Spam Detection Using ICNEURO for Enhanced Accuracy

Spam detection or filtering process is required to cope with the harmfull effect of spam e-mails affecting directly or indirectly to the users. SPAM e-mails have a direct cost in terms of time, server storage space, network bandwidth consumptions and indirect costs to protect privacy and security breaches [6]. For providing solution to solve this problem various techniques has been implemented. This paper present the ICNEURO which is formed with the combination of Independent component analysis and Neural Network technique for enhancing the accuracy of spam detection from the dataset which is basically in the textual form applying the content based filtering technique. We make an ICNEURO as a user level program which uses the advance feature of Independent Component Analysis (ICA). Results of our approach show the enhancement in accuracy as the content or words will increase. KeywordsSpam; Neural Network; content based filtering; Independent Component Analysis; Principal Component Analysis component