Twenty-eight years have passed since the appearance of Data Loss Prevention (DLP) solutions, a set of processes and tools commonly used in organizations to ensure that confidential data is not disclosed, mis-used or accessed by non-authorized users.
Today, after three generations, companies are more mature regarding this technology’s characteristics, capabilities, and limitations. There have been nearly three decades of learning in which cybersecurity departments have faced three common challenges:
- Regulatory compliance.
- Intellectual Property protection.
- Data visibility.
The first generations of DLP succeeded in solving these three use cases. However, current solutions have numerous bottlenecks, especially when it comes to remediating various weaknesses, including insider threats, data security in back-office systems, user and entity behavioral analysis, and advanced and persistent threats.
In 2017, Gartner estimated that the total DLP market would reach US$1.3 billion by 2020. Nevertheless, they fell short of the estimate because that year, the market size increased to US$2.64 billion.
DLP solutions have evolved to include managed services, cloud functionality, and advanced threat protection, among other things. In parallel, the growing trend of large data breaches has resulted in a massive increase in the adoption of DLP as a means of safeguarding private data.
What’s new about this fourth generation of DLP?
In contrast to previous versions, the approach used in this Fourth Generation leverages the power of Artificial Intelligence and Machine Learning to provide a comprehensive barrier for data leak protection.
This new generation is based on four elements that are managed in an end-to-end approach, works in line with organizations data flows, and are implemented in conjunction with applications, data repositories, and end devices:
- Automated data classification.
- Automated generation of protection policies.
- Advanced control of access levels.
- Automated authorization flows.
These four elements address a common challenge: preventing malicious data leakage by enforcing automated policies and access control criteria based on roles and identities. The main objective is to implement relevant data security policies against any possible exfiltration and/or compliance violation of confidential information.
Around the world, data protection continues to be a top priority for organizations. As forms of collaboration and communication evolve, it is equally imperative to ensure that your organization’s security posture is updated and capable of reducing the risk of data loss, exposure, and exfiltration.
The new generation of DLP secures data based on its contextual and conceptual meaning, utilizing a correlation engine and security algorithms to automatically identify, classify and protect large volumes of information in real-time, with unmatched accuracy.
This is a crucial circumstance in today’s multi-cloud, web services, mobile devices, and email environments where data needs to be secured as it is created and moved outside the enterprise perimeter.
This is where DLP 4th Generation unleashes its full potential by understanding the modern context of cloud and web access and encompassing users, devices, applications, and activities at a contextual level to accurately and efficiently detect and protect sensitive content no matter where it is located. Additionally, this solution allows companies to optimize their costs by achieving operational efficiencies through improved controls and processes.
Etek has more than 25 years of experience in customized and innovative cybersecurity solutions recognized worldwide. In addition, Etek has built a foundation of knowledge and best practices through more than 15 years of experience as an MSS with more than 110 specialists, multiple certifications, and more than 300 customers in different industries. It also supports an infrastructure of more than $88 million / hour in banking transactions, more than 240,000 transactions per year, and more than 1,000,000,000 transactions per year.