Rumor has it: By 2025, over 175 zettabytes will be pushed to the cloud. With scattered sensitive data across multiple cloud platforms and hundreds of services, the increase of shadow data – unmanaged data residing outside the security team’s control – has imploded, leading to a new era of security challenges in the cloud.
Major challenges in securing sensitive data in the cloud:
And that’s why we’ve seen the rise of data security posture management (DSPM). DSPM is designed to continuously monitor data in the cloud to protect against vulnerabilities and potential risks. Per Gartner’s definition, “[DSPM] provides visibility as to where sensitive data is, who has access to that data, how it has been used, and what the security posture of the data stored, or application is.” DSPM provides actionable insights to improve data security posture, enabling security teams to protect sensitive data with intelligence and context.
With these challenges in mind, here are the top 5 requirements you should look for in your next DSPM solution:
1. Data discovery, classification, exposure, and posture management
Visibility and inventory of your environment is critical in the attempt to secure cloud data due to the complex nature of cloud environments. It is important that your DSPM solution is capable of scanning cloud data repositories to discover cloud native structured and unstructured data stores, which in turn provides a clear image of the data landscape, inventory, and security posture.
Given that all data is not created equally, accurate data classification by your DSPM solution is vital. This can be achieved through a combination of techniques including content analysis, AI, machine learning, metadata, or tagging. Upon data classification, your DSPM solution should provide deep context and insight into sensitive data across the ecosystem. Its capabilities should include assessing data security posture and identifying data exposures, misconfigurations, and overly permissive access that could lead to a data leak. Additionally, it should alert security teams when new data stores or objects that could potentially be at risk are discovered, creating a precise map and inventory of the organization’s data assets. This activity enables the security team to understand the whereabouts of sensitive data, who has access to it, where it’s heading, and its level of security.
2. Single DLP engine across your entire enterprise
Understanding the whereabouts, movement, and exposure of sensitive information is crucial for security teams in any organization utilizing a diverse range of data and cloud services. This understanding allows them to avoid potential data leakage and avert data exfiltration attempts. Consistent implementation and enforcement of data security policies that can identify and rectify breaches both on-premise and in the cloud is equally critical.
Adopting a unified Data Loss Prevention (DLP) engine for your entire data protection strategy can be extremely beneficial for organizations. A single policy crafted by the organization can be applied across all enterprise levels, ensuring the optimal tracking and consistent safeguarding of sensitive data. This applies regardless of the location or the mode of access to the data, thereby cutting down the expenses and intricacies associated with deploying and managing complicated policies.
3. Advanced AI/ML for Threat Correlation
In an elaborate setting, managing data security risks can pose a challenging task, more so if an organization depends on an ecosystem of multiple independent cloud and security point products with disconnected metrics and high frequency alerts. Adopting a risk-based prioritization methodology is fundamental to control data risks in such complex settings while dealing with numerous security alerts. This will allow teams to concentrate on addressing the most severe risks.
It’s crucial for your DSPM to utilize AI, ML, and cutting-edge threat correlation functionality. This will allow it to gather and convert security information into valuable insights effectively. These insights will reveal hidden dangers or attack channels which could cause a security breach. These systems can be reinforced with alerts and notifications in near-real-time, together with remediation advice. This allows your security crew to concentrate on what’s truly important.
4. Multicloud support
Today, many corporations are adopting a multicloud approach. This means utilizing more than one cloud service provider (CSP). While this method offers several advantages, tracking data becomes more difficult as the multicloud scheme becomes more intricate. On-site data security solutions, such as DLP, can’t expand to fit the cloud. Solutions provided by native cloud providers are also limited and do not support the multicloud environment.
Your DSPM should effortlessly cover diverse cloud environments and pull from different databases, data pipelines, object storage, disk storage, managed file storages, data warehouses, lakes, and analytics pipelines. This includes both managed and self-hosted systems. It’s key that your DSPM offers a unified, consistent perspective of data across clouds, geographical areas, and organizational borders. This unified perspective allows security teams to assess the risk level associated with sensitive data across various cloud environments, as opposed to each one individually.
5. Compliance management
Data protection legislation such as GDPR, HIPAA, PCI compliance, and others require careful handling of sensitive information. You need to be aware of the nature of your sensitive data and how and where it is being accessed, as well as what specific guidelines apply to that data, for instance, data residency rules or the right to be forgotten.
Your DSPM tool should support streamlined compliance procedures related to data security, with capabilities like automated matching of data attitudes with both internal and external regulatory reference points linked to GDPR, HIPAA, PCI DSS, etc. The system should also raise alerts to notify security teams or relevant stakeholders about what configuration glitch or problem is causing a breach in compliance, which assets it involves, the at-risk regulations, and the risk’s seriousness. It makes it easier for relevant stakeholders to assess the compliance rate and identify deficits. DSPM should also offer suggestions for rectification to lessen the risk associated to access controls and configuration mishaps. This helps an organization easily meet several data protection criteria like HIPAA, GDPR, and others. The DSPM tool can also simplify the typically manual, cumbersome, and time-consuming aspects of compliance reporting. A DSPM tool offers unified automated simple, audit-ready compliance reporting, making it easier for compliance and security personnel to monitor compliance with relevant regulations.
Zscaler DSPM
Zscaler AI Data Protection Platform is the globe’s most thorough fully combined data protection platform that secures both structured and unstructured data across the web, SaaS-based services, public cloud environments (AWS, Azure, GCP), private applications, email, and endpoints.
Zscaler Data Security Posture Management (DSPM) supplies granular visibility into cloud data, classifies, and recognizes data and access, and contextualize the data’s exposure and security position, empowering organizations, and security teams to avoid and remediate cloud data breaches at scale.
Zscaler DSPM belongs to Zscaler Data Protection that offers a thorough, cloud-supplied platform designed to safeguard sensitive data within your entire enterprise – web, SaaS, on-prem applications, endpoints, BYOD devices, and public cloud. It uses a single and unified DLP engine to deliver consistent, top of the line data protection across all channels. By trailing all users across all locations, and governing data in use and at rest, it guarantees sensitive data is constantly protected and compliance is fulfilled.
For more info visit, check out our recent DSPM launch webinar!