Data Loss Prevention Solutions: As we See in 2024

Business

The Evolution of Data Loss Prevention Solutions: As we See in 2024

September 17, 2024
10:21 pm

By: Omer Choudhry

Data Loss Prevention (DLP) solutions have been on the market for quite some time. The evolution of DLP solutions like any other security products are driven by mainly three elements, the compliance requirements, multiplication of data and the overall outlook of the threat landscape. In the early days, mere presence of text or string-based detection was enough, and even companies felt safe when they used the DLP component bundled in their email solutions or web gateways. The biggest motive back then was to keep the competition away from biting into your piece of pie. Insider threats were a possibility too until the compliance regulations came into effect and changed the game altogether.

We are living in an era where all sophistication is applied to a DLP solution and yet the market demand is not satisfied. All entities of a business, including the end user customers, know how important their data is. It is like living the dream for a data security enthusiast.

The way the landscape of data security is evolving, looks like we are on the bullet train moving towards cloud-based solutions. Business sectors known traditionally for slow technological evolution are pacing towards cloud computing.

There are good reasons for the financial sector and telecommunication especially to take a lot of time to adapt to new technologies. Their huge employee base, reliance on technology and change management processes are to name a few, however now that everyone is on the same page, there is so much more expected from data security products.

A huge gap was left when Symantec was acquired by Broadcom and the most comprehensive DLP solution practically froze on its paws. To fill this vacuum many rushed in no matter how prepared they were, but this is an old debacle now, yet the requirement list is still new.

The biggest challenge is to handle unstructured data. Although some solutions are much better than others in correctly identifying unstructured data using fingerprinting techniques, reliance on pre-classified data is not very satisfying. The biggest challenge is we are more reliant on accuracy of data classification solutions than we should be. That leaves gaps where unclassified data is most likely to slip through and in some cases even make headlines.

Question asked everywhere is how AI can help. The answer is not very simple. The unsaid agreement is on spending more resources and time towards gathering statistics to establish the right owners and right users of data so it can be tracked for exfiltration.

This approach looks systematic and right. The focus as a result changes from infrastructure management since almost all DLP solutions are now not only cloud based but determined to move away from on-premises as soon as possible. The organizations still not ready to move all their data from on-premises to cloud will have to hurry. It is evident that soon they will be out of options.

This change impacts the way data security professionals have been working in the past. They are now diverting their attention more towards examining the data correlation and improving their policies based on the findings. With some help from AI, soon we will be seeing seamless integration of DLP with SOC where you don’t have to spend time on manually tackling the false positives. First CASB and now SASE are real catalysts to the process.

So, challenges in future DLP days might be accuracy of data analysis, alignment of data security program with compliance and business requirements and to some extent a sanity check because there will be a lot more insight information for compliance managers to process than before.

This will lead to the development of new data security tools helping compliance managers and internal auditors. The identity and access management solutions will also have more stuff on their plate and the features of a data protection program will look way different in the upcoming years.

The machine learning techniques will surely be in the limelight for quite some time. Their role and efficacy will be one of the deciding factors on success or failure of a DLP program.

In conclusion, as artificial intelligence grows and thrives, the progress towards robust yet adaptable Data Loss Prevention strategies incorporate ingenuity and innovation alike.

The blog page omerchoudhrysblog.blogspot.com discusses technical insight into specific DLP solutions and techniques in detail and the writer can be reached at omeranwaar@gmail.com.