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Tales from the Dark Web: Device Emulators

Published: April 11, 2016 by Guest Contributor

Device emulators — wolves in sheep’s clothing

device-emulatorsDespite all the fraud prevention systems and resources in the public and private sectors, online fraud continues to grow at an alarming rate, offering a low-risk, high-reward proposition for fraudsters. Unfortunately, the Web houses a number of easily accessible tools that criminals can use to perpetrate fraud and avoid detection. The device emulator is one of these tools.

Simply put, a device emulator is one device that pretends to be another. What began as innovative technology to enable easy site testing for Web developers quickly evolved into a universally available tool that attackers can exploit to wreak havoc across all industry verticals. While it’s not new technology, there has been a significant increase in its use by criminals to deceive simple device identification and automated risk-management solutions to carry out fraudulent activities. Suspected device emulation (or spoofing) traffic historically has been difficult to identify because fraud solutions rely heavily on reputation databases or negative lists.

Detecting and defeating these criminals in sheep’s clothing is possible, however. Leveraging Experian’s collective fraud intelligence and data modeling expertise, our fraud research team has isolated several device attributes that can identify the presence of an emulator being used to submit multiple transactions. Thanks to these latest FraudNet rule sets, financial institutions, ecommerce merchants, airlines, insurers and government entities alike now can uncloak and protect against many of these cybercriminals.

Unfortunately, device emulators are just one of many tools available to criminals on the Dark Web. Join me at Vision 2016, where U.S. Secret Service and I will share more tales from the Dark Web. We will explore the scale of the global cybercrime problem, walk through the anatomy of a typical hack, explain how hackers exploit browser plug-ins, and describe how enhanced device intelligence and visibility across all channels can stop fraudsters in their tracks.

Listen to Mike Gross as he shares a short overview of his Vision 2016 breakout session in this short video.

Don’t miss this innovative Vision 2016 session! See you there.

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In today’s digital lending landscape, fraudsters are more sophisticated, coordinated, and relentless than ever. For companies like Terrace Finance — a specialty finance platform connecting over 5,000 merchants, consumers, and lenders — effectively staying ahead of these threats is a major competitive advantage. That is why Terrace Finance partnered with NeuroID, a part of Experian, to bring behavioral analytics into their fraud prevention strategy. It has given Terrace’s team a proactive, real-time defense that is transforming how they detect and respond to attacks — potentially stopping fraud before it ever reaches their lending partners. The challenge: Sophisticated fraud in a high-stakes ecosystem Terrace Finance operates in a complex environment, offering financing across a wide range of industries and credit profiles. With applications flowing in from countless channels, the risk of fraud is ever-present. A single fraudulent transaction can damage lender relationships or even cut off financing access for entire merchant groups. According to CEO Andy Hopkins, protecting its partners is a top priority for Terrace:“We know that each individual fraud attack can be very costly for merchants, and some merchants will get shut off from their lending partners because fraud was let through ... It is necessary in this business to keep fraud at a tolerable level, with the ultimate goal to eliminate it entirely.” Prior to NeuroID, Terrace was confident in its ability to validate submitted data. But with concerns about GenAI-powered fraud growing, including the threat of next-generation fraud bots, Terrace sought out a solution that could provide visibility into how data was being entered and detect risk before applications are submitted. The solution: Behavioral analytics from NeuroID via Experian After integrating NeuroID through Experian’s orchestration platform, Terrace gained access to real-time behavioral signals that detected fraud before data was even submitted. Just hours after Terrace turned NeuroID on, behavioral signals revealed a major attack in progress — NeuroID enabled Terrace to respond faster than ever and reduce risk immediately. “Going live was my most nerve-wracking day. We knew we would see data that we have never seen before and sure enough, we were right in the middle of an attack,” Hopkins said. “We thought the fraud was a little more generic and a little more spread out. What we found was much more coordinated activities, but this also meant we could bring more surgical solutions to the problem instead of broad strokes.” Terrace has seen significant results with NeuroID in place, including: Together, NeuroID and Experian enabled Terrace to build a layered, intelligent fraud defense that adapts in real time. A partnership built on innovation Terrace Finance’s success is a testament to what is  possible when forward-thinking companies partner with innovative technology providers. With Experian’s fraud analytics and NeuroID’s behavioral intelligence, they have built a fraud prevention strategy that is proactive, precise, and scalable. And they are not stopping there. Terrace is now working with Experian to explore additional tools and insights across the ecosystem, continuing to refine their fraud defenses and deliver the best possible experience for genuine users. “We use the analogy of a stream,” Hopkins explained. “Rocks block the flow, and as you remove them, it flows better. But that means smaller rocks are now exposed. We can repeat these improvements until the water flows smoothly.” Learn more about Terrace Finance and NeuroID Want more of the story? Read the full case study to explore how behavioral analytics provided immediate and long-term value to Terrace Finance’s innovative fraud prevention strategy. Read case study

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