F5 Networks this week announced it is acquiring Shape Security, a provider of a cloud service that leverages machine learning algorithms to identify instances of fraud, for roughly $1 billion in cash.
Preston Hogue, senior director of security marketing for F5 Networks, said the services Shape Security provides are a natural extension of the range of managed services F5 Networks provides to secure applications. The company claims the acquisition of Shape Security will double the addressable market for its security services.
Hogue noted many of the machine learning algorithms developed by Shape Security will also be applicable to, for example, the managed security operations center (SOC) service that F5 Networks currently provides. F5 Networks also will be in a position to extend the reach of the Shape Security service via NGINX, the provider of widely used open source platform for web serving, reverse proxying, caching and load balancing that F5 Networks acquired earlier this year, he said.
F5 Networks chose to acquire Shape Security because the company already provides a proven service spanning more 200 million mobile devices. That level of scale is required to address fraud issues stemming from the 3 billion credentials that are compromised each year, said Hogue. Overall, F5 Networks values the fraud detection market at $4 billion. With 40% of all bot traffic suspected of being malicious, Hogue said the scale of the cybersecurity challenges organizations face is increasingly pushing them toward embracing managed secure services, he said.
The challenge and the opportunity that will emerge as organizations make that transition, Hogue noted, will be the melding of the managed services provided by vendors such as F5 Networks with the application development and deployment practices organizations are putting in place to drive a broad range of digital business transformation initiatives.
While fraud detection is clearly a natural extension of any cybersecurity service, it’s also an area that is attracting the attention of a wide range of IT vendors, including a host of startups looking to usurp incumbents such as IBM and RSA, a unit of Dell Technologies. It’s unclear to what degree the fraud detection market may be about to consolidate as larger vendors consider the potential that machine learning algorithms and other forms of artificial intelligence (AI) afford to address what has clearly become a chronic problem for many companies.
It’s not likely algorithms are going to replace the need for humans to review transactions anytime soon. However, the number of transactions that can be reviewed by relying more on machine learning algorithms to root out the most common forms of fraud should enable cybersecurity teams to become much more effective. Of course, fraud detection, like any other form of cybersecurity, is an arms race. Every time organizations improve their overall security posture, it’s usually not too long before cybercriminals find yet another method to compromise transactions.
The good news is, given the amount of research and development resources being poured into identifying and preventing fraudulent transactions, it’s only a matter of time before the next generation of fraud detection services based on machine learning algorithms becomes widely accessible to all.
Author: Michael Fizard