How to protecting your company's data when employees leave
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How to protecting your company’s data when employees leave

How to protecting your company’s data when employees leave

A new wave of intelligent data classification solutions greatly improves both visibility and accuracy

Data employees

After years of experiencing a hiring frenzy, the tech industry became inflated with employees of all types be it sales, engineers, customer support, marketing and others. With present market dynamics in play, more than 30,000 tech workers have been laid off so far this year and even more leaving through voluntary resignations. We are on the heels of what could be coined “The great deflate.”

And as more companies look to cut costs and size down in the months ahead, or deflate, enterprises need to prepare and protect themselves, and nowhere is this more important than when it comes to protecting data assets.

Companies across industries now find themselves in an increasingly vulnerable position when former employees can walk out the front door with more than their box of personal items. It’s time we rethink the approach for preventing critical data loss.

Understand points of vulnerability
It’s no surprise that the job functions and departments that handle data most critical to a company’s success tend to be where most data leakage incidents occur. While not every “leaver” will steal, lose or misplace your data, anyone with the right access privileges can download, or email to their personal devices or cloud accounts.

The leavers representing the highest risk are disgruntled or frustrated, ignorant of policy and confidentiality agreements, or feeling entitled to the proprietary data and want to use at their next job. The typical points of exfiltration are everyday business tools and services like emails, websites, cloud apps and collaboration tools. With people and information spread far and wide, security teams need better visibility to everything, at all times.

Data classification accuracy with AI
A new wave of intelligent data classification solutions greatly improves both visibility and accuracy. Instead of security pros having to manually train the system, the modern data classifier uses AI and machine learning to mimic neural networks and learn automatically “on the fly.” The AI-based classification engine, then, is predictive and continuously self-learning, which becomes more accurate and efficient the more you use it over time. You can apply labels for everything from source code to employee email and automate controls for how this information can be accessed and shared. This level of automation can directly feed your data loss prevention engine, which brings us to our third point, security enforcement.

Automate policy enforcement
If you know where your data is and who has access to it, you’re giving your security teams a fighting chance against inadvertent or malicious data theft. Start by unifying policy management for all the channels where you use data. By combining data classification with data security for web, cloud, private apps, with a single policy can prevent proprietary data from leaving with the employee. Adopting a holistic data security programme, which offers a broader view of where data resides within an organisation, helps you close gaps you didn’t even know existed. Incorporating technologies that unify management, adapt to risk, and provide full visibility and classification more than even the odds. They can help you simplify security and automate prevention to mitigate the risk of data loss, especially from the threat posed by job leavers.

Jaimen Hoopes is the vice president – Data Security Product Management at Forcepoint

Read: Top five privacy trends to protect personal data challenges through 2024

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