Open AccessPractical Comparison Between Genetic Algorithm and Clonal Selection Theory on KDD Dataset
Author(s) -
Najlaa Aldabagh,
Mafaz Khalil
Publication year - 2010
Publication title -
maǧallaẗ al-rāfidayn li-ʿulūm al-ḥāsibāt wa-al-riyāḍiyyāẗ/al-rafidain journal for computer sciences and mathematics
Language(s) - English
Resource type - Journals
eISSN - 2311-7990
pISSN - 1815-4816
DOI - 10.33899/csmj.2010.163917
Subject(s) - computer science , genetic algorithm , selection (genetic algorithm) , data mining , knowledge extraction , intrusion detection system , field (mathematics) , artificial intelligence , machine learning , artificial immune system , clonal selection , population , the internet , biology , mathematics , demography , world wide web , sociology , pure mathematics , immunology
This paper compares between two models: Common Genetic algorithm and the new Clonal selection theory in the field of Intrusion Detection. Genetic algorithms (GA) which is a model of genetic evolution, while Clonal selection theory (CST) is from models of the natural immune system NIS, the two models are from two different fields of Artificial Intelligence AI but they have portion of shared operations and objectives. The comparison to be done by applying the two models on some records of Knowledge Discovery and Data mining tools which is known by the name KDD data sets (its records the data of the interring packets to the computer system from the internet), to produce population ( in case of GA) or antibodies (in case of CST) can recognize these abnormal records. ةعومجم ىلع ةللاسلا ءاقتنإ ةيرظنو ةينيجلا ةيمزراوخلا نيب ةيلمع ةنراقم
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