Proofpoint unveils the industry's most advanced anti- spam laboratory The openness of the Internet, long touted as… Campuses struggle to support solutions that will control the costs of filtering spam, keep "false positives" to a minimum and not diminish their own marketing use of mass e-mails. It is a social issue, and it threatens something very dear: the viability of e-mail. A comparative analysis among the algorithms has also been presented. The effectiveness of the proposed work is explores and identifies the use of different learning algorithms for classifying spam messages from e-mail. In recent days, Machine learning for spam classification is an important research issue. Many researches in spam filtering have been centered on the more sophisticated classifier-related issues. Among the approaches developed to stop spam, filtering is the one of the most important technique. Also when the counter measures are over sensitive, even legitimate emails will be eliminated. In spite of all the measures taken to eliminate spam, they are not yet eradicated. While most of the users want to do right think to avoid and get rid of spam, they need clear and simple guidelines on how to behave. The vast majority of Internet users are outspoken in their disdain for spam, although enough of them respond to commercial offers that spam remains a viable source of income to spammers. They consume more network capacity as well as time in checking and deleting spam mails. Spam emails are invading users without their consent and filling their mail boxes. Email spam is one of the major problems of the today’s Internet, bringing financial damage to companies and annoying individual users. The flaws in the e-mail protocols and the increasing amount of electronic business and financial transactions directly contribute to the increase in e-mail-based threats. SPAM CLASSIFICATION BASED ON SUPERVISED LEARNING USING MACHINE LEARNING TECHNIQUESĭirectory of Open Access Journals (Sweden)įull Text Available E-mail is one of the most popular and frequently used ways of communication due to its worldwide accessibility, relatively fast message transfer, and low sending cost. Its highly effective filtering engine identifies spam and allows multiple levels of tuning and customization to meet each user's personal e-mail spam filtering requirements" (1 page). "PreciseMail Anti- Spam Gateway uses a combination of proven heuristic (rules-based) and artificial intelligence technologies that eliminates unwanted spam e-mail at an Internet gateway without filtering critical e-mail messages. PreciseMail anti- spam gateway allows users more control over spam definitions unwanted email is eliminated with no false positives
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