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How Spammers Fool Rule-based and Signature-Based Spam FiltersEffectively stopping spam over the long-term requires much more than blocking individual IP addresses and creating rules based on keywords that spammers typically use. Learn what sorts of solutions are out there, how the spammers fool them, and what you can do about it. Effectively stopping spam over the long-term requires much more than blocking individual IP addresses and creating rules based on keywords that spammers typically use. The increasing sophistication of spam tools coupled with the increasing number of spammers in the wild has created a hyper-evolution in the variety and volume of spam. The old ways of blocking the bad guys just don’t work anymore. Examining spam and spam-blocking technology can illuminate how this evolution is taking place and what can be done to combat spam and reclaim e-mail as the efficient, effective communication tool it was intended to be. Heuristics (Rule-based Filtering) The major drawback of this approach is the difficulty in identifying keywords that are consistently indicative of spam. While spammers may frequently use the words “sex” and ‘Viagra” in spam emails, these words are also used in legitimate business correspondence, particularly in the healthcare industry. Additionally, spammers have learned to obfuscate suspect words by using spellings such as "S*E*X", or "VI a a GRR A". It is impossible to develop dictionaries that identify every possible misspelling of "spammy" keywords. Additionally, because filtering for certain keywords produces large numbers of false positives, many organizations have found they cannot afford to rely solely on rule-based filters to identify spam. Signature-Based Spam Filters The benefit of signature-based filters is that they rarely produce false-positives, or legitimate email incorrectly identified as spam. The drawback of signature-based filters is that they are very easy to defeat. Because they are backward-looking, they only deal with spam that has already been sent. By the time the honey pot receives a spam message, the system assigns a signature, and the update is sent and installed on the subscribers’ network, the spammer has already sent millions of emails. A slight modification of the email message will render the existing signature useless. Furthermore, spammers can easily evade signature-based filters by using special email software that adds random strings of content to the subject line and body of the email. Because the variable content alters the signature of each email sent by the spammer, signature-based spam filters are unable to match the email to known pieces of spam. Developers of signature-based spam filters have learned to identify the tell-tale signs of automated random character generation. But as is often the case, spammers remain a step ahead and have developed more sophisticated methods for inserting random content. As a result, most spam continues to fool signature-based filters. The Solution Article Tags: Signature-based Spam Filters, Signature-based Spam, Spam Filters, Combat Spam, Signature-based Filters Source: Free Articles from ArticlesFactory.com
ABOUT THE AUTHORDr. Paul Judge is a noted scholar and entrepreneur. He is Chief Technology Officer at CipherTrust, the industry's largest provider of enterprise email security. The company’s flagship product, IronMail, provides a best of breed enterprise anti spam solution designed to stop spam, phishing attacks and other email-based threats. Learn more by visiting www.ciphertrust.com/products/spam_and_fraud_protection today.
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