In this study, a subspace analysis approach is proposed for the detection of spam e-mail. Spam e-mails can be described as messages that are sent for promotion, advertisement or directly disturbance purposes. We have chosen covariance based subspace analysis methods to approach the classification problem. The training and test sets used in the study are composed of HTML e-mails in English. A no...

We describe an in-depth analysis of spam-filtering performance of a simple Naive Bayes learner and two current variants. A set of seven mailboxes comprising about 65,000 mails from seven different users, as well as a representative snapshot of 25,000 mails which were received over 18 weeks by a single user, were used for evaluation. Our main motivation was to test whether two variants of Naive ...

Accurate spam filters are of high necessity in present days as the high amount of commercial mail entering accounts has become a real threat to everyone, from causing personal computers to crash to costing big companies billions of dollars annually because of employees loss of productivity. Moreover, lately, spam also carries viruses along. Current paper presents an evolutionary model of a spam...

Although the Internet has developed into a mass-medium for communication and information exchange over the last couple of years, many problems still exist regarding security and anonymity. One of these Achilles’ Heels is spam. Electronic mail (e-mail) has become one of the most used communication mechanism. It is absolutely easy to use and cost-effective. Unfortunately, the simplicity and effec...

Electronic mail is an important communication method for most computer users. Spam e-mails however consume bandwidth resource, fill-up server storage and are also a waste of time to tackle. The general way to label an e-mail as spam or non-spam is to set up a finite set of discriminative features and use a classifier for the detection. In most cases, the selection of such features is empiricall...

Unsolicited emails, known as spam, are one of the fast growing and costly problems associated with the Internet today. Among the many proposed solutions, a technique using Bayesian filtering is considered as the most effective weapon against spam. Bayesian filtering works by evaluating the probability of different words appearing in legitimate and spam mails and then classifying them based on t...

A large part of modern day communications are carried out through the medium of E-mails, especially corporate communications. More and more people are using E-mail for personal uses too. Companies also send notifications to their customers in E-mail. In fact, in the Multinational business scenario E-mail is the most convenient and sought-after method of communication. Important features of E-ma...

Unsolicited emails, known as spam, are one of the fast growing and costly problems associated with the Internet today. Among the many proposed solutions, a technique using Bayesian filtering is considered as the most effective weapon against spam. Bayesian filtering works by evaluating the probability of different words appearing in legitimate and spam mails and then classifying them based on t...

Unsolicited emails, known as spam, are one of the fast growing and costly problems associated with the Internet today. Among the many proposed solutions, a technique using Bayesian filtering is considered as the most effective weapon against spam. Bayesian filtering works by evaluating the probability of different words appearing in legitimate and spam mails and then classifying them based on t...

Bayesian spam filtering is a classification method based on the theory of probability and statistics, and the Bayesian spam filtering based on Mapreduce can solve the defect of the traditional Bayesian spam filtering that consumes large amounts of system resources and network resources when the mail set is pre-training. It needs to classify mails manually in the pre-training phase of mail set, ...