A Guide to Data Security Posture Management (DSPM)

Data Protection

In today’s world of speed and convenience, cloud computing has revolutionized where and how companies store their data as more migrate to the cloud. One of the main benefits is that it offers organizations immense cost savings by outsourcing infrastructure and giving them the flexibility to pay only for the resources used. Additionally, the cloud allows people to access files and resources from anywhere in the world which makes collaboration much easier in a remote work environment.

However, the lower costs and better scalability of the cloud do not come without their consequences. With data growing faster and in more places every day, cloud data security has become a top concern for security professionals.

What Is Data Security Posture Management?

DSPM is an essential strategy that security and IT teams use to automatically identify and protect their sensitive data, reducing their organization’s risk of data leaks, compliance violations and much more.

Data security posture management helps organizations discover and understand their cloud data in depth, take actionable steps to protect or remediate it, and continually assess their cloud data security risk.

How to Assess Cloud Data Security Vulnerabilities

Companies must know what type of sensitive data it has and where it is stored to ensure that it is in a secure location and only accessible by authorized users. Without an accurate and up-to-date inventory, they have no way of guaranteeing sensitive and regulated data remains confidential and compliant.

Examining your data visibility is an efficient way to assess your cloud data security vulnerabilities. Improving your security risk posture in the cloud requires you to have control across all of your data. Without proper knowledge of what exact data is being stored, your security team won’t be able to fully manage risk across the multi-cloud. Taking a data centric approach will allow you to automatically map, monitor and remediate your data—all in one cloud data security platform.

451 & BigID Research Report for Cloud Data Security
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Challenges in Cloud Data Protection

One of the main reasons why cloud data security has become a top priority is that companies store a lot of information in the cloud, including all types of sensitive information—like intellectual property, finance data, customer data, protected health information (PHI), and payment card information (PCI). Due to the rapid growth of cloud data, companies may not know where all data is stored or how it is used, especially unknown dark data. You can’t protect what you don’t know, leaving sensitive and regulated data open to breaches and leaks.

The prevalence of different data types outside traditional structured databases also creates a major challenge for organizations looking to keep an accurate and up-to-date inventory of all of their data. Many existing cloud data security solutions fail to properly scan unstructured and semi-structured data types such as files, documents, and images. This leaves a large gap for sensitive data to go unprotected and remain vulnerable to breaches and leaks. As a result, organizations are blind without context on what data needs to be prioritized and protected and where it’s hiding. You may end up storing sensitive and regulated data in the same way as the rest of your data, creating major security risks.

Organizations also lack a consolidated view of data across different cloud service providers and SaaS applications, leading to lower visibility and inconsistent security controls. This can result in critical issues such as users getting unauthorized access to sensitive data, non-compliance with global regulations like the General Data Protection Regulation (GDPR) and Health Insurance Portability and Accountability Act (HIPAA), and improper storage of personal data — just to name a few. Companies must know what type of sensitive data it has and where it is stored to ensure that it is in a secure location and only accessible by authorized users. Without an accurate and up-to-date inventory, they have no way of guaranteeing sensitive and regulated data remains confidential and compliant.

Although the cloud allows for scale and flexibility, organizations struggle with enforcing global data regulations across their entire data catalog. Many are in the dark regarding the locality of their data, how it was collected, and how it’s being used. This can lead to expensive fines and penalties levied due to non-compliance. Not only will companies experience heavy financial losses, but they will suffer from the loss of trust and goodwill from customers and prospects. The combined reputation loss and resource burden will cause short-term business disruptions and long-term damage.

As more organizations migrate to the cloud, it’s critical for them to assess their cloud data security posture. In this guide, we will discuss best practices to protect your cloud data and stay compliant with global regulations.

Best Practices to Improve Cloud Data Security Posture

1. Understand what data you have in the cloud

The first step in protecting your data is to understand what data you’re storing in the cloud in the first place: being able to identify what it is, how important or sensitive it is, whose it is, and where it is.

If you don’t know where your sensitive data is, how can you take steps to protect it? Building and maintaining an accurate data inventory creates the critical foundation to assess your current cloud data security posture. Organizations must discover what type of data they have, where it is stored, and how it is being used, so they know where all of their sensitive data is hiding.

It’s the first step to being able to protect that data, enforce controls around it, and improve your risk posture.

2. Gain complete visibility of multi cloud and hybrid cloud in a unified view

Companies that lack the infrastructure to scan for unstructured, structured, and dark data will be much more vulnerable to security threats and breaches.

Advanced data classification is critical to provide accurate context on what type of data was found. This allows for organizations to identify and categorize sensitive data amongst all of their data, and easily classify all of your cloud data with accuracy and scale to achieve protection and compliance.

Additionally, organizations must have a centralized view of all of their cloud data across different service providers and applications in the multi-cloud. This gives them a complete overview of their cloud data security posture and provides clarity on areas to focus on based on sensitivity and policies. Different types of data require different security controls and handling methods — you wouldn’t treat car model data in the same way as social security number data, right? Highly valuable and sensitive data should be prioritized first since they pose the highest risk in security and compliance.

3. Reduce your attack surface

After an organization finds and classifies all of its data, its next focus should be on data minimization: reducing the amount of sensitive data they store in the first place. The goal is to reduce your attack surface so those with malicious intent have less data to target, making it more difficult for them to find the sensitive data they’re looking for. Protecting and managing cloud data becomes a faster and simpler process with less data stored in fewer places. In addition to the security benefits, data minimization also helps reduce the amount of data that must be monitored for regulatory compliance, saving organizations time and resources.

Data minimization can be achieved through:

  • Limiting the collection of data to only what is relevant and necessary to achieve a purpose
  • Retaining data for only as long as it is needed
  • Identifying and reducing duplicate, redundant, stale, and similar data

Organizations with an accurate inventory of all of their data will have a much easier task in minimizing their data. By knowing what data they have and where it is stored, they can find problem areas to update what and how data is being collected, delete unnecessary data, and secure sensitive data that is needed.

Data minimization helps organizations reduce their risk of breaches and data leaks, simplify compliance for global regulations, allow for faster data scans and identification, and lower operating costs. The compounding benefits of this strategy make it a critical component for cloud data security posture management.

4. Monitor your data and keep an up-to-date cloud data inventory

It’s not only enough to have a current inventory of all of your data but also to maintain it and keep it up-to-date. Cloud data security is a dynamic process that requires regular monitoring and updates as your data changes. New data is created every day and old data is constantly being modified, so it’s important to have a system in place that can keep track of these changes.

Your organizations should consider using an automated cloud data security solution that can help you easily inventory your data, dynamically monitor for changes, and update your inventory in real-time. This will help ensure that you always have an accurate picture of your data and can take the necessary steps to protect it.

Keeping an up-to-date cloud data inventory is a critical part of managing your organization’s cloud data security posture. Automated solutions make it easier to keep track of your data and ensure that you always have an accurate picture of what you have and where it is. This allows you to monitor and see at a quick glance where there are potential security and compliance risks due to improper storage or access.

Leverage SmallID to Protect Your Cloud Data

The massive migration of data to the cloud has made cloud data security posture management (DSPM) a top priority for security professionals. Today’s organizations require a cloud-native data security solution that offers high accuracy in data discovery and classification, fast time-to-value, and flexibility in scale based on their data.

SmallID brings unmatched native coverage for data across cloud service providers like AWS, Azure, GCP and SaaS apps like Salesforce, ServiceNow, Slack, GitHub, and GDrive. Organizations can easily connect and scan data across multiple sources, giving them a centralized view of all of their data. With this, you’ll gain complete visibility across your data landscape, shine a light on dark data, eliminating vulnerable blind spots.

The next step? Automatically classifying sensitive, regulated, and valuable data with accuracy, reducing manual resources and accelerating time to value. Using SmallID’s advanced data discovery and classification, organizations can know exactly where to prioritize based on sensitivity and risk and reduce their attack surface to defend against data leaks.

SmallID is on-demand data protection and data discovery, built on years of advanced ML classification for a modern data environment. Whether you need to scan 1 TB or 50 TB, SmallID provides flexible pricing tiers based on data scan volume.

Schedule a demo with our team and see how SmallID can improve your cloud data security posture in minutes.