The Dangers of Spam and How to Prevent It

Let's begin by defining spam, an irrelevant message or an inappropriate message sent to a large number of recipients on the internet. Microsoft defines spam as spam, trying to obtain information, selling something to you [1]. This may be a fake email from your bank. Let me explain how to prevent spam. According to Vitali Friedman, the biggest and easiest thing is not to say your e-mail anywhere on the Web [2].

100% of known viruses are blocked. 99% of spam blocked all emails sent to Exchange Online and became available through 5 different SPAM filters. You can customize filters to allow specific partners, safe and dangerous IP addresses, content filtering, etc. Many third party solutions such as Mimecast are available to enhance security. Can you say that I am a fan of Mimecast? If you are using a third party SPAM filter, you can configure Exchange Online to block messages other than Safe Senders List. Outbound mail is also safe. It is designed to prevent fraud and exclude organizations from black list. I used Office 365 (formerly called BPOS). There is no need to delete a single organization from the blacklist. Those who had to deal with these problems are a little excited about this.

Internet criminals continue to develop technology to break into organization defenses. E-mail threats are expanding from simple annoying spam to dangerous phishing and unauthorized spam. Cisco IronPort Anti-Spam uses traditional technology and innovative context-sensitive detection technology to eliminate a variety of known new e-mail threats. Cisco IronPort is the first company to introduce reputation filtering technology into a strong anti-spam defense outer layer. The Cisco IronPort reputation filter blocks up to 90% of the received spam at the connection level. The Cisco IronPort appliance also supports its own rate limiting feature that intelligently delays suspicious senders, which can significantly reduce spam without the risk of false positives.

Precision shows that messages classified as spam are actually percentages of spam. This is the ratio of true positive (classified as spam and actually spam e-mail) to all positive (e-mail classified as all spam regardless of whether this is the correct categorization). In other words, it is the ratio of true positive / (true positive + false positive). Recall or sensitivity indicates that the actual percentage of spam is classified as spam. This is the ratio of words classified as spam for all words that are actually spam (actually classified as spam) (regardless of whether they were correctly classified). It is given by the formula - True Positive / (True Positive + False Negative)