Thursday, August 12, 2010
12:14 PM
 
If  you are the one who works with emails on a daily basis, you are most  likely to be using a SPAM FILTER to ease the job of sifting through a  large number of spam emails every day. Needless to say that spam filters  do make our job a lot simpler by automatically filtering out the spam  without which it is almost impossible to manually filter the junk emails  that arrive in millions each day. However, it is often necessary to  have a basic knowledge of how spam filters work and on what basis they  flag an email as spam.
                                                     
 
  
How Spam Filters Work?
 
There are different kinds of spam filters:
 
  
Header Spam Filters
 
Header spam filters work by examining the header information of a  particular email message to check if it appears to have been forged. The  header of every email contains information which tells the origin of  the email. ie: The incoming email ID and usually the IP address (server  address) of the sender. So spammers often forge the header to input a  false sender ID and IP address so as to make it difficult to trace them.  Thus if an email is supposed to have a forged header or if the same  message is found to have been sent to multiple recipients, it is most  likely considered as a spam by many filters. This method of spam  filtering is often quite effective, however occasionally it may result  in some of the requested newsletters from being misdirected into the  spam folders. 
 
  
Content Spam Filters
 
Content spam filter is one of the most effective and widely used  filter to combat spam emails. They use a sophisticated algorithm with a  set of pre-defined rules to determine whether a given email is a spam.  They work by scanning the entire text/body of the email to search for  specific words and patterns that make them resemble a typical spam  message. Most content spam filters work based on the following criteria  and check to see
 
1. If the message speaks a lot about money matter. Commonly suspected words include: lottery, discount, offer, bank account, money back guarantee etc.
 
2. If the message contains adult terms like: viagra, pills, bed, drugs, hot and so on.
 
3. If there is any sort of urgency. Most spam emails call for an urgency by using terms such as hurry, offer valid till etc.
 
4. If the message contains a single large image with little or no text then it is often considered as spam by many filters.
 
Each content spam filter may have it’s own set of additional rules  using which it evaluates each incoming email. In most cases content and  header spam filters are combined together to achieve higher level of  accuracy.
 
  
Language Spam Filters
 
Language spam filter is designed to simply filter out any email that  is not in the user’s native language. Since spammers come from all parts  of the world with different languages, a language spam filter can help  get rid of those annoying emails that come in the languages that you  can’t read!
 
  
User Defined Spam Filters
 
User defined spam filters can be very handy, however they need a  considerable amount of time investment in configuring and setting up a  set the rules using which the filter works. For example, the user can  configure to have all the emails from friends and company to reach the  inbox, newsletters to reach a secondary inbox and all those remaining to  the spam folder. Here the user must carefully examine the patterns of  spam emails that he receives from time to time and needs to set up the  rules accordingly. This filter when improperly configured can sometime  lead to false positives or false negatives.
 
  
Other Types of Spam Filters
 
Popular webmail services like Gmail, Yahoo and Hotmail combine both  header and content spam filtering techniques. In addition to this they  also use their own algorithms to combat spam. For example services like  Gmail uses “optical text recognition” to identify spammy text inside an  image. Also users are provided with an option to “Report Spam” whenever a  spam email accidentally reaches the inbox. With the user feedback, the  filter learns and becomes more powerful in carrying out the filtering  process.
 
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