The anti-spam system is provided by Vade Secure. The system is based on a scale of –infinity to +infinity with a legitimate/spam threshold set at 100. However the values are subject to be changed by the provider.
All e-mails with a score lower than 100 are legitimate.
All e-mails with a score higher than or equal to 100 are spam or Dirty Commercial E-mails.
Commercial e-mails have a score situated between 0 and 20 and are identified by their status.
The Vade Secure score is the result of the sum of the weight of each rule used for scanning the e-mail. An example of use with weights and fictitious rule names:
(50) Bad headers, (-10) Politeness, (80) White text on white background
In this case, the final score will be 50 - 10 + 80 = 120
The emails are filtered into 3 main categories for the email system detection and flagging:
- PCE (Professional Commercial E-mails)
- MCE (Miscellaneous Commercial E-mails
- DCE(Dirty Commercial E-mails)
Category | Description | Source Data |
---|---|---|
PCE | Gathers all e-mails from a sender identified by Vade Secure. These e-mails comply with e-mailing best practices. These practices are checked through exclusion tools from the category described under DCE. | Examples in Feedback Loop. These e-mails are detected beforehand as MCE, then identified for the purpose of categorisation (PCE or DCE). |
MCE | E-mails from unidentified senders. A behavioral scan will be conducted to determine the type: advertisement or information. These e-mails comply with e-mailing best practices. These practices are checked through exclusion tools from the category described under DCE. | Predictive identification based on a behavioral scan. The change in the behavior of announcers in general is identified through feedback loops and the analysis of false negatives. |
DCE | Gathers all e-mails that have been identified as not complying with e- mailing best practices. The criteria for switching to DCE are: – Failure to honor opt-in requests – Absence of an unsubscribe link – Failure to honor unsubscribe requests – Anonymous declarations in WHOIS entries, deliberate obfuscation of details and addressing complaints. |
Volume of complaints measured through feedback loops Unsubscribe link detection tool (rate of detection of links higher than 97%) Automated and secure unsubscribe tool, identification of redundant requests. |