• Jul. 23, 2017, 5:43 pm

ThreatMetrix awarded patent pair

Digital fraud prevention company ThreatMetrix has added two new patents to a list that now numbers 11.

The first was awarded for technology which identifies devices and related fraud and security violations in real time across a global network. It covers attribute capture from a network device connected to a web service. Taken together the services can identify a device, recognize if it is new or returning, determine if it is spoofed or compromised and rate its trust level.

It is applicable to web servers, mobile apps, firewalls, prevention systems, anti-spam devices and other environments.

The second involved the use of device fingerprinting technology to track machines on a wide area network to detect and combat malicious and compromised activity. It watches website traffic via computer networks and can identify malicious hosts coupled on the network.

Firewalls, intrusion detection and prevention systems, servers, content filter devices, anti virus processes, and any combination of anti-spam devices, web proxy filters, spyware, web security processes, and electronic mail filters.

Alisdair Faulkner

Alisdair Faulkner

The technology covered by the new patents allows ThreatMetrix to globally use shared intelligence to track devices and changes to them on a global scale, allowing them to detect suspicious activity anonymously and without user interaction.

Just like fingerprint matching is a critical tool for fighting crime in an offline world, we need a robust approach for matching and identifying devices and associated digital identities to detect and prevent cybercrime,” ThreatMetrix Chief Products Officer Alisdair Faulkner said.

“Where real fingerprints get smudged and criminals wear gloves, valid users upgrade their devices and cybercriminals use anonymizes and bots.

“With online authentication and fraud prevention, a big difference is that matching digital fingerprints across the internet needs to take milliseconds, be continuously updated with every single interaction and transaction in real-time, and assume that criminals are going to try to avoid detection.”

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