Author/Authors :
SHAMSUDDIN, SITI MARIYAM Universiti Teknologi Malaysia - Fakulti Sains Komputer Sistem Maklumat, Malaysia , ZAINAL, ANAZIDA Universiti Teknologi Malaysia - Fakulti Sains Komputer Sistem Maklumat, Malaysia , ABDUL HALIM, SHAHLIZA Universiti Teknologi Malaysia - Fakulti Sains Komputer Sistem Maklumat, Malaysia
Abstract :
Artificial Immune System (AlS) is an emerging field to the computer scientists and most of the recent works concerning AlS is in the area of Intrusion Detection System (IDS). AlS is based on human immune system. It is distributed in nature, deploys the adaptive learning and exercises complementary mechanism to defend human body from bacteria or foreign elements. Artificial Immune system is non-linear and adopts the biological concept in classifying self against the nonself cells. This paper discusses on the implementation of AlS using the Negative Selection Algorithm in classifying andrecognizing patterns on digits (0 to 9). Data for every digit is extracted using moment invariants and is represented in 8 bit string. There are 10 sets of detectors generated and the complementary process between self and non-self is done using the XOR operator. The result for classification for a digit is based on the percentage matched. Higher percentage indicates that the test data is closed to the digit to be recognized.
