US-based cybersecurity solutions provider Forcepoint said that it was launching a new division that would develop expertise on behavioural-intelligence innovations.
Called X-Labs, the new division will use data insights from the entire Forcepoint product portfolio to drive innovation in modern, risk-adaptive security solutions, the company said in a statement.
"This will deliver enterprises and government agencies more flexible and effective cybersecurity solutions appropriate for today’s intricate, cloud-first threat landscape," Nicolas Fischbach, chief technology officer, Forcepoint, said.
Explaining further, he said that the laboratory made sense since old and legacy cybersecurity solutions are currently failing as they are not coded for newer attacks.
“Forcepoint X-Labs’ mission is to understand digital identities and their related cyber behaviours, particularly as they interact with high-value data and intellectual property,” Fischbach said, adding that over time this unique behavioural intelligence corpus will integrate into the new Forcepoint Converged Security Platform to extend automated and risk-adaptive protection across an organisation’s entire on-premises and cloud infrastructure.
The company also said that X-Labs will leverage a new technology called Adaptive Trust Profile (ATP) that runs on artificial intelligence and allows security professionals to focus on those entities which pose the highest level of risk to businesses or employees.
It further said that ATP is designed to natively integrate with Forcepoint’s behaviour-based analytics, which collects data from sensors across cloud, endpoint, third-party applications, services (including SaaS or Software as a Service) and more.
The artificial intelligence models within ATP then contextualise the events and compute a risk score for each entity, Raffael Marty, vice-president of research and intelligence, Forcepoint, said, adding that then risk scores are calculated by utilising an expansive behaviour catalogue comprising innumerable scenarios, such as a user stealing data or when an individual’s account credentials are compromised.