. Springer, Berlin, Heidelberg.
[21] Mohamed, M. S., Barakat, H. M., Al Mutairi, A., & SidAhmed, M. (2023). Further properties of Tsallis extropy and some of its related measures. AIMS Mathematics, 8(12), 28219-28245. https://doi.org/10.3934/math.20231445
[22] Mojahedian, M. M., Gohari, A., & Aref, M. R. (2017, June). On the equivalency of reliability and security metrics for wireline networks. In 2017 IEEE International Symposium on Information Theory (ISIT), 2713-2717. https://doi.org/10.1109/ISIT.2017.8007007
[23] Rajagopal, A. K., Sudha, Nayak, A. S., & Devi, A. U. (2014). From the quantum relative Tsallis entropy to its conditional form: separability criterion beyond local and global spectra. Physical Review A, 89(1), 012331. https://doi.org/10.1103/PhysRevA.89.012331
[24] Rastegin, A. E. (2013). Bounds of the Pinsker and Fannes types on the Tsallis relative entropy. Mathematical Physics, Analysis and Geometry, 16(3), 213-228. https://doi.org/10.1007/s11040-013-9125-2
[25] Rastegin, A. E. (2015). Further results on generalized conditional entropies. RAIRO-Theoretical Informatics and Applications, 49(1), 67-92. https://doi.org/10.1051/ita/2015004
[26] Shah, S. M., & Sharma, V. (2015, March). Achieving Shannon capacity region as secrecy rate region in a multiple access wiretap channel. In 2015 IEEE Wireless Communications and Networking Conference (WCNC), 759-764.
https://doi.org/10.1109/WCNC.2015.7127592
[27] Shrahili, M., & Kayid, M. (2023). Residual Tsallis entropy and record Values: some new insights. Symmetry, 15(11), 2040. https://doi.org/10.3390/sym15112040
[28] Singh, S. P., & Tiwari, S. (2023). A dual multimodal biometric authentication system based on WOA-ANN and SSA-DBN techniques. Sci, 5(1), 10. https://doi.org/10.3390/sci5010010
[29] Tian, D. (2023). Pricing principle via Tsallis relative entropy in incomplete markets. SIAM Journal on Financial Mathematics, 14(1), 250-278.https://doi.org/10.1137/22M1491710
[30] Tsallis, C. (1988). Possible generalizations of Boltzmann-Gibbs Statistics. Journal of Statistical Physics, 52(1), 479-487. https://doi.org/10.1007/BF01016429
[31] Venkatesan, R. C. (2007). Generalized Statistics Framework for Rate Distortion Theory with Bregman Divergences. arXiv preprint cond-mat/0701218. https://arxiv.org/abs/cond-mat/0701218
[32] Venkatesan, R. C., & Plastino, A. (2011). Scaled Bregman divergences in a Tsallis scenario. Physica A: Statistical Mechanics and Its Applications, 390(15), 2749-2758. https://doi.org/10.1016/j.physa.2011.03.009
[33] Vila, M., Bardera, A., Feixas, M., & Sbert, M. (2011). Tsallis mutual information for document classi cation. Entropy, 13(9), 1694-1707. https://doi.org/10.3390/e13091694
[34] Vilasini, V., & Colbeck, R. (2019). Analyzing causal structures using Tsallis entropies. Physical Review A, 100(6), 062108. https://doi.org/10.1103/PhysRevA.100.062108
[35] Yeung, R. W. (2008). Information Theory and Network Coding. Springer. https://doi.org/10.1007/978-0-387-79234-7
[36] Wyner, A. D. (1975). The wire tap channel. Bell System Technical Journal, 54(8), 1355-1387. https://doi.org/10.1002/j.1538-7305.1975.tb02040.x