On the Application of Symbolic Regression and Genetic Programming for Cryptanalysis of Symmetric Encryption Algorithm

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F16%3APU123009" target="_blank" >RIV/00216305:26230/16:PU123009 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.fit.vutbr.cz/research/pubs/all.php?id=11144" target="_blank" >http://www.fit.vutbr.cz/research/pubs/all.php?id=11144</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/CCST.2016.7815720" target="_blank" >10.1109/CCST.2016.7815720</a>

Jazyk výsledku

angličtina

Název v původním jazyce

On the Application of Symbolic Regression and Genetic Programming for Cryptanalysis of Symmetric Encryption Algorithm

Popis výsledku v původním jazyce

The aim of the paper is to show different point of view on the problem of cryptanalysis of symmetric encryption algorithms. Our dissimilar approach, compared to the existing methods, lies in the use of the power of evolutionary principles which are in our cryptanalytic system utilized with utilization of the genetic programming (GP) in order to perform known plain-text attack (KPA). Our expected result is to find a program (i.e. function) that models the behavior of a symmetric encryption algorithm DES instantiated by specific key. If such a program would exist, then it could be possible to decipher new messages that have been encrypted by unknown secret key.The GP is employed as the basis of this work. GP is an evolutionary algorithm-based methodology inspired by biological evolution which is capable of creating computer programs solving a corresponding problem. The symbolic regression (SR) method is employed as the application of GP in practical problem. The SR method builds functions from predefined set of terminal blocks in the process of the GP evolution; and these functions approximate a list of input values pairs. The evolution of GP is controlled by a fitness function which evaluates the goal of a corresponding problem. The Hamming distance, a difference between a current individual value and a reference one, is chosen as the fitness function for our cryptanalysis problem.The functionality of our GP solution is verified by validation tests composed of polynomials of various degrees. Control statements IF and FOR are verified by computation of factorial function.The set of preconditions is determined in the experimenting stage: estimation of the worst fitness value; finding the most suitable GP parameters; transformation of KPA with elimination of an initial and final permutations; evolution of the best individual; influence of the number of encryption rounds; the cardinality of a training set; and the model generalization.The results

Název v anglickém jazyce

On the Application of Symbolic Regression and Genetic Programming for Cryptanalysis of Symmetric Encryption Algorithm

Popis výsledku anglicky

The aim of the paper is to show different point of view on the problem of cryptanalysis of symmetric encryption algorithms. Our dissimilar approach, compared to the existing methods, lies in the use of the power of evolutionary principles which are in our cryptanalytic system utilized with utilization of the genetic programming (GP) in order to perform known plain-text attack (KPA). Our expected result is to find a program (i.e. function) that models the behavior of a symmetric encryption algorithm DES instantiated by specific key. If such a program would exist, then it could be possible to decipher new messages that have been encrypted by unknown secret key.The GP is employed as the basis of this work. GP is an evolutionary algorithm-based methodology inspired by biological evolution which is capable of creating computer programs solving a corresponding problem. The symbolic regression (SR) method is employed as the application of GP in practical problem. The SR method builds functions from predefined set of terminal blocks in the process of the GP evolution; and these functions approximate a list of input values pairs. The evolution of GP is controlled by a fitness function which evaluates the goal of a corresponding problem. The Hamming distance, a difference between a current individual value and a reference one, is chosen as the fitness function for our cryptanalysis problem.The functionality of our GP solution is verified by validation tests composed of polynomials of various degrees. Control statements IF and FOR are verified by computation of factorial function.The set of preconditions is determined in the experimenting stage: estimation of the worst fitness value; finding the most suitable GP parameters; transformation of KPA with elimination of an initial and final permutations; evolution of the best individual; influence of the number of encryption rounds; the cardinality of a training set; and the model generalization.The results

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of 2016 IEEE International Carnahan Conference on Security Technology

ISBN

978-1-5090-1072-1

ISSN

—

e-ISSN

—

Počet stran výsledku

8

Strana od-do

1-8

Název nakladatele

Institute of Electrical and Electronics Engineers

Místo vydání

Orlando, Fl

Místo konání akce

Orlando, Florida

Datum konání akce

24. 10. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000405490700047