computational intelligence applied on cryptology: a brief ... · cellular automata and cryptology...

Computational

Intelligence Applied

on Cryptology:

a Brief Review

Moisés Danziger

Marco Aurélio Amaral Henriques

CIBSI 2011 – Bucaramanga – Colombia

03/11/2011

Outline

Introduction

Computational Intelligence (CI)

CI and cryptology

Some applications

Artificial Neural Network (ANN)

Evolutive Computation (EC)

Cellular Automata (CA)

DNA computing

Looking at the future

Remembering the past

New possibilities

New vision

Conclusions

CI applied on cryptology 2

Introduction


Computational Intelligence (CI) has been applied successfully on several areas of science.

Generally, it is applied on hard problems as classifications, optimizations, searches etc.

Cryptology deals with two main problems Cryptography – looks for unbreakable cryptosystems;

Cryptanalysis – looks for methods to break cryptosystems.

This research is trying to answer questions like: Is it possible to use CI to solve cryptology problems?

What is the cost of applying CI to this area?

What are the future perspectives?

Computational Intelligence (CI)


Frequently, CI has some biological inspiration

Simulates intelligent behaviors.

Good aspects:

Can get approximate results quickly, which can be used as an input to other deterministic techniques decreasing their complexity.

Can solve many kinds of problems.

Can work together with other CI techniques (hybrid approach) .

Bad aspects:

It is necessary to guide the main process with some heuristic.

Convergence is not assured.

It is difficulty to map the problems to CI models.

Computational Intelligence Tools


Evolutive Computation (EC) Inspired on natural evolution theory.

Copes very well with large search spaces.

Computational cost is the main drawback.

Some EC examples: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony

Optimization (ACO), Artificial Immune Systems (AIS)

Artificial Neural Networks (ANN) Inspired on neurons (nervous system cells).

Connections are the base of this paradigm.

Copes very well with classification problems.

It is difficult to obtain information about how the output values were produced (black box concept).

Computational Intelligence Tools


DNA Computing Inspired on DNA.

Based on massive parallelism and high storage capacity.

Is on embryo phase.

Cellular Automata Inspired on biological cells and their evolution.

A discrete model that uses a group of simple cells.

Works with simple deterministic rules to create new cell generations (states).

Easy implementation in hardware.

Defining correct evolution rules is a difficult and important task.

Computational Intelligence and

Cryptology


Applications can be divided in two classes:

Applications in classical cryptographic systems

Most of the works fall into this class.

Applications in modern cryptographic systems Only a few works (quite initial).

Applications X CI techniques

Cryptography applications ANN, CA and DNA.

Cryptanalysis applications EC and DNA.

Hash function applications ANN and CA.

ANN is generally applied to development of

cryptosystems

Most of the works included one chaotic layer to:

increase the hardness: attack needs to break the chaotic system first

provide data diffusion

The linear neuron layer provides data confusion

Example (Shiguo Lian): Neural block cipher

ANN and Cryptology


Evolutive Computation and Cryptology


Most applications are in cryptanalysis. It was probably the first CI technique applied to cryptology.

Many works show good results compared to classical methods.

Several search models were used together to find the bits of a secret key (better exploration of the search space).

Some works were able to find the input parameters to other CI techniques (e.g. finding appropriate differences between plaintext and ciphertext pairs to decrease the time of differential attack).

By contrast, only a few works propose the application of this technique on cryptography (mainly to construct stronger S-boxes).



Ant Colony Optimization

This technique is inspired on ant behaviour (mainly in its highest capacity: the

search for food).

The ants are able to find the shortest path between the nest and the food even if

one obstacle exists in the path.

55 56



Ant Colony Optimization (ACO)

Khan, Shahzad and Khan applied this approach to find the key in

the cryptanalysis of Four-Rounded DES.

An ant completes its path by making

decisions using heuristic based on

pheromone found on the way. Each

completed path represents a possible trial

key to the problem.

This is a binary model where the ants

need to choose 56 times between 0 and

1.

Cellular Automata and Cryptology


CA is suitable to construct cryptosystems or part of them. Wolfram was the first to appoint the possibility of using CA in

cryptography.

Probably, the best use for CA in cryptology is the generation of random numbers.

The choice of evolution rules was indicated by Bao as the main challenge of CA in cryptology.

New works are looking for new CA applications in cryptography (see the work by Tardivo and Henriques in this conference).

DNA Computing and Cryptology


This is the only technique with the same level of

applications in cryptography and cryptanalysis.

Theoretical results showed that the super-parallelism

achieved by DNA Computing has great potential in

cryptology (works of Boneh et al. and Adleman).

Some researchers identified potential to apply DNA on

One-Time Pad (OTP) schema using the high storage

capacity (one trillion CDs ≈ one DNA gram) as showed

by Hirabayashi et al.

DNA Computing and Cryptology

Hirabayashi et al schema:


Secret key generation using the physical

random process of DNA assembly.

Random key generation is obtained by

connection of each key tile, which has a

value of zero or one with probability = 0.5.

Looking at the Future

Remembering the Past


We can define the 1990s as the best time for CI applications on cryptology.

Many works were developed using almost all known CI techniques.

Good results obtained with classical cryptosystems.

However, in the last 10 years, the number of CI applications in cryptology decreased because of:

Few substantial results in modern ciphers;

Difficulties in representing the problem in terms of CI;

The poor interaction between researchers of cryptology and CI.

Looking at the Future

New Possibilities


We believe that exists potential in CI techniques for cryptology. CI techniques have been improved and new aspects have been

incorporated into them.

There is more computational power available (generally, the CI tools need a lot of it).

New concepts and ideas emerged in cryptology and they can be used with CI tools. In cryptography:

chaotic theory, lattice-based algorithms

In cryptanalysis:

new types of attacks have been created (e. g. biclique on AES, lattice-based algorithms, algebraic methods etc);

the known attacks have been refined (e. g. differential approach and its several sub-models).

The Future of CI and Cryptology

New Vision


According to our studies, there are new opportunities for

CI application in cryptology (hypothesis).

We believe that CI techniques can help create more robust

ciphers.

We can use CI techniques to improve parts of attacks done by

other techniques (most of the works used CI in the entire attack

process, but CI techniques normally can be more efficient if used

only in some parts of the attack).

Problems with mapping and representation of CI techniques

can get a new perspective as more researchers start to pay

attention to this kind of problems.

New ideas will certainly emerge.

The Future of CI and Cryptology

New Vision


Generally, the works applied only one CI technique Hybrid methods, combining two or more techniques, could

be explored further to deal with the complexity involved in cryptology.

CI could be used together with new kinds of mathematical and statistical attacks against block ciphers, as AES and SERPENT, to improve these attacks and make them more efficient. Some ANNs are known as universal approximation tools

and they could be to used to approximate results of some crypto functions decreasing the complexity of algebraic attacks.

Conclusions


CI tools have been used successfully in many areas. However, due to the mapping difficulties and the unsatisfactory results found when they are applied to modern ciphers, the cryptology community moved away from CI techniques.

Based on new discovers in cryptology, mainly in cryptanalysis (new attacks on AES and hash functions, for example), and on the evolution of CI techniques, we believe that there are good opportunities to explore in this frontier.

Our work is aimed at obtaining new good results from cryptanalysis based on CI and catch again the attention of cryptologists to this area.

Acknowledgments:


Thank you!

Questions?

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