Computational Intelligence Applied on Cryptology: a Brief Review

Transcription

1 Computational Intelligence Applied on Cryptology: a Brief Review Moisés Danziger Marco Aurélio Amaral Henriques CIBSI 2011 Bucaramanga Colombia 03/11/2011

2 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

3 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? CI applied on cryptology 3

4 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. CI applied on cryptology 4

5 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). CI applied on cryptology 5

6 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. CI applied on cryptology 6

7 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. CI applied on cryptology 7

8 ANN and Cryptology 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 CI applied on cryptology 8

9 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). CI applied on cryptology 9

10 Evolutive Computation and Cryptology 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. CI applied on cryptology 10

11 Evolutive Computation and Cryptology Ant Colony Optimization (ACO) Khan, Shahzad and Khan applied this approach to find the key in the cryptanalysis of Four-Rounded DES 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. CI applied on cryptology 11

12 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). CI applied on cryptology 12

13 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. CI applied on cryptology 13

14 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. CI applied on cryptology 14

15 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. CI applied on cryptology 15

16 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, latticebased algorithms, algebraic methods etc); the known attacks have been refined (e. g. differential approach and its several sub-models). CI applied on cryptology 16

17 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. CI applied on cryptology 17

18 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. CI applied on cryptology 18

19 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. CI applied on cryptology 19

20 Acknowledgments: CI applied on cryptology 20

21 Thank you! Questions? CI applied on cryptology 21