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While 99.9% of spam, malware and phishing emails are being caught by our spam filters, occasionally some can slip through. When this happens, it's very important to mark the email as spam, then our system will learn that messages from a specific sender aren't good and helps us make AOL Mail even better at recognizing future spam emails.
• Don't respond to unsolicited emails or requests to send money. • Pay attention to the types of data you're authorizing access to, especially in third-party apps. • Don't use internet search engines to find AOL contact info, as they may lead you to malicious websites and support scams.
Even though spam attacks typically end in about a week, there are things you can do to manage it. • Mark spam and mailing lists. • Create filters to keep your inbox clear. • Create strong and unique passwords for your accounts. • Check credit card and bank statements for illegitimate transactions.
The conclusion is that the purpose of greylisting is to reduce the amount of spam that the server's spam-filtering software needs to analyze, resource-intensively, and save money on servers, not to reduce the spam reaching users. The conclusion: "[Greylisting] is very, very annoying. Much more annoying than spam." [7]
Digital junk mail is just like the unwanted coupons, flyers and other stuff you get in your mailbox, except your spam folder is separate from your main email inbox — so if you never check it and ...
Social spam is on the rise, with analysts reporting over a tripling of social spam activity in six months. [7] It is estimated that up to 40% of all social user accounts are fake, depending on the site. [8] In August, 2012, Facebook admitted through its updated regulatory filing [9] that 8.7% of its 955 million active accounts were fake. [10]
With this additional contextual recognition, it is one of the more accurate spam filters available. Initial testing in 2002 by author Bill Yerazunis [ 1 ] gave a 99.87% accuracy; [ 2 ] Holden [ 3 ] and TREC 2005 and 2006 [ 4 ] [ 5 ] gave results of better than 99%, with significant variation depending on the particular corpus.