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InfoWatch rolls out new user behaviour analytics solution

InfoWatch Group has recently announced the release of InfoWatch Prediction, a User and Entity Behavior Analytics (UEBA) solution that automatically predicts cybersecurity risks associated with HR and finance policies, malicious insiders, account compromising, as well as other HR-critical processes.

The first product version will become commercially available later this year, focusing on proactive detection of employees that are about to leave, according to the firm.

“InfoWatch Prediction is about verifiable completion of certain enterprise cybersecurity tasks,” said Andrey Arefyev, Head of Advanced Development Department, InfoWatch Group. “Its key feature is an underlying strict mathematical model, which helps prevent specific risks and check the prediction accuracy. We provide enterprises with a tool that precisely and proactively identifies leaving employees, thus minimising related cybersecurity risks.”

InfoWatch Prediction analyses enterprise information flows (Big Data) and uses machine learning-based models to predict employee resignation probability by calculating individual rating (positive or negative) of each employee. Positive rating is assigned to high-risk employees (the higher the rating, the more likely an employee will leave).

During performance tests within infrastructures of several large companies with tens of thousands of events analysed a day, InfoWatch Prediction identified employees who were about to leave with 90% accuracy. In addition, customers can quickly check the prediction accuracy using retrospective data sampling.

“Unlike most other information security products that take months to prove their effectiveness and require customer’s equipment, time and money, we can demonstrate our system’s output almost instantly,” said Andrey Arefyev. “Our product analyses data received from the company’s mail server or DLP system for the last year to identify employees who left. Customers can compare the findings with data from their HR teams.”

Once a leaving employee is identified, a security officer can apply special security policy settings and extra control over their actions and communications. Moreover, the solution not only minimises cybersecurity risks, but also contributes to personnel record keeping, as well as management and financial accounting.

Andrey Arefyev believes that the cost of losing an employee equals their annual salary and includes losses caused by underperformance of a leaving employee, their severance pay, as well as efforts and time spent for new employee search and onboarding.

At the recently held GISEC 2018, InfoWatch Group also unveiled its international digital technology and cybersecurity training center in the Middle East that will provide education and advanced training in cybersecurity, IoT, Big Data, artificial intelligence and blockchain among others.

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