Email Filtering

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Vade - phishing definition

What is email filtering? 

Email filtering refers to the process of analyzing incoming emails and applying specific rules to determine their legitimacy and potential risk. Email filters automatically sort, categorize, and prioritize emails based on predefined criteria. The primary objective of email filtering is to ensure that only safe and relevant messages reach users’ inboxes while keeping malicious or unwanted content at bay.

How does email filtering work?

Email filtering uses a combination of techniques to assess the content, sender, and other attributes of incoming emails. These techniques include:

Blacklisting

Blacklists include a list of domains or IP addresses associated with malicious or unwanted senders. Emails from these senders are automatically blocked or filtered to prevent them from reaching the user's inbox. 

Content filtering

Often, spear phishers will convince their victims that they have only hours—or even minutes—to send a wire transfer, change their bank account information, or purchase gift cards for clients.

Reputation-based filtering

This filtering method assigns a reputation score to emails based on factors such as IP addresses and past actions of the sender. Email filters typically block messages with low reputation scores and prevent them from reaching a user’s inbox.

Whitelisting

While blacklisting prevents users from receiving messages from a specific sender, whitelisting does the opposite. Emails from senders on the whitelist are always delivered regardless of the content of their messages.

Bayesian filtering

Bayesian filtering prevents spam from reaching a user’s inbox using a statistical model. This method of filtering evolves over time as the filter learns to distinguish between legitimate and spam messages.

Language filtering

Language filtering blocks emails written in a foreign language and prevents them from reaching a user’s inbox.

Vade’s AI-powered email filtering solution

Vade provides advanced email filtering that leverages artificial intelligence, including Machine Learning and Deep Learning, to perform a comprehensive behavioral analysis of the entire email. This advanced filtering approach surpasses the limitations of traditional signature and reputation-scanning methods, which often fail to detect unknown threats and unreported and short-wave spam.

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