PKWARE Makes Its Entrance in the Gartner Hype Cycle for Data Security

Security and risk management leaders face an unprecedented challenge – how to safeguard sensitive data in a world where innovation knows no bounds. The key to success? Embracing cutting-edge technologies like data security posture management and data security platforms, while also preparing for the transformative impacts of quantum computing and artificial intelligence.

PKWARE was recently named in the 2023 Gartner Hype Cycle for Data Security for a multitude of reasons. PKWARE’s PK Protect Endpoint Manager and Data Store Manager products align with data security posture management allowing our customers the ability to strategically align their data protection efforts within one tool, that protects on endpoints, in the cloud, on servers, and in mainframes.

According to Gartner, Cloud service providers (CSPs) have completely revolutionized the way we handle data analytics and data pipelines. The ability to deploy these pipelines dynamically has ushered in a new era, but it also presents a unique set of challenges for data security teams. With increased data storage, backups, data subsets, extractions, and combinations of various data formats, maintaining consistent data security has become a Herculean task.

One of the major stumbling blocks in achieving data security consistency is the siloed nature of many security products. These products often use proprietary data classification systems and operate independently, making it difficult for organizations to implement robust and unified data security controls. Achieving a balance between data access requirements and security demands may appear as a daunting challenge.

However, the introduction of sovereign data strategies and products like PK Protect, are changing the game. These strategies, newcomers in the Hype Cycle, support data security governance, privacy impact assessment, financial data risk assessment (FinDRA), and data risk assessment. They aim to create a framework that bridges the gap between data and analytics categorization and data security categorization, thereby enabling organizations to integrate data discovery, classification, and metadata management seamlessly. Learn more about PKWARE’s data risk assessment to see how your data security posture measures up.

As technology continues to evolve, generative AI techniques are being harnessed to boost performance, while privacy laws undergo significant changes. Data security strategies and technologies must adapt to the risks posed by generative AI and other evolving technologies.

The Hype Cycle shows a comprehensive view of data security, providing security and risk management leaders with the guidance they need to align their strategies with their risk appetite. It covers various aspects of data security, including governance, privacy, data discovery, categorization, data processing, and analytics.

• Data Security Governance, Privacy, and Risk: Explore entries such as data security governance, data risk assessment, privacy impact assessments, data breach response, privacy by design, sovereign data strategies, and FinDRA.
• Data Discovery and Categorization: Delve into data security posture management, data discovery, data classification, and augmented data catalog/metadata management.
• Data Protection Techniques: Discover techniques like encryption, , format-preserving encryption, and enterprise key management.
• Multicloud Platforms: Explore entries for data security as a service and data security platforms.

To navigate this complex landscape, it’s crucial to seek out technologies that integrate multiple security controls to simplify orchestration. Some choices will drive transformative benefits, reducing operational complexity and cost. For instance, the evolution of data security platforms holds immense promise. Vendors are developing techniques to support data security governance through focused data and privacy risk assessments, and data security posture management is poised to revolutionize data risk assessments across various data security technologies. The convergence of financial and security risk management will guide data security investment decisions to align with business goals.

In the 2022 Gartner Shifting Cybersecurity Operating Model Survey, the need for consistency in cybersecurity policies emerged as a primary driver for centralizing cybersecurity risk decision-making. Many organizations are centralizing enterprise cybersecurity decision rights, emphasizing consistency in product functionality and reducing the complexity of policy orchestration. Convergence is the way forward, with various technologies merging to create more effective processes.

One of the standout innovations on the horizon is Data Security Posture Management (DSPM). This transformative technology is set to disrupt the data security landscape. Here’s why it matters:

DSPM is all about discovering previously unknown data across CSPs and categorizing and classifying both unstructured and structured data. As data continues to proliferate across the cloud, DSPM becomes a critical tool for assessing data security posture and identifying exposure to privacy and security risks. It forms the foundation of data risk assessments and the implementation of data security governance policies.

With data multiplying across cloud environments, organizations must grapple with privacy and security risks stemming from undiscovered or unidentified data. DSPM is a game-changer because it creates data maps and analyzes data flows to determine data security posture. It sheds light on data sensitivity, infrastructure configurations, and access privileges. DSPM’s unique ability to discover shadow data is a game-changer, providing critical insights into previously unassessed business risks. It enables consistent data security posture across previously disjointed controls, helping organizations navigate the complexities of data deployments.

Dynamic changes in data pipelines and CSP services create shadow data repositories, potentially leading to risks. Mapping user access to specific datasets was traditionally complex due to siloed data security and identity access management (IAM) products. Organizations now need to track data across various formats and locations. Regulations mandating data risk assessments are on the rise, increasing the need for tools that can assess policy compliance. The need to protect data from exposure due to misconfigurations, access privileges, or data residency risks drives integration with cloud-native application protection platforms.

However, there are challenges to overcome. DSPM products are predominantly offered by early-stage vendors, which may raise concerns for some organizations. Each DSPM product varies in its capabilities, making it difficult to achieve consistency or integration with selected security controls. Currently, DSPM products integrate with a limited set of third-party security products, posing challenges for orchestration and remediation.

Recommendations

• Start with data security governance to identify datasets requiring specific policies to be assessed via DSPM.
• Compare DSPM products to evaluate their ability to find shadow data repositories and integrate with your existing cloud security stack.
• Treat DSPM investments as tactical and consider shorter contract durations as the market matures.
• Evaluate and compare response options among different DSPM tools for creating and updating data maps.
• Identify third-party data security products that can integrate with DSPM and assess their ability to leverage DSPM functionality.

In conclusion, the world of data security is undergoing a seismic shift, driven by emerging technologies and the evolving threat landscape. By embracing innovations like DSPM and staying abreast of the latest trends in data security, organizations can not only protect their valuable data assets but also position themselves for success in an increasingly digital world. Stay tuned for more updates on the ever-evolving journey of data security in the age of quantum computing and AI.