Vade Secure

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.