The Difference Between Spam Blockers Filters Explained

If you’re getting a lot of spam, you should look into spam filters and how they can help your business. This overview should explain everything you need to know about anti-spam filters so you can reduce the threats represented by spam before it hits your network.

A common way to combat junk email or spam is through the consistent use of spam filters. Spam filtering is a method that eliminates unwanted emails before they reach your inbox.

The type of spam filtering differs based on the needs of the organization. Some anti-spam filters will eliminated spams based on subject matter. If a word like ‘free’ or ‘guranteed’ is in the subject line, the email may be quarantined. The disadvantage of using a method like this should be obvious. If the rules are too Draconian, legitimate email will be lost. Most filtering software will take this into account and allow you to review all messages that have been filtered. If you find that important messages are missing, you can easily restore them and loosen up the filtering options.

Spam filters remain popular because they can do a lot of the heavy lifting associated with removing bad emails. The sensitivity of the spam filters can be adjusted, giving the user a lot of control over what gets removed. Spam filtering can also be done based on attachments, data types, ‘bad words,’ and a whole lot more. Truly comprehensive solutions combine the best of multiple scanning concepts in order to offer a robust filtering solution to keep email safe.

Setting up spam filters is generally very easy. You can keep adding filtering rules until you achieve exactly what you want. If you overshoot, you can pull back and revise your filtering rules until they’re absolutely perfect.

‘Smarter’ spam filters have been in style for awhile now, and will continue to become more popular. They’re a bit tougher to setup initially, but they offer powerful spam filtering which can benefit most organizations.

New generations of spam filtering goes even further than traditional means, relying on statistical features of spam. These types of filters scan and analyze the entire email before making a decision on whether the email is spam or not. They compare the new email against a database of known spam emails and can match up whether the message is spam or not. This type of method generally pushes spam detection rates to 99% of higher. This type of filtering is very effective, even against phishing attempts.

Bayesian Filter Used To Fight Against Spammers

Advertising has changed drastically in the last four decades. The way people communicate has also changed during the same timeframe. There are numerous new communications options available, and along with this explosion of new technology a new wave of unsolicited messages has also arrived. Automation works just as well for the ‘bad guys’ as it does for everyone else. Therefore it’s not particularly surprising that so much automated spam is being sent daily. The messages still turn a profit, which is motive enough for many to engage in the practice.

Numerous techniques have been aimed at stopping spam over the years, including blacklisted domains, banned IPs, words in the subject line and many, many more. Spammers have always worked just as hard to adapt to these changes so they can continue to bombard email messages to everyone’s inbox.

Spammers might be able to easily change IP addresses and domain names, but it’s a bit tougher for them to change the content of their messages. That’s where their money is made, by pushing offers to unsuspecting people. If the content was to change too much, the commercial intent might be lost in the translation. For this reason, spam filters which focus on message content are generally the most effective.

“Phishing emails” are a huge vector of threat, and content-based filtering attempts to eliminate these emails totally. Many times phishing emails purport to be from companies like PayPal or organizations like the USPS. They generally have dire sounding titles like “Attention Required,” “Last Warning.” or something similar. They prey on the fears of the recipient, warning them of a dire consequence for not responding.

Once the victim opens the attachment or clicks on the link in the email, they’re sent to a website that resembles the one that’s being spoofed. They’re asked to give up more information, such as their account information or password. If they do, they’ve just give control of extremely important information to a criminal enterprise.

The key benefit of a Bayesian filter is that it helps use content to determine whether a message is spam or not. When combined with a Black List of spammers as well as a White list of trusted emails ids, is an extremely effective spam countermeasure. The most interesting fact is that Spam Filter with Bayesian algorithm is a self learning filter. The more you use, the more secure you shall be within a matter of few days.

Spam Filters For Outlook express

The spam filter integrate easily with popular emails clients such MS outlook and Outlook Express. With due course, up to 98% of the spam mails can be stopped from entering your Inbox.

The Spam Filter for Outlook Express and Spam Filter for Microsoft Outlook, with the features of White List/Black List and properly used Bayesian Algorithm will help prevent spam mails, phishing mails and fraud mails from bothering you further.

There has been a considerable increase in the spam mails containing Non English Characters also. The Bayesian Algorithm based Spam Filter also must have the capability to parse non English characters and mark as spam mail.

To get rid of a continuous stream of spam mails, phishing mails, fraud emails and Non-English email, you should probably consider a cloud-based filtering system that can eliminate threads before they ever reach your inbox.

At MostHost, our solution combines numerous spam filtering techniques into one cohesive program that has the capability to seamlessly integrate with MS Outlook and Outlook Express and provides the following features:

• •Bayesian Algorithm for Anti Spam Filtering
• •Auto Learning Bayesian Filter to challenge Spam Emails
• •White List of Trusted Email Address
• •Custom Black List
• •Individual Marking of Spam/Not Spam Emails
• •Optional feature to block Non-English Emails
• •Complete Mail Header Information