Скачать или смотреть This Surprisingly Simple Email Trick Will Stop Spam With One Click

Some 320 billion spam emails are sent every day, and 94% of malware is delivered via this medium. What if I were to tell you a surprisingly simple one-click email trick could stop them? Over half of all global email traffic is spam, a statistic that is only surprising in as far as most people probably expected it to be more than that. To put that into some perspective, the latest analysis from Cisco Talos intelligence puts the average daily spam volume for April at 320 billion. Spam is always annoying, sometimes amusing and often dangerous. According to Google, its Gmail service blocks more than 100 million phishing emails every single day, 18 million of them related to COVID-19 in some way. With as much as 94% of malware being delivered by email, and one in every 3,000 email messages containing malware payloads, spam remains a very real problem in 2020. But what if I were to tell you a surprisingly simple email trick could stop that spam with just one click? The history of spam is a long and dishonorable one. I'll skip the email advertisement sent to a couple of hundred users of the Advanced Research Projects Agency Network (ARPANET), a technical precursor to the internet as we know it, back in 1978. Instead, I had to wait until April 1994 before receiving my first spam message: sent to USENET groups rather than by email, advertising a green card lottery service by two lawyers, Canter and Siegel. It was this simple advertising message that formed the foundation of what became the junk email phenomenon. That danger was demonstrated almost precisely 20 years ago to the day when the ILOVEYOU worm was distributed by email and infected millions of Windows computers. Across the two decades that have followed, spam has remained the primary vehicle for delivering malware as well as being an ever-present irritant. Twenty years ago, spam blacklists were the most commonly used anti-spam technique: and oh boy did they suck. Filtering spam by the IPs of known bad senders only works if those IPs are not only known but accurate. Seeing as many spammers used the same internet service providers as everyone else, false positives were the order of the day and most of us turned such filtering firmly off soon enough. Dedicated spam filtering solutions using a combination of sender reputation scoring and keywords soon emerged and proved more effective. They did, however, require a period of training whereby the recipient would have to categorize email as being spam or not manually. Thankfully, email applications now come with anti-spam measures built-in, and the likes of Gmail, for example, reckon the machine learning algorithms that power the spam filtering for 1.5 billion Google email users are 99.9% accurate. That still leaves way too many actual spam messages getting through when you do the math, and it's dealing with these that is proving difficult.


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