What is Email Filtering?

Email filtering services filter an organization’s inbound and outbound email traffic.


What does a typical filtering scan consist of?

  • Outbound email filtering uses the same process of scanning messages from users before delivering any potentially harmful messages to other organizations.
  •         Inbound email filtering scans messages addressed to users and classifies messages into different categories. These include, but are not limited to: Spam, Malware, Adult, Bulk, Virus, Impostor, Suspicious Links, and Others. 
Email Filtering Techniques used here at AL
    1.        Reputation-Based Email Filters: Attempts to stop spam or allow legitimate email by filtering out known spammers or approving trusted senders based on reputation databases. Reputation Block Lists (RBLs) are lists of domains, URLs, and IP addresses that have been analyzed and deemed as possible security threats. RBLs are one of the main ways organizations can use spam filtering for protection.
    2.        Safelisting: Provides organizations the ability to determine which senders they accept email from by adding them to a list. 
    3.        Blocklisting: Provides organizations the ability to determine which senders they want to block email from by adding them to a list.
    4.        Temporarily blocklisting (sometimes called greylisting): Allows an organization to defend against spam by temporarily rejecting any email from a sender that it does not recognize. If the mail is legitimate, the sending server will try again after a delay, and the email will be accepted.
    5.         Anti-virus: Protects against new and existing viruses and other forms of malicious code using signature-based and non-signature-based technology.
    6.         Content Analysis: Offers the ability to block an email based on the content of the message. For example, if a message contains certain words, the content filter can determine that it is a spam message. Another example is if the message contained an attachment, and the organization doesn’t want to let it through. Another form of content filtering is Bayesian analysis. Bayesian analysis improves spam filtering by learning from each message it scans. The more messages are scanned, the greater the effectiveness of the analysis.