Currently, spam mails are the major issue over mail boxes as well as over the internet. Spam mails can be the cause of phishing attack, hacking of banking accounts, attacks on confidential data. Spamming is growing at a rapid rate since sending a flood of mails is easy and very cheap. Spam mails disturb the mind-peace, waste time and consume resources e.g., memory space and network bandwidth, so fighting against spam is a big issue in internet security.
This paper presents an approach of spam filtering which is based on mining knowledge base, analysis of the mail header, cross validation. Proposed methodology includes the several techniques of spam filtering with the higher accuracy. It works well with all kinds of spam mails (text based spam as well as image spam). Our experiments and results shows promising results, and spam’s are filtered out at least 97.34 % with 0.11% false positive.