There has been a fundamental tension in every organisation’s cyber security strategy over the years: the tighter and tighter the data protection policies, the greater the operational friction for employees becomes.
IT teams faced a constant challenge of calibration – rules that were too loose created security gaps, while those that were too rigid generated bottlenecks in business processes.
Today, thanks to an approach known as adaptive data protection, this compromise is no longer a necessity.
The new generation of security systems is moving away from static rules to dynamic, automated, real-time risk assessment.
It is a technological paradigm shift that allows organisations to maintain a strong security posture without inhibiting the natural flow of work.
Limitations of static security policies
Traditional data protection models were based on a binary ‘allow/block’ logic. Administrators created sets of rules that determined in absolute terms what actions were permissible.
This approach, although simple to implement, was characterised by a lack of contextual awareness. The consequences of this manifested themselves on several levels. First and foremost, it generated bottlenecks in business processes, as legitimate and justified activities that did not fit into the predefined framework were automatically blocked.
An employee wanting to move a presentation to a client meeting was treated by the system in the same way as someone trying to take confidential data.
This situation naturally led to the emergence of ‘Shadow IT‘. In the search for efficiencies and ways to bypass restrictions, employees began to use unauthorised, external tools such as public cloud drives or private messengers.
This resulted in a loss of visibility and control over the flow of corporate data. Finally, the whole system generated a significant administrative overhead for IT departments, which were inundated with requests to temporarily lift locks or create numerous exceptions to rules, which absorbed their resources.
Mechanics of the context-aware system
Adaptive data protection replaces rigid rules with algorithmic risk analysis. Instead of checking whether an action is on the prohibited list, the system calculates a numerical ‘risk score’ for it in real time.
At its core is a multidimensional analysis that provides a complete picture of the situation. This process starts with the identification and classification of the very data it is interacting with. The system needs to know whether it is dealing with publicly available material or with strategic financial data.
The system then assesses the parameters of the action itself, distinguishing whether the user is trying to read, modify, copy or send data outside the organisation. Equally important is the human context, provided by integrated behavioural analysis systems (UEBA).
They form a baseline of normal behaviour for each user, and any deviation from this pattern, such as working at unusual hours or downloading significantly more data than usual, is treated as an indicator of increasing risk.
The overall picture is completed by an analysis of the endpoint, i.e. the device from which access is performed. Its security status, its company affiliation and the network on which it is located are assessed.
Differentiated responses in practice
The strength of the adaptive approach lies in the flexibility of the response, which is precisely calibrated to the calculated level of risk. Instead of a single, binary response, the system has a whole spectrum of automated actions at its disposal.
In low-risk scenarios, which include most day-to-day routine activities, the system runs in the background, remaining completely transparent to the user and providing a seamless workflow.
However, when the algorithms detect an elevated level of risk, the system can apply additional, proportionate controls. This could be, for example, enforcing multi-component authentication, displaying an educational notification to the user or activating an on-the-fly data encryption mechanism.
If critical status activity is detected and the risk score exceeds a set threshold, the system is able to take decisive action, such as blocking the operation completely, terminating the user session and immediately generating a detailed alert for the security analyst team.
A new paradigm for data protection
The move from static rules to adaptive risk analysis is an evolution that reconciles two previously conflicting goals. Organisations can maintain operational agility and allow employees to work freely, while maintaining granular control over their data.
Security ceases to be an external layer of lockdowns and becomes an integrated, intelligent system function that adapts its level of protection to dynamically changing conditions. It’s a solution that allows you to protect your company’s assets with precision – like a scalpel, not a hammer.
