Recover plaintext attack to block ciphers

Similar documents
Foundations of Arithmetic

The Multiple Classical Linear Regression Model (CLRM): Specification and Assumptions. 1. Introduction

3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X

The Order Relation and Trace Inequalities for. Hermitian Operators

NP-Completeness : Proofs

Anti-van der Waerden numbers of 3-term arithmetic progressions.

Linear Approximation with Regularization and Moving Least Squares

THE CHINESE REMAINDER THEOREM. We should thank the Chinese for their wonderful remainder theorem. Glenn Stevens

A Simple Research of Divisor Graphs

Remarks on the Properties of a Quasi-Fibonacci-like Polynomial Sequence

Discussion 11 Summary 11/20/2018

First day August 1, Problems and Solutions

FACTORIZATION IN KRULL MONOIDS WITH INFINITE CLASS GROUP

An improved lower-bound on the counterfeit coins problem

Attacks on RSA The Rabin Cryptosystem Semantic Security of RSA Cryptology, Tuesday, February 27th, 2007 Nils Andersen. Complexity Theoretic Reduction

Chapter 13: Multiple Regression

Graph Reconstruction by Permutations

Maximizing the number of nonnegative subsets

Beyond Zudilin s Conjectured q-analog of Schmidt s problem

Case Study of Markov Chains Ray-Knight Compactification

Société de Calcul Mathématique SA

Color Rendering Uncertainty

ANSWERS. Problem 1. and the moment generating function (mgf) by. defined for any real t. Use this to show that E( U) var( U)

Section 3.6 Complex Zeros

arxiv: v1 [math.co] 1 Mar 2014

HMMT February 2016 February 20, 2016

Dr. Ing. J. H. (Jo) Walling Consultant Cables Standards Machinery

FREQUENCY DISTRIBUTIONS Page 1 of The idea of a frequency distribution for sets of observations will be introduced,

DONALD M. DAVIS. 1. Main result

Improved Integral Cryptanalysis of FOX Block Cipher 1

SL n (F ) Equals its Own Derived Group

CHALMERS GÖTEBORGS UNIVERSITET. TDA352 (Chalmers) - DIT250 (GU) 12 Jan. 2017, 14:00-18:00

arxiv:quant-ph/ Jul 2002

Linear Regression Analysis: Terminology and Notation

A new Approach for Solving Linear Ordinary Differential Equations

Pulse Coded Modulation

Economics 101. Lecture 4 - Equilibrium and Efficiency

Module 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur

COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS

Case A. P k = Ni ( 2L i k 1 ) + (# big cells) 10d 2 P k.

An (almost) unbiased estimator for the S-Gini index

x = , so that calculated

A combinatorial problem associated with nonograms

Statistical Foundations of Pattern Recognition

Errors in Nobel Prize for Physics (7) Improper Schrodinger Equation and Dirac Equation

Econ107 Applied Econometrics Topic 3: Classical Model (Studenmund, Chapter 4)

Lecture 20: Lift and Project, SDP Duality. Today we will study the Lift and Project method. Then we will prove the SDP duality theorem.

Supplementary material: Margin based PU Learning. Matrix Concentration Inequalities

Complete subgraphs in multipartite graphs

2.3 Nilpotent endomorphisms

Module 2. Random Processes. Version 2 ECE IIT, Kharagpur

2 More examples with details

Difference Equations

Differential Cryptanalysis of Nimbus

EPR Paradox and the Physical Meaning of an Experiment in Quantum Mechanics. Vesselin C. Noninski

COMPLEX NUMBERS AND QUADRATIC EQUATIONS

The Key-Dependent Attack on Block Ciphers

Negative Binomial Regression

(1 ) (1 ) 0 (1 ) (1 ) 0

STEINHAUS PROPERTY IN BANACH LATTICES

Games of Threats. Elon Kohlberg Abraham Neyman. Working Paper

Caps and Colouring Steiner Triple Systems

The internal structure of natural numbers and one method for the definition of large prime numbers

EXPANSIVE MAPPINGS. by W. R. Utz

1. Estimation, Approximation and Errors Percentages Polynomials and Formulas Identities and Factorization 52

THE CHVÁTAL-ERDŐS CONDITION AND 2-FACTORS WITH A SPECIFIED NUMBER OF COMPONENTS

DISCRIMINANTS AND RAMIFIED PRIMES. 1. Introduction A prime number p is said to be ramified in a number field K if the prime ideal factorization

MMA and GCMMA two methods for nonlinear optimization

A new construction of 3-separable matrices via an improved decoding of Macula s construction

On quasiperfect numbers

k(k 1)(k 2)(p 2) 6(p d.

STAT 3008 Applied Regression Analysis

CHAPTER 14 GENERAL PERTURBATION THEORY

Lecture 4: Universal Hash Functions/Streaming Cont d

arxiv: v2 [cs.cr] 29 Sep 2016

A be a probability space. A random vector

Self-complementing permutations of k-uniform hypergraphs

Some Consequences. Example of Extended Euclidean Algorithm. The Fundamental Theorem of Arithmetic, II. Characterizing the GCD and LCM

G /G Advanced Cryptography 12/9/2009. Lecture 14

On cyclic of Steiner system (v); V=2,3,5,7,11,13

Math 426: Probability MWF 1pm, Gasson 310 Homework 4 Selected Solutions

Power law and dimension of the maximum value for belief distribution with the max Deng entropy

Copyright 2017 by Taylor Enterprises, Inc., All Rights Reserved. Adjusted Control Limits for U Charts. Dr. Wayne A. Taylor

Exhaustive Search for the Binary Sequences of Length 2047 and 4095 with Ideal Autocorrelation

5 The Rational Canonical Form

Christian Aebi Collège Calvin, Geneva, Switzerland

Affine transformations and convexity

Composite Hypotheses testing

Topics in Probability Theory and Stochastic Processes Steven R. Dunbar. Classes of States and Stationary Distributions

Notes on Frequency Estimation in Data Streams

On the correction of the h-index for career length

A Novel Feistel Cipher Involving a Bunch of Keys supplemented with Modular Arithmetic Addition

Smarandache-Zero Divisors in Group Rings

The optimal delay of the second test is therefore approximately 210 hours earlier than =2.

Hyper-Sums of Powers of Integers and the Akiyama-Tanigawa Matrix

8.6 The Complex Number System

Sampling Theory MODULE VII LECTURE - 23 VARYING PROBABILITY SAMPLING

Restricted divisor sums

Asymptotics of the Solution of a Boundary Value. Problem for One-Characteristic Differential. Equation Degenerating into a Parabolic Equation

Geometry of Müntz Spaces

Transcription:

Recover plantext attac to bloc cphers L An-Png Bejng 100085, P.R.Chna apl0001@sna.com Abstract In ths paper, we wll present an estmaton for the upper-bound of the amount of 16-bytes plantexts for Englsh texts, that s not suffcent large mae clear that the bloc cphers wth bloc length no more than 16-bytes wll be subject to recover plantext attacs n the occasons of plantext -nown or plantext-chosen attacs. Keywords: bloc cpher, recover-plantext attac, brthday paradox,

1. Introducton For the securty of bloc cphers there are many researches, whch may be found n most of textboos and papers n cryptography, refer to see [1]. It s nown that bloc cphers have a characterstc that t encrypt plantexts n blocs wth a regular encrypton scheme, so, plantexts are 1-1 related to the cphertexts n blocs for a secret ey. It s not dffcult to now that these bloc cphers wll be easy subjected to recover plantext attac f the amount of bloc plantexts s not suffcent large. Suppose that the amount of all possble plantexts blocs s no more than 2 m, /2 2 an adversary has a dctonary of the bloc-pars (cphertext, plantext wth sze about 2 m +, then /2 he wll recover a bloc plantext whle collect 2 m blocs of cphertexts wth hgh successful probablty by the general brthday paradox. In most of the currently used bloc cphers, the output szes, that s, the lengths of blocs are equal to, or smaller than 16 bytes. In ths paper, we wll show that n the case of Englsh text the number of 16-bytes plantexts s less than 2 56, so the bloc cphers wth output sze of 16 bytes wll be vulnerable to recover plantext attacs n the occasons of plantext-nown or plantext-chosen attacs. In the rest of ths secton, we gve some conceptons used n ths paper. Denoted by Q the vocabulary for the plantexts, and suppose that the sze Q = N. For a word w Q,, denote by w the length,.e., the number of the letters contaned n the word w. An Englsh phase or a plantext blocα s called of -terms f t conssts of words or parts of words, There are four possble expressons for the -terms plantext blocs word1 word2 word (1.1 word1 word2 word (1.2 word1 word2 word (1.3 word1 word2 word (1.4 Where word s the th word ofα, and symbol represents a blan space. It should be mentoned that there are the possbltes that word1 n (1.1, (1.2 and word n (1.1, (1.3 are not complete Englsh words but only parts. Besdes, possbly there are exsted some blocs contan some punctuaton mars such as ',' or '.' or ;, whch wll be agreed to be a character rather than a term, except the specal case that word1 n (1.1 or (1.2 s just a punctuaton mar. We wll only tae the frequently used three punctuaton mars ',', '.' and ; nto the consderaton n the followng dscusson. For the smplcty, n ths paper, t s assumed that the words n the vocabulary Q are consst of Englsh letters, no nclude specal characters such as @, #, etc, and Araban numbers and abbrevatons. 2. The estmatons of the amount of plantext blocs

In ths secton, we wll present a estmaton for the amount of 16-bytes plantexts. Proposton 1. Suppose that Q s a vocabulary consst of Englsh words, ncludng no specal characters and Araban numbers, and the sze Q 60000. Let F be the set of all possble 16-bytes blocs of Englsh texts over Q. Denoted by words, 1 16, f the dstrbuton of Q satsfy that Q the subset of Q consst of -letters where μ s a constant, μ = 2, then Q, 1 16, (2.1 1 μ C16 56 2. F (2.2 Proof. Denoted by F, F and F the subsets of F consst of 16-bytes plantexts wth that the frst letter s a mnuscule one, a captal one and a punctuaton respectvely. We wll see that F possess a man part n the amount. For an postve nteger, 1 8, Let F be the subsets of F consst of -terms blocs, and (1 F, F, F (2 (3 and (4 F be the subsets of F wth (1 the expresson forms (1.1, (1.2, (1.3 and (1.4 respectvely. We wll frstly calculate F. Suppose that ζ F, s a -terms bloc, ζ = ( (. (2.3 word1 word2 word Denoted by word = c, obvously, c 1, 1, and δ = 1, 0, 0, 1, for 1 c = 16 + δ, (2.4 ζ F, F, F, F respectvely. At frst we are restrcted n the case (1 (2 (3 (4 (1 ζ F. We call ζ s of 1 2 ( c, c,..., c -type, and let F be the set of ( c1, c2,, c ( c, c,..., c -type blocs. For any -subset I of{1, 2,, }, denoted by 1 2 F ( I ( c1, c2,, c be the subset of F consst of the blocs wth punctuaton mars followng the words wth ( c1, c2,, c ndces n I. In the next, we calculate the szes F, and we at frst calculate ( ( c1, c2,, c F. (0 ( c1, c2,, c

c1 c Denoted by x = mn(26, N, y = mn(26, N, by (2.1, t has 1 (0 c 1 ( c1, c2,, c x y μ C16 = 2 F ( c1 1 c 1 2 c 1 16 16 μ 16 = 1 ( x/ C ( y/ C C. (2.5 By the basc combnatorcs, we now that for any postve nteger s, t has c1 + + c = s = 1 C = C c s 16 16. (2.6 And for the assumpton N 60000, t s easy to now that mn{ 26 / C, N / C } 26 / C 147, c1 c1 1 c1 1 3 2 16 16 16 mn{ 26 / C, N / C } 26 / C 147. So, wth (2.5, (2.6, (2.7 and (2.4, we have c1 + + c = 17 c c 1 c 1 3 2 16 16 16 (0 2 2 17 2 ( c1, c2,, c μ C 16 (2.7 F (147 ( (2.8 ( I To get an estmaton for F, > 0, have to change 16 nto 16 n the equaton (2.4, ( c1, c2,, c and notce that there are C 3 -subsets I s, so we have Hence, I c1 + + c = 17 F (147 C 3 μ C (1 2 2 17 2 16 0 2 (147 / μ C 3 μ 0 F (147 3 (2.9 ( I 2 2 17 2 ( c1, c2,, c C μ C 16 17 2 (16 (17 2 (17 2+ 1 (17 2! (16 2 17 2 (147 / μ μ e 16 (17 2 (17 2+ 1 C 3 2 π (17 2 17 2 0 (16 17 2 2 ( 147 / μ μ e 16 3 (17 2 1 +, 2 π (17 2 17 2 16 where Strlng s formula has been appled. (2.10 The estmatons for (2 F, (3 F (4 and F are smlar to the one above, but notce that that word1 n (1,2, (1.4 and word n (1.3, (1.4 are complete Englsh word rather than a part, and now δ = 0 n the equaton (2.5 for (3 F, F and δ = 1for (2 (4 F. Thus, we has

16 2 ( (147 / μ μ e 16 3 (16 2 F 1 +, = 2,3. 2 π (16 2 16 2 16 15 2 (4 μ e 16 3 (15 2 F 1 +. 2 π (15 2 15 2 16 (2.11 So, (1 (2 (3 (4 F ( F + F + F + F 1 8 2 17 2 (147 / μ μ e 16 3 (17 2 1+ 1 8 2 π (17 2 17 2 16 16 2 (147 / μ μ e 16 3 (16 2 + 2 1+ 1 < 8 2 π (16 2 16 2 16 + 1 < 8 15 2 μ e 16 3 (15 2 2 6 1 + + (147 μ 2 π ( 15 2 15 2 16 (2.12 For μ = 2, t has 3.73 10 16 F. (2.13 In respect to the estmaton of F, we now that the frst letter of a sentence s captal or mnuscule s determned by the punctuaton ahead t, and that the frst letter of word1 n (1.1 or (1.2 s captal one means word1 s a complete Englsh word rather than a part. Denoted by ( F, 1 4, the subsets of F consst of the plantext blocs wth type as n (1.1, (1.2, (1.3 and (1.4 respectvely, that s, ( ( F = F, = 1,2,3,4. Then, t has μ 4.2 10 147 (3 (4 14 F F + F + F. (2.14 For the estmaton of F, provded to substtute 16 by 16 1 n the estmaton of (3 F and (4 F, and wth multple 3 for there are three punctuaton mars. So 4 10 13 F (2.15 Hence, we have + + 3.8 10 2 16 56 F F F F. Remar 1. It s lely the nequaton (2.1 s true for the dstrbuton of Englsh words, but we

have not checed n total, so we have taen t as a condton, so that the constant μ may be modfed accordng to the actual cases. Remar 2. Moreover, for a -letters word w, and a postve nteger,, we call the segment formed by the frst letters of w as the -prefx of w, smlarly, the segment formed by the last letters of w as the -suffx of w. Denoted by [] Q and [] Q the sets of all the dstnct -prefx s and -suffx s of the words nq respectvely. Suppose that and denoted by Q = λ C, Q = λ C, (2.16 ( max{ λ, λ } [] ( 1 1 16 [ ] 16 λ =. In the proof above we nown that λ 147 guess that for the ordnary vocabulary there may be λ = 26, f so, then 15 51 1.8 10 2., however, we F (2.17 It s easy to now that the conjecture s true for = 1, and > 5, so the rest to be verfed are the cases 2 5. 3. Concluson For the smplcty of dscusson, we have excluded Araban numbers and some specal characters such as @, $, etc, and some specal punctuatons such as!,?, etc, though they occasonally appear n the Englsh texts, but a lttle. So, the estmaton above may be vewed as the one for the frequently appeared ones. The calculatons n the paper s nearly n combnatorcs, no consderatons on the Englsh grammar, logc and semantcs, so t s very lely that the actual amount of plantext blocs wll be much smaller then the one presented n Proposton 1. In fact, our frst dea s from the consderaton n Englsh grammar, but whch s somewhat trflng. The result presented ndcate that the bloc cphers wth 16-bytes bloc length such as AES wll be subject to recover plantext attacs when appled to encrypt Englsh texts n the occasons of plantext-nown or plantext-chosen attacs. From the dscusson above, we have seen that the amount of plantext blocs not only depend the sze of bloc length but also the dstrbuton of the words n languages. References [1] A. Menezes, P. van Oorschot, S. Vanstone, Handboo of Appled Cryptograpgy, CRC Press,1997.