Are you staying on top of the online fraud and abuse headlines? It’s time to test your knowledge! Fill in the blanks below. No cheating! And don’t forget to check your answers when you’re done.

Fill in the blanks!

1. China is currently testing a groundbreaking national_____.

2. In 2016, about $12 billion in fraud loss came from_____.

3. Using machine learning, Cisco was able to detect_____.

How did you do?

1. China is currently testing a groundbreaking national digital currency.

It may seem like something out of a sci-fi novel, but it’ll soon be a reality for Chinese citizens: digital money! The People’s Bank of China is currently testing a digital currency by using it to conduct fake transactions among commercial banks. The currency will be tied to the Chinese Yuan.

Although China cautions that there’s still considerable work to be done before they can deploy the currency alongside the Yuan, this is still a groundbreaking step toward faster, safer banking. According MIT’s Technology Review, a digital currency will lower the cost of financial transactions, increase the reach of financial services, reduce fraud, and increase transparency.

2. In 2016, about $12 billion in fraud loss came from data breach victims.

That’s an astonishing three-quarters of the total fraud losses in 2016. According to a report from Javelin Advisory Services, $8.3 billion came from victims who’d experienced a data breach in the past 12 months, while $12 billion came from victims who had been breached in the past 6 years.

What can we learn from this report? People who suffer data breaches are usually advised to monitor their bank accounts for suspicious activity, but this report suggests that even after years of monitoring, victims still might not be in the clear. The report also suggests that businesses (and their customers) benefit from taking fraudsters seriously: those who established fraud and risk teams were less likely to fall prey to data breaches than those who did not.

3. Using machine learning, Cisco was able to detect malware in encrypted traffic.

It’s been called an impossible task: not just looking into encrypted traffic, but learning from it. And yet an advanced security research group at Cisco may have figured out a way to crack into encrypted data using machine learning, and then to learn when such data might be infected with malware.

The machine learning algorithm, developed by Blake Anderson and David McGrew, examines patterns in flows between encrypted traffic streams. By comparing the streams, the algorithm learns which kinds of traffic are associated with malware, and which kinds of traffic are benign. While the online fraud world is excited about the findings, researches are already raising understandable privacy concerns. Tom Kellerman of Strategic Cyber Ventures worries this technology could be used for “malicious purposes,” such as reading encrypted emails and user IDs.

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Roxanna "Evan" Ramzipoor

Roxanna "Evan" Ramzipoor is a writer on the marketing team at Sift Science. Her fiction is represented by Kristin Nelson of Nelson Literary. To see more of her work, check out her blog: http://just-three-words.tumblr.com/