Performance Lab DataSan

The main articles are:

• DLP - Data Loss/Leak Prevention
• Data management

2024

Integration with popular DBMS

Performance Lab presented an updated version of DataSan on November 28, 2024. The product is adapted to the latest requirements of the legislation on the protection of personal data, which this week tightened responsibility for their leakage.

Key DataSan technical enhancements:

1. Data processing speed. Engine optimization has reduced data depersonalization time by half. For example, TB 37 processing now takes 32-36 hours instead of the previous 80.
2. Advanced grading module. The updated version automatically finds and classifies personal data even in outdated and unattended databases, minimizing the risks of leaks.
3. Improved performance. The system is capable of depersonalizing up to 1 million lines of data in less than a minute.
4. Integration with popular DBMS. DataSan supports PostgreSQL, Oracle, MySQL, Microsoft SQL Server and other systems, making it a versatile tool for any infrastructure.
5. Economy. The solution works on existing customer capacities without requiring additional infrastructure costs.

In the face of challenges, our task is to offer companies a tool that not only protects data, but also allows businesses to work efficiently, saving resources, "said Vladimir Kashirsky, General Director of Performance Lab.

Key features of DataSan:

1. Complete preservation of the data structure, ensuring its performance after depersonalization.
2. Integration into CI/CD processes, which speeds up testing and development.
3. Resistance to attacks, reliable data protection from decoding.
4. Usability - the product provides flexible customization for the needs of a specific business.

Include in the FinTech Association repository

On October 18, 2024, Performance Lab announced the inclusion of its DataSan depersonalization product in the FinTech Association (AFL) repository. This event means moving to a new level of information infrastructure security for the financial sector. Russian companies can now choose already proven and recognized data protection solutions without reinventing the wheel, but relying on the experience and expertise of industry leaders.

DataSan is the only solution among competitors presented in the repository, which emphasizes its high value and innovation. It enables financial institutions to effectively optimize the preparation of depersonalized integration test environments in the face of increased data protection requirements. The product reduces the risk of sensitive data leakage by ensuring the security of confidential customer information.

The inclusion of DataSan in the AFL repository confirms the recognition of our product by industry colleagues and opens up new prospects for us to cooperate with members of the association. We are confident that this will help financial institutions build reliable and secure IT landscapes based on domestic solutions that meet all security and sustainability requirements, "said Vladimir Kashirsky, General Director of Performance Lab.

DataSan meets all the key criteria for inclusion in the AFL repository: the product is completely Russian and independent, has practical value for organizations financial sector and contributes to the replacement of a foreign ON one with domestic solutions. Importantly, DataSan complies with data protection, critical information infrastructure data security, and financial continuity regulations.

The presence in the AFL repository ensures that the product has already passed the expert assessment and is ready for use in real conditions. For individuals, this means ensuring that their data remains protected, which minimizes the risks of leaks and fraud.

The inclusion of DataSan in the AFL repository is not only a confirmation of the high level of the Performance Lab solution, but also a significant contribution to the development of the domestic financial ecosystem.

Start DataSan

The Resident Group, Performance LabSkolkovo March 6, 2024, announced the launch of DataSan, a depersonalization solution. data Developed using hashing and mapping technologies, DataSan offers a high level of anonymization of data, while maintaining its functional value. The combination of technologies allows you to achieve a high speed of data masking and meet the functional requirements of any customer. DataSan does not require additional infrastructure, which creates new standards for privacy protection and. information security

The solution passed pilot testing in large Russian companies, proving its effectiveness and reliability. One of the key cases is the introduction in a large Russian bank, where DataSan depersonalized 20 TB of data in just 16 hours, confirming its effectiveness and reliability.

In the era of business digitalization, when data becomes new gold, protecting it is a critical task. The relevance data protection from hacker attacks is growing every day. DataSan is not just a solution, it is our mission to provide Russian companies with a reliable, efficient and affordable tool that surpasses foreign counterparts in its power. DataSan provides complete flexibility and control over the depersonalization process, said Vladimir Kashirsky, General Director of Performance Lab.

The solution stands out from the background of analogues with a special combination of performance, availability and efficiency. Working directly at the database's capacity, the tool delivers high-speed data processing - up to a million lines in less than a minute - while maintaining the full structure and semantic integrity of the information. This makes DataSan not only a cost-effective choice for business, but also a powerful tool in the fight for information security. The solution has built-in multithreading and the ability to resume the process in the event of an unexpected interruption.

DataSan has the following key features: it maintains the completeness of the data, ensuring its quality and accuracy; supports data structuring without disrupting its internal logic and communications; guarantees semantic integrity, preserving the meaningfulness of information; provides anonymity, making it impossible to identify personal information; offers resistance to attacks and decoding attempts, increasing data security; and provides variability in the choice of depersonalization methods, allowing a flexible approach to information protection.