Mail Classification Terms and Definitions
Situation – While familiarizing yourself with your Spambrella platform and features, you may encounter words and terms you are unfamiliar with.
Solution – Some terms on the Essentials console related to mail classification are defined below.
- Spam – unsolicited junk email / useless email that you never asked to receive. Spam is often understood as any email that a recipient didn’t want, but true Spam is something that will always carry a payload (a link to some website or stock or something) containing some information that tries to financially benefit a third party, and often sent using criminal means (misappropriation of email servers or clients for bandwidth or false legitimacy, as well as the unethical harvesting or guessing of email addresses). It is important to remember that Spam would not exist if not enough people were fooled by it into parting with their money.
- Ham, Clean, Innocent – these are synonyms we use for email that doesn’t fall into the other categories and which Spambrella should pass unhindered.
- Virus – a malignant executable that hides and poses as, or in the middle of, something it is not and spreads itself actively when running or passively by relying on social engineering (fooling people to forward that email); classic viruses used to harm one’s computer (like formatting/damaging the disk) but modern viruses tend to try to either steal information (access credentials, credit card details, identity theft) or take control of your computer (and join a botnet (a network of ‘bots), using it to send spam, launch attacks, etc.)
- False Positive – a positive is desired email, and this term is from classification theory, i.e. a false positive is a desired email that falsely got misclassified as spam.
- False Negative – a negative is an undesired email (spam/virus), and in this terminology, a false negative is an undesired email that falsely got misclassified as clean.
Are you seeing False Positives or Negatives and wondering how to report them? Check out our article False Positive and False Negative Reporting!