Decisioning at the Edge: Changing the Way Cybersecurity and Fraud Prevention Works

Digital risk is the scourge of our modern times. Its growth in volume, sophistication and reach has even led some experts to brand it a threat to national security. Bad bots swarmed the internet in record numbers last year, driving up account takeovers, new account fraud and other malicious activity. Phishing attacks, credential stuffing and a steady stream of data breaches ensure the underground economy is well stocked with a mountain of identity data for scammers to leverage.

Facing down this challenge won’t be easy, but innovation is occurring. By deploying intelligent digital risk management tools at the network edge, organizations have a great opportunity to take the fight to adversaries, at a lower cost and with reduced impact on the end-user.

Living at the Edge

The history of computing began with a highly centralized model based around monolithic mainframe machines. With the client-server era, we saw democratization for the first time as regular users could buy computing hardware for their homes. Yet the advent of cloud computing has, to an extent, seen a re-centralization of architecture, back to a few centralized datacenters and providers. Most organizations now rely on cloud service providers (CSPs) like AWS, Microsoft, Google and IBM to deliver their infrastructure, machine learning and compute power.

However, the next evolution in computing will see things move in the opposite direction. With edge computing, more of the heavy lifting is done at the network edge rather than the centralized cloud data center. This means computing decisions are made closer to users and their devices. This will open up a new set of use cases, from autonomous vehicles to VR gaming, to delight those users. But it’s not all about IoT and smart devices. Edge computing could also be tapped for enhanced detection of fraud, abuse and security risks.

Faster Decisions at Lower Cost

Content delivery network (CDN) providers are early adopters of edge computing technology. Sitting between the client (e.g., a user’s browser) and origin server (like a website server), they’re perfectly placed to handle rules and machine learning models and make split-second decisions, such as whether traffic is coming from a legitimate or bad bot.

There are several advantages to making fraud-related decisions at this layer. First, it reduces the volume of requests made to the origin server, improving stability. Second, processing data more locally at a device level means less chance of damaging breaches occurring at a centralized cloud server. Because there’s less distance for data to travel, latency is reduced, enhancing the customer experience. Additionally, as packets are not being sent in large volumes to a central data store, transmission costs are reduced. Finally, decision-making at the edge delivers a holistic view of the entire customer journey, meaning the highest level of context is available for every decision.

Maximizing Value at the Edge

Yet CDN customers might question the logic of handing all this decision-making power to a single provider. They also want to benefit from multi-dimensional decisions which require more context from how users interact downstream – something most CDNs can’t deliver. They should therefore look for third-party digital risk management specialists who can deploy at the CDN layer to extract maximum value from edge computing but also support a wide range of analytical techniques. These could include device and digital data profiling, injecting new content, behavioral biometrics, IP location, text and image similarity analysis, machine learning and orchestration of third-party scripts and APIs.

This blend of techniques is increasingly key to mitigating the large range of sophisticated digital threats in the wild. And with the right provider, they can be enhanced with new models executed in real-time according to each organization’s risk appetite. The fight against adversaries is taking an exciting new turn.

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