Abstract
Cryptographic algorithms are composed of many complex mathematical functions. When analyzing the complexity of these algorithms, one fixes priory the overall complexity of the algorithm as the complexity of the most dominating operations for a group of operations. Generally, it is the count of this operation which determines the complexity of the algorithm in case of compounding operations. We have instead used the weight factor to determine the complexity of an algorithm with many operating functions working simultaneously and have taken time of the operation as a measure of the weight factor. We statistically analyze the two most used operations in RSA, namely “power” and “mod,” through a method of revised difference to compare whether these are statistically similar or dissimilar. We have also calculated the empirical computational complexity of these two operations through the fundamental theorem of finite differences to verify whether these operations are statistically dissimilar and if so then which of the two is dominant. We have also analyzed empirically the complexity of each of the four sub-steps involved in the encryption and decryption of AES-128, to determine which operation dominates the most and consumes most of the time in an overall run time of AES-128.
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References
Aho A, Hopcroft JE, Ullman JD (1975) The design and analysis of algorithms. Addison-Wesley, Boston
Announcing the ADVANCED ENCRYPTION STANDARD (AES) (2012) Federal Information Processing Standards Publication 197. United States National Institute of Standards and Technology (NIST). November 26, 2001. Retrieved October 2, 2012
Bogdanov A, Chang D, Ghosh M, Sanadhya SK (2015) Bicliques with minimal data and time complexity for AES. In: Lee J, Kim J (eds) Information security and cryptology—ICISC 2014. ICISC 2014. Lecture notes in computer science, vol 8949. Springer, Cham. https://doi.org/10.1007/978-3-319-15943-0_10
Chakraborty S (2007) A simple empirical formula for categorizing computing operations. Appl Math Comput 189:326–340. https://doi.org/10.1016/j.amc.2006.11.097
Chakraborty S, Chaudhary P (2000) A statistical analysis of an algorithm’s complexity. Appl Math Lett 13:121–126
Chakraborty S, Sourabh SK (2007) On why an algorithmic time complexity measure can be system invariant rather than system independent. Appl Math Comput 190(1):195–204
Chakraborty S, Sourabh SK, Bose M, Sushant K (2007) Replacement sort revisited: The ‘“gold standard”’ unearthed! Appl Math Comput 189:384–394
Chakraborty S, Sundararajan KK (2007) Winograd’s algorithm statistically revisited: It pays to weigh than to count! Appl Math Comput 190:15–20
Chakraborty S, Sourabh SK (2010) A computer experiment oriented approach to algorithmic complexity. LAP LAMBERT Academic
Cormen TH, Leiserson CE, Rivest RL, Stein C (2009) Introduction to algorithms, 3rd edn. MIT Press, New York
Cotta C, Moscato P (2004) A mixed evolutionary-statistical analysis of an algorithm’s complexity. Appl Math Lett. https://doi.org/10.1016/S0893-9659(02)00142-8
Daemen J, Rijmen V (2003) AES proposal: Rijndael. National Institute of Standards and Technology, p 1
Diffie W, Landau S (2007) Privacy on the line. The politics of wiretapping and encryption. MIT Press, Cambridge
Dutta S, Sinha S (2020) An improved pig latin algorithm for lightweight cryptography. https://doi.org/10.1007/978-981-13-8222-2_28.
Forouzan BA, Mukhopadhyay D (2010) Cryptography and network security, 2nd edn. Tata McGraw-Hill, New York
Goldsmith SF, Aiken AS, Wilkerson DS (2007) Measuring empirical computational complexity. ACM, New York
Greene DH, Knuth DE (1991) Mathematics for the analysis of algorithms, 3rd edn. Birkhäuser, Boston
Knuth DE (1973) Fundamental algorithms, vol 1. Addison-Wesley, Boston
Coffin M, Saltzman MJ (2000) Statistical analysis of computational tests of algorithms and heuristics. INFORMS J Comput 12(1):24–44. https://doi.org/10.1287/ijoc.12.1.24.11899
Pranav P, Chakraborty S, Dutta S (2020) A new cipher system using semi-natural composition in Indian raga. Soft Comput 24:1529–1537. https://doi.org/10.1007/s00500-019-03983-8
Pranav P, Dutta S, Chakraborty S (2021) An involution function-based symmetric stream cipher. In: Nath V, Mandal JK (eds) Proceedings of the fourth international conference on microelectronics, computing and communication systems. Lecture notes in electrical engineering, vol 673. Springer, Singapore. https://doi.org/10.1007/978-981-15-5546-6_5
Rothe J (2005) Complexity theory and cryptology. Springer, Berlin
Schoor A (1982) Fast algorithm for sparse matrix multiplication. Inf Process Lett 15(2):87–89
Singh N, Chakraborty S, Mallick D (2014) A new look at worst case complexity: a statistical approach. Int J Anal 2014:1–10. https://doi.org/10.1155/2014/840432
Singh N, Chakraborty S, Mallick D (2019) Complexity verification through design and analysis of computer experiments. Int J Comput Complex Intell Algorithms 1:178. https://doi.org/10.1504/IJCCIA.2019.103729
Singh NK, Chakraborty S (2011) Partition sort and its empirical analysis. In: Das V.V., Thankachan N. (eds) Computational intelligence and information technology. CIIT 2011. Communications in computer and information science, vol 250. Springer, Berlin. https://doi.org/10.1007/978-3-642-25734-6_51
Singh N, Chakraborty S, Mallick DK (2013) A statistical peek into average case complexity. ArXiv, abs/1312.4802
Stallings W (2005) Cryptography and network security, 4th edn. Pearson, London
Stallings W (2009) Network and Internetwork Security: Principles and Practice, 5th edn. Prentice Hall, Hoboken
Talbot J, Welsh D (2006) Complexity and Cryptography. Cambridge University Press, Cambridge
Tanenbaum A (2001) Modern operating systems. Prentice Hall of India, Hoboken
The Advanced Encryption Standard (Rijndael) (2010) http://www.quadibloc.com/crypto/co040401.htmAccessed March 10, 2019
Trenholme S "S-box." AES (2010) http://www.samiam.org/s-box.html. Accessed 10 March 2019
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Pranav, P., Dutta, S. & Chakraborty, S. Empirical and statistical comparison of intermediate steps of AES-128 and RSA in terms of time consumption. Soft Comput 25, 13127–13145 (2021). https://doi.org/10.1007/s00500-021-06085-6
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DOI: https://doi.org/10.1007/s00500-021-06085-6