Computational
Intelligence Applied
on Cryptology:
a Brief Review
Moisés Danziger
Marco Aurélio Amaral Henriques
CIBSI 2011 – Bucaramanga – Colombia
03/11/2011
Outline
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Introduction
Computational Intelligence (CI)
CI and cryptology
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Some applications
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Looking at the future
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Artificial Neural Network (ANN)
Evolutive Computation (EC)
Cellular Automata (CA)
DNA computing
Remembering the past
New possibilities
New vision
Conclusions
CI applied on cryptology
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Introduction
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Computational Intelligence (CI) has been applied successfully
on several areas of science.
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Generally, it is applied on hard problems as classifications,
optimizations, searches etc.
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Cryptology deals with two main problems
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Cryptography – looks for unbreakable cryptosystems;
Cryptanalysis – looks for methods to break cryptosystems.
This research is trying to answer questions like:
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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?
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Computational Intelligence (CI)
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Frequently, CI has some biological inspiration
 Simulates intelligent behaviors.
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Good aspects:
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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:
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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.
CI applied on cryptology
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Computational Intelligence Tools
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Evolutive Computation (EC)
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Inspired on natural evolution theory.
Copes very well with large search spaces.
Computational cost is the main drawback.
Some EC examples:
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Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony
Optimization (ACO), Artificial Immune Systems (AIS)
Artificial Neural Networks (ANN)
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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).
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Computational Intelligence Tools
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DNA Computing
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Inspired on DNA.
Based on massive parallelism and high storage capacity.
Is on embryo phase.
Cellular Automata
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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.
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Computational Intelligence and
Cryptology
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Applications can be divided in two classes:
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Applications in classical cryptographic systems
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Applications in modern cryptographic systems
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Most of the works fall into this class.
Only a few works (quite initial).
Applications X CI techniques
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Cryptography applications
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Cryptanalysis applications
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ANN, CA and DNA.
EC and DNA.
Hash function applications
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ANN and CA.
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ANN and Cryptology
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ANN is generally applied to development of
cryptosystems
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Most of the works included one chaotic layer to:
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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
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Evolutive Computation and Cryptology
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Most applications are in cryptanalysis.
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It was probably the first CI technique applied to cryptology.
Many works show good results compared to classical methods.
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Several search models were used together to find the bits of a
secret key (better exploration of the search space).
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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).
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By contrast, only a few works propose the application of this
technique on cryptography (mainly to construct stronger Sboxes).
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Evolutive Computation and Cryptology
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Ant Colony Optimization
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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.
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Evolutive Computation and Cryptology
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Ant Colony Optimization (ACO)
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Khan, Shahzad and Khan applied this approach to find the key in
the cryptanalysis of Four-Rounded DES.
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This is a binary model where the ants
need to choose 56 times between 0 and
1.
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.
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Cellular Automata and Cryptology
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CA is suitable to construct cryptosystems or part of them.
 Wolfram was the first to appoint the possibility of using CA in
cryptography.
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Probably, the best use for CA in cryptology is the
generation of random numbers.
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The choice of evolution rules was indicated by Bao as the
main challenge of CA in cryptology.
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New works are looking for new CA applications in
cryptography (see the work by Tardivo and Henriques in
this conference).
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DNA Computing and Cryptology
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This is the only technique with the same level of
applications in cryptography and cryptanalysis.
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Theoretical results showed that the super-parallelism
achieved by DNA Computing has great potential in
cryptology (works of Boneh et al. and Adleman).
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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.
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DNA Computing and Cryptology
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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.
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Looking at the Future
Remembering the Past
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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.
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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.
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Looking at the Future
New Possibilities
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We believe that exists potential in CI techniques for
cryptology.
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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.
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In cryptography:
 chaotic theory, lattice-based algorithms
In cryptanalysis:
 new types of attacks have been created (e. g. biclique on AES, latticebased algorithms, algebraic methods etc);
 the known attacks have been refined (e. g. differential approach and its
several sub-models).
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The Future of CI and Cryptology
New Vision
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According to our studies, there are new opportunities for
CI application in cryptology (hypothesis).
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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.
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New ideas will certainly emerge.
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The Future of CI and Cryptology
New Vision
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Generally, the works applied only one CI technique
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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.
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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.
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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.
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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.
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Our work is aimed at obtaining new good results from
cryptanalysis based on CI and catch again the attention of
cryptologists to this area.
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Acknowledgments:
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 Thank
you!
 Questions?
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[email protected]
 [email protected]
[email protected]
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