Please use this identifier to cite or link to this item:
Title: An Improved AIS Based E-mail Classification Technique for Spam Detection
Abdulhamid, Shafi’i Muhammad
Keywords: Artificial immunesystem
E-mail Classification
Cyber Crime
Issue Date: 10-Jun-2012
Publisher: The Eighth International Conference on eLearning for Knowledge-Based Society
Abstract: An improved email classification method based on Artificial Immune System is proposed in this paper to develop an immune based system by using the immune learning, immune memory in solving complex problems in spam detection. An optimized technique for e-mail classification is accomplished by distinguishing the characteristics of spam and non-spam that is been acquired from trained data set. These extracted features of spam and non-spam are then combined to make a single detector, therefore reducing the false rate. (Non-spam that were wrongly classified as spam). Effectiveness of our technique in decreasing the false rate shall be demonstrated by the result that will be acquired.
Appears in Collections:Cyber Security Science

Files in This Item:
File Description SizeFormat 
65.pdfAn Improved AIS Based E-mail Classification Technique for Spam Detection179.72 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.