Ensuring data security and compliance is increasingly difficult as organizations adopt multi-cloud computing environments. Data can reside on a device, in a SaaS application, in cloud-based storage, and in other locations. Many users have access to these resources. Improving data assurance led to the emergence of Data Security Posture Management (DSPM). This product category improves the discovery, categorization, and protection of data at scale.
With this backdrop, Proofpoint has announced its acquisition of Normalyze, a DSPM provider. Proofpoint will integrate the Normalyze AI-powered products to allow security teams to increase visibility and control over critical data assets while adhering to a human-centric security posture.
Human-Centric Security Challenges
Data has value. People access all types of data as part of their jobs. Doctors access medical records, salespeople acquire and process credit card transactions, engineers work with technical specifications, and there are other examples. The problem is that people view, create, modify, and move data, which becomes difficult to protect. People make mistakes, and these errors lead to compliance violations and potentially data breaches. According to Proofpoint’s 2024 Voice of the CISO Report, 80% of cybersecurity leaders view human risk as a key concern. These concerns are not limited to unintentional events but also include malicious insiders.
Addressing the human component of risk along with technology is a challenge. The human-centric dynamic is humans are part of the team. It realizes that security is not solely the domain of tools but a sophisticated interplay between technology and human insight.
Proofpoint's human-centric approach recognizes that humans are not just a source of vulnerability but are an asset that should be leveraged in defeating cyber threats. Creating a security-conscious culture with solutions that make security intuitive, effortless, and useable allows humans to actively engage and be empowered to contribute to protecting data.
Normalyze also fosters a human-centric approach in its products. Although they leverage AI in the performance of data discovery and classification, they also have a user feedback element that improves classification accuracy and remediation recommendations. The security team can understand and tune the signatures used for data classification.
Strengthening Data Visibility and Protection Across Environments
The increasingly complex web of interconnected data environments associated with SaaS, PaaS, public or multi-cloud, on-prem, and hybrid environments has created a data protection and compliance nightmare. The vast majority of data breaches involve data stored in the cloud, according to the IBM Cost of a Data Breach Report 2023. This situation cultivated the need for data security protection that ultimately became DSPM.
The underlying concept behind the technology is to protect data directly, not to rely on security associated with the devices and applications that process or store data. Key elements of DSPM include the ability to discover and classify data, identify and prioritize vulnerabilities associated with data sets, and remediate and resolve data security threats in progress. Fundamentally, DSPM should have the ability to discover shadow data, which is data generated by cloud services a business unit uses without having been sanctioned by IT or security. It also must find forgotten and misclassified data.
According to Amer Deeba, CEO and co-founder of Normalyze, "Our solution helps data and security teams understand what sensitive or valuable data they have wherever it lives, then provides insights on who is accessing it, how it’s being used, and what the impact would be if the data were misused.”
Data Security within Generative AI
Data is the lifeblood of operations, but in today’s widely dispersed IT infrastructure and with the growth of generative AI applications, it is critical that organizations rethink data security. Generative AI requires huge amounts of data and will create its own. Some might be proprietary or sensitive. A generative AI application might accidentally combine benign data sets, which results in new data that has an elevated level of classification that the original data sets did not have. Data security capabilities must be able to scale at the speed of AI-generated data, have the ability to identify data being fed into foundational or custom models and classify all the data by sensitivity.
DSPM, although a new technology, is a critical tool for improving data visibility, prioritizing protection based on data sensitivity, and aligning security with regulatory requirements. Its ability to address the risks associated with AI-driven, multi-cloud projects will allow businesses to move forward with AI initiatives with confidence. Normalyze's AI-powered capabilities have been designed to meet these challenges, and Proofpoint plans to leverage them to address the data security challenges unique to AI integration.
A Strategic Move for a Changing Digital Era
The acquisition of Normalyze by Proofpoint should create a robust and holistic human-centric data security platform that leverages AI to accurately identify and classify valuable and sensitive data. Mayank Choudhary, executive vice president and general manager, Data Security & Compliance, Proofpoint said, “These modern applications are highly interconnected, making it hard for security teams to manage the heterogeneous and ever-growing sprawl of their data. By combining Proofpoint’s leading human-centric security platform with Normalyze’s pioneering DSPM technology, we can provide our customers with comprehensive visibility and control of their data posture so they can further mitigate human risk across their organization.”
Customers will have even greater visibility and security of all of their data. Combining DSPM and Data Loss Prevention should offer customers the ability to identify and classify sensitive data, analyze how the data is used, and leverage user behavior analytics to uncover previously unknown issues with data. The combination of these two technologies can enrich data flow analysis, which can more accurately identify attack paths to sensitive data and uncover new security risks. For example, Normalyze’s ability to monitor the flow of data can be combined with Proofpoint’s Very Attacked People capability to gain a better understanding of the attack surface.
It will be interesting to watch how Normalyze’s DSPM capabilities for multi-cloud data discovery and protection are fully integrated with Proofpoint’s technologies designed to protect people and defend data against abuse. The ability to perform these functions across multiple data stores and applications, including generative AI, will make it easier to safely share information across multiple cloud and hybrid computing environments.
