Allure Security patents method for data protection with behavioral biometrics

Data loss prevention company Allure Security has been issued a patent for a method of applying behavioral biometrics to detect network attacks using stolen credentials or hijacked user sessions.

“System Level User Behavior Biometrics Using Feature Extraction and Monitoring” has been accepted by the U.S. Patent and Trademark Office, and describes the installation of a sensor and selection of discriminating operating system audit data to identify attackers with high accuracy, according to the announcement. The method also involves detecting interaction with decoy documents, which strongly indicates malicious activity.

“The issuance of our seventh U.S. patent demonstrates the industry-first nature of our technology, and protects use of our proprietary beacon and deception technologies. To simplify the science, this technology allows enterprises to know exactly when their documents have opened outside of a defined perimeter, and identify adversary attempts to steal data,” says Allure Security CTO Dr. Salvatore Stolfo.

The company says the host-based user behavior modelling technology described by the patent, No. 9,870,455, is a key aspect of its award-winning data detection and response technology.

“Allure is proud of the groundbreaking research our development team has been conducting for the last four years, establishing the foundation of our beacon technology. This newest patent underscores the practical yet forward-thinking approach we are taking to solving a rampant problem in the enterprise: the inability to track and validate where your confidential data is and who is accessing it when protection protocols are not followed,” said Mark Jaffe, chief executive officer of Allure Security. “Sal and the research team have shown deep expertise and an unwavering dedication to the development of this technology.”

Plurilock reached a distribution deal this week to provide its behavioral biometrics-based network security technology to U.S. federal agencies.

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