Genetic evolution and equivalence of some complex systems: fractals, cellular automata and lindenmayer systems

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid. Escuela Politécnica Superior, Departamento de Ingeniería informática.26-04-200

Grammatical evolution to design fractal curves with a given dimension

Original paper in http://ieeexplore.ieee.org/Lindenmayer grammars have frequently been applied to represent fractal curves. In this work, the ideas behind grammar evolution are used to automatically generate and evolve Lindenmayer grammars which represent fractal curves with a fractal dimension that approximates a predefined required value. For many dimensions, this is a nontrivial task to be performed manually. The procedure we propose closely parallels biological evolution because it acts through three different levels: a genotype (a vector of integers), a protein-like intermediate level (the Lindenmayer grammar), and a phenotype (the fractal curve). Variation acts at the genotype level, while selection is performed at the phenotype level (by comparing the dimensions of the fractal curves to the desired value).This paper has been sponsored by the Spanish Ministry of Science and Technology (MCYT), project numbers TIC2002-01948 and TIC2001-0685-C02-01

Cellular automata equivalent to D0L system

This paper describes an algorithm for the construction of a certain one-dimensional cellular automaton equivalent to a given D0L system. A cellular automaton is considered equivalent to an L-system if both generates the same words in the same order. Our cellular automata produce the same words and in the same order as the given D0L system for a finite number of derivations. There is no constraint to the D0L system considered, so the method is a general algorithm and can be used as a proof for an equivalence theorem

Audio scrambling technique based on cellular automata

The final publication is available at Springer via http://dx.doi.org/10.1007/s11042-012-1306-7Scrambling is a process that has proved to be very effective in increasing the quality of data hiding, watermarking, and encryption applications. Cellular automata are used in diverse and numerous applications because of their ability to obtain complex global behavior from simple and localized rules. In this paper we apply cellular automata in the field of audio scrambling because of the potential it holds in breaking the correlation between audio samples effectively. We also analyze the effect of using different cellular automata types on audio scrambling and we test different cellular automata rules with different Lambda values. The scrambling degree is measured and the relation between the robustness and the scrambling degree obtained is studied. Experimental results show that the proposed technique is robust to data loss attack where 1/3 of the data is lost and that the algorithm can be applied to music and speech files of different sizes.This work is partially supported by the Spanish Ministry of Science and Innovation under coordinated research projects TIN2011-28260-C03-00 and TIN2011-28260-C03-02 and by the Comunidad Autónoma de Madrid under research project e-madrid S2009/TIC-165

Blind audio watermarking technique based on two dimensional cellular automata

In this paper we propose a new method of digital audio watermarking based on two dimensional cellular automata; the method increases the dimension of the audio and uses cellular automata in generating the key of watermark embedding. The watermarking method is blind, and does not require the original host audio or any of its features to extract the watermark; the watermark can be easily extracted using the right key. The experimental results show that the watermarks are imperceptible; and show a high similarity between the original and the watermarked audio. Cosine similarity and peak signal-to-noise ratio were used to measure the similarity between the original audio and the watermarked audio

Computer-Generated music using grammatical evolution

This is an electronic version of the paper presented at the Middle Eastern Simulation Multiconference (MESM) held in Amman (Jordan) on 2008This paper proposes a new musical notation with Lindenmayer grammars, and describes the use of grammar evolution for the automatic generation of music expressed in this notation, with the normalized compression distance as the fitness function. The computer music generated tries to reproduce the style of a selected pre-existent piece of music. In spite of the simplicity of the algorithm, the procedure obtains interesting results.This work has been partially sponsored by the Spanish Ministry of Science and Technology (MCYT), project number TIC2002-01948

Network intrusion detection using genetic algorithm to find best DNA signature

Bioinformatics is part of computer science that joins between computer programming and molecular biology. DNA consists of long sequence of nucleotides which formulates the genome. Our method is to generate normal signature sequence and alignment threshold value from processing the system training data and encode observed network connection into corresponding DNA nucleotides sequence, then to align the signature sequence with observed sequence to find similarity degree value and decide whether the connection is attack or normal. Number of DNA sequences makes up each population, and then new generations are produced to select the Signature with best alignment value with normal network connection sequences. This paper ends up with accuracy value and threshold score for detecting the network anomalies that no known conditions exist for them to be discovered in addition for percentage of generating false positive and true negative alarms

Digital image scrambling using 2D cellular automata

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. A. L. A. Dalhoum et al., "Digital Image Scrambling Using 2D Cellular Automata", IEEE MultiMedia, vol. 19, no. 4 pp. 28 – 36, oct-dec. 2012A digital image scrambling method based on a 2D cellular automaton, specifically the well-known Game of Life, produces an effective image encryption technique.This work has been partially sponsored by the Spanish MICINN project TIN2011-28260-C03-0

Utilizing an enhanced cellular automata model for data mining

Data mining deals with clustering and classifying large amounts of data, in order to discover new knowledge from the existent data by identifying correlations and relationships between various data-sets. Cellular automata have been used before for classification purposes. This paper presents a cellular automata enhanced classification algorithm for data mining. Experimental results show that the proposed enhancement gives better performance in terms of accuracy and execution time than previous work using cellular automata