Daniel Suissa

Gartner recently released its much-anticipated 2024 Hype Cycle for Data Security, and the spotlight is shining bright on Data Security Posture Management (DSPM). Described as having a "transformative" potential, DSPM is lauded for its ability to address long-standing data security challenges. 

DSPM solutions are gaining traction to fill visibility gaps as companies rush to the cloud.  Best of breed solutions provide coverage across multi-clouds and on-premises, providing a holistic approach that can become the authoritative inventory of data for an organization - and a useful up-to-date source of contextual detail to inform other security stack tools such as DLPs, CSPMs/CNAPPS, data catalogs, and more, enabling these to work more effectively. Learn more about this in our latest blog, Data: The Unifying Force Behind Disparate GRC Functions.

However, as with any emerging technology, Gartner also highlighted several obstacles that could hinder its widespread adoption. In this blog, we’ll dive into these obstacles, separating the legitimate concerns from those that shouldn't deter any organization from embracing DSPM—especially when using a comprehensive solution like Sentra.

Obstacle 1: Scanning the Entire Infrastructure for Data Can Take Days to Complete

This concern holds some truth, particularly for organizations managing petabytes of data. Full infrastructure scans can indeed take time. However, this doesn’t mean you're left twiddling your thumbs waiting for results. With Sentra, insights start flowing while the scan is still in progress. Our platform is designed to alert you to data vulnerabilities as they’re detected, ensuring you're never in the dark for long. So, while the scan might take days to finish, actionable insights are available much sooner. And scans for changes occur continuously so you’re always up to date.

Obstacle 2: Limited Integration with Security Controls for Remediation

Gartner pointed out that DSPM tools often integrate with a limited set of security controls, potentially complicating remediation efforts. While it’s true that each security solution prioritizes certain integrations, this is not a challenge unique to DSPM. Sentra, for instance, offers dozens of built-in integrations with popular ticketing systems and data remediation tools. Moreover, Sentra enables automated actions like auto-masking and revoking unauthorized access via platforms like Okta, seamlessly fitting into your existing workflow processes and enhancing your cloud security posture.

Obstacle 3: DSPM as a Function within Broader Data Security Suites

Another obstacle Gartner identified is that DSPM is sometimes offered merely as a function within a broader suite of data security offerings, which may not integrate well with other vendor products. This is a valid concern. Many cloud security platforms are introducing DSPM modules, but these often lack the discovery breadth and classification granularity needed for robust and accurate data security.

Sentra takes a different approach by going beyond surface-level vulnerabilities. Our platform uses advanced automatic grouping to create "Data Assets"—groups of files with similar structures, security postures, and business functions. This allows Sentra to reduce petabytes of cloud data into manageable data assets, fully scanning all data types daily without relying on random sampling. This level of detail and continuous monitoring is something many other solutions simply cannot match.

Obstacle 4: Inconsistent Product Capabilities Across Environments

Gartner also highlighted the varying capabilities of DSPM solutions, especially when it comes to mapping user access privileges and tracking data across different environments—on-premises, cloud services, and endpoints. While it’s true that DSPM solutions can differ in their abilities, the key is to choose a platform designed for multi-cloud and hybrid environments. Sentra is built precisely for this purpose, offering robust capabilities to identify and protect data across diverse environments (IaaS, PaaS, SaaS, and On-premises), ensuring consistent security and risk management no matter where your data resides.

Conclusion

While Gartner's 2024 Hype Cycle for Data Security outlines several obstacles to DSPM adoption, many of these challenges are either surmountable or less significant than they might first appear. With the right DSPM solution, organizations can effectively overcome these obstacles and harness the full transformative power of DSPM.

Curious about how Sentra can elevate your data security? 

Request a demo here.

Source code lies at the heart of every technology company’s business. Aside from being the very blueprint upon which the organization relies upon to sell its products, source code can reveal how the business operates, its strategies, and how its infrastructure is designed. Many of the recent data breaches we’ve witnessed, including those against industry leaders like LastPass, Okta, Intel, and Samsung, were instances where attackers were able to gain access to all or part of the organization's source code.

The good news with source code is that we usually know where it originated from, and even where it’s destined to be shipped. The bad news is that code delivery is getting increasingly more complex in order to meet business demands for fast iterations, causing code to pass multiple stations on its way to its final destination. We like to think that the tools we use to ship code protect it well and clean it up where it's no longer needed, but that’s wishful thinking that puts the business at risk. To make matters worse, bad development practices can lead to developer secrets and even customer information being stolen with a source code breach, which can in turn trigger cascading problems. 

At Sentra, we see protecting source code as the heart of protecting an organization’s data. Simply put, code is a qualitative type of data, which means that unlike quantitative data, the impact of the breach does not depend on its scale. Even a small breach can provide the attacker with crucial intellectual property or intel that can be used for follow up attacks. That said, not every piece of code leaked can damage the business in the same way. 

So how do we protect source code in the cloud? 

Visualization

All data protection starts with knowing where the data is and how it’s protected. We always start with the home repository, usually in GitLab, GitHub, or BitBucket. Then we move to data stores that are a part of the code delivery cycle. These can be container-management services like Amazon’s Elastic Containers Service or Azure Container Instances, as well as the VMs running that code. But because code is also used by developers on personal VMs and moved through Data Lakes, Sentra takes a wider approach and looks for source code across all of the organizations’ non-tabular data stores across all IaaS and SaaS services, such as files in Azure Disk Storage volumes attached to Azure VMs.

Classification

We said it before and we’ll say it again - not all data is created equal. Some copies of source code may include intellectual property and some may not. For example, a CPP file with complex logic is not the same as an HTML file distributed by a CDN. On the other hand, that HTML might accidentally contain a developer secret, so we must look for those as well before we label it as ‘non-sensitive’. Classifying exactly what kind of data each particular source code file contains helps us filter out the noise and focus on the most sensitive data. 

Detecting Data Movement

At this point we may know where source code is located and what kind of information it contains, but not how where it came from or how to stop bad data flows that lead to unwanted exposure. Remember, source code is handled both manually and by automatic processes. Sometimes it’s copied in its entirety, and sometimes partially. Detecting how much is copied and through which processes will help us enforce good code handling practices in the organization. Sentra combines multiple methods to identify source code movement at the function level by understanding the organization’s user access scheme, activity, and by looking at the code itself. 

Determining Risk

Security efficiency begins with prioritization. Some of the code we will find in the environment may be properly separated from the world behind a private network, or even encrypted, and some of it may be partially exposed or even publicly accessible. By determining the Data Security Posture of each piece of code we can determine what processes are conducive to the business’ goals and which put it at risk. This is where we combine all of the above steps and determine the risk based on the kind of data in the code, how it is moved, who has access to it, and how well it’s protected. 

Remediation

Now that we understand what source code needs protecting against which risks, and more importantly, what are processes which require the code in each store, we can choose from several remediation tools in our arsenal:

• Encrypt. Often source code is not required to be loaded from rest very-quickly, so it’s alway a good idea to encrypt or obfuscate it. 
• Limiting access to all stores other than the source code repository. 
  
• Use a retention policy anywhere where the code is needed only intermediately. 
• Review old code delivery processes that are no longer needed.
• Remove any shadow data. Code inside unused VMs or old stores that weren't accessed in a while can most probably be removed altogether. 
• Detect and remove any secrets in source code and move them to vaults.
• Detect intellectual property that is used in non-compliant or insecure environments.

Source code is the data that absolutely cannot be allowed to leak. By taking the steps above, Sentra's DSPM ensures that it stays where it’s supposed to be, and always is protected properly. 

Book a demo and learn how Sentra’s solution can redefine your cloud data security landscape.

Businesses must understand where and how their sensitive data is used in their ever-changing data estates because the stakes are higher than ever. IBM’s Cost of a Data Breach 2023 report found that the average global cost of a data breach in 2023 was $4.45 million. And with the rise in generative AI tools, malicious actors develop new attacks and find security vulnerabilities quicker than ever before. 

Even if your organization doesn’t experience a data breach, growing data and privacy regulations could negatively impact your business’s bottom line if not heeded. 

With all of these factors in play, why haven’t many businesses up-leveled their data security and risen to the new challenges? In many cases, it’s because they are leveraging outdated technologies to secure a modern cloud environment. Tools designed for on premises environments often produce too many false positives, require manual setup and constant reconfiguration, and lack complete visibility into multi-cloud environments. To answer these liabilities, many businesses are turning to data security posture management (DSPM), a relatively new approach to data security that focuses on securing data wherever it goes despite the underlying infrastructure. 

Can Legacy Tools Enable Today’s Data Security Best Practices?

As today’s teams look to secure their ever-evolving cloud data stores, a few specific requirements arise. Let’s see how these modern requirements stack up with legacy tools’ capabilities:

Compatibility with a Multi-Cloud Environment

Today, the average organization uses several connected databases, technologies, and storage methods to host its data and operations. Its data estate will likely consist of SaaS applications, a few cloud instances, and, in some cases, on premises data centers. 

Legacy tools are incompatible with many multi-cloud environments because:

• They cannot recognize all the moving parts of a modern cloud environment and treat cloud and SaaS technologies as though they are full members of the IT ecosystem. They may flag normal cloud operations as threats, leading to lots of false positives and noisy alerts.
• They are difficult to maintain in a sprawling cloud environment, as they often require teams to manually configure a connector for each data store. When an organization is spinning up cloud resources rapidly and must connect dozens of stores daily, this process takes tons of effort and limits security, scalability and agility.

Continuous Threat Detection

In addition, today’s businesses need security measures that can keep up with emerging threats. Malicious actors are constantly finding new ways to commit data breaches. For example, generative AI can be used to scan an organization’s environment and identify any weaknesses with unprecedented speed and accuracy. In addition, LLMs often create internal threats which are more prevalent because so many employees have access to sensitive data.

Legacy tools cannot respond adequately to these growing threats because:

• They use signature-based malware detection to detect and contain threats. 
• This technique for detecting risk will inevitably miss novel threats and more nuanced risks within SaaS and cloud environments.

Data-Centric Security Approach

Today’s teams also need a data-centric approach to security. Data democratization happens in most businesses (which is a good thing!). However, this democratization comes with a cost, as it allows any number of employees to access, move, and copy sensitive data. 

In addition, newer applications that feature lots of AI and automation require massive amounts of data to function. As they perform tasks within businesses, these modern applications will share, copy, and transform data at a rapid speed — often at a scale unmanageable via manual processes.

As a result, sensitive data proliferates everywhere in the organization, whether within cloud storage like SharePoint, as part of data pipelines for modern applications, or even as downloaded files on an employee’s computer.

Legacy tools tend to be ineffective in finding data across the organization because:

• Legacy tools’ best defense against this proliferation is to block any actions that look risky. These hyperactive security defenses become “red tape” for employees  or connected applications that just need to access the data to do their jobs. 
• They also trigger false alarms frequently and tend to miss important signals, such as suspicious activities in SaaS applications.

Accurate Data Classification

Modern organizations also need the ability to classify discovered data in precise and granular ways. The likelihood of exposure for any given data will depend on several contextual factors, including location, usage, and the level of security surrounding it. 

Legacy tools fall short in this area because:

• They cannot classify data with this level of granularity, which, again, leads to false positives and noisy alerts.
• There is inadequate data context to determine the true sensitivity based on business use
• Many tools also require agents or sidecars to start classifying data, which requires extensive time and work to set up and maintain.

Big-Picture Visibility of Risk

Organizations require a big-picture view of data context, movement, and risk to successfully monitor the entire data estate. This is especially important because the risk landscape in a modern data environment is extremely prone to change. In addition, many data and privacy regulations require businesses to understand how and where they leverage PII. 

Legacy tools make it difficult for organizations to stay on top of these changes because:

• Legacy tools can only monitor data stored in on premises storage and SaaS applications, leaving cloud technologies like IaaS and PaaS unaccounted for.
• Legacy tools fail to meet emerging regulations. For example, a new addendum to GDPR requires companies to tell individuals how and where they leverage their personal data. It’s difficult to follow these guidelines if you can’t figure out where this sensitive data resides in the first place.

Data Security Posture Management (DSPM): A Modern Approach

As we can see, legacy data security tools lack key functionality to meet the demands of a modern hybrid environment. Instead, today’s organizations need a solution that can secure all areas of their data estate — cloud, on premises, SaaS applications, and more. 

Data Security Posture Management (also known as DSPM) is a modern approach that works alongside the complexity and breadth of a modern cloud environment. It offers automated data discovery and classification, continuous monitoring of data movement and access, and a deep focus on data-centric security that goes far beyond just defending network perimeters. 

Key Features of Legacy Data Security Tools vs. DSPM

But how does DSPM stack up against some specific legacy tools? Let’s dive into some one-to-one comparisons.

How does DSPM integrate with existing security tools?

DSPM integrates seamlessly with other security tools, such as team collaboration tools (Microsoft Teams, Slack, etc.), observability tools (Datadog), security and incident response tools (such as SIEMs, SOARs, and Jira/ServiceNow ITSM), and more.

Can DSPM help my existing data loss prevention system?

DSPM integrates with existing DLP solutions, providing rich context regarding data sensitivity that can be used to better prioritize remediation efforts/actions. DSPM provides accurate, granular sensitivity labels that can facilitate confident automated actions and better streamline processes.

What are the benefits of using DSPM?

DSPM enables businesses to take a proactive approach to data security, leading to:

• Reduced risk of data breaches
• Improved compliance posture
• Faster incident response times
• Optimized security resource allocation

Embrace DSPM for a Future-Proof Security Strategy

Embracing DSPM for your organization doesn’t just support your proactive security initiatives today; it ensures that your data security measures will scale up with your business’s growth tomorrow. Because today’s data estates evolve so rapidly — both in number of components and in data proliferation — it’s in your business’s best interest to find cloud-native solutions that will adapt to these changes seamlessly. 

Learn how Sentra’s DSPM can help your team gain data visibility within minutes of deployment.

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What is a Cloud Security Strategy?

During the initial phases of digital transformation, organizations may view cloud services as an extension of their traditional data centers. But to fully harness cloud security, there must be progression beyond this view.

A cloud security strategy is an extensive framework that outlines how an organization manages its dynamic, software-defined security ecosystem and protects its cloud-based assets. Security, in its essence, is about managing risk – addressing the probability and impact of attacks instead of eliminating them outright. This reality essentially positions security as a continuous endeavor rather than being a finite problem with a singular solution.

Cloud security strategy advocates for:

• Ensuring the cloud framework’s integrity: Involves implementing security controls as a foundational part of cloud service planning and operational processes. The aim is to ensure that security measures are a seamless part of the cloud environment, guarding every resource.
  
• Harnessing cloud capabilities for defense: Employing the cloud as a force multiplier to bolster overall security posture. This shift in strategy leverages the cloud's agility and advanced capabilities to enhance security mechanisms, particularly those natively integrated into the cloud infrastructure.

Why is a Cloud Security Strategy Important?

Some organizations make the mistake of miscalculating the duality of productivity and security. They often learn the hard way that while innovation drives competitiveness, robust security preserves it. The absence of either can lead to diminished market presence or organizational failure. As such, a balanced focus on both fronts is paramount.

Customers are more likely to do business with organizations that consistently retain the trust to protect proprietary data. When a single instance of a data breach or a security incident that can erode customer trust and damage an organization's reputation, the stakes are naturally high. A cloud security strategy can help organizations address these challenges by providing a framework for managing risk.

A well-crafted cloud security strategy will include the following:

• Risk assessment to identify and prioritize the organization's key security risks.
• Set of security controls to mitigate those risks.
• Process framework for monitoring and improving the security posture of the cloud environment over time.

Key Elements of a Cloud Security Strategy

Tactically, a cloud security strategy empowers organizations to navigate the complexities of shared responsibility models, where the burden of security is divided between the cloud provider and the client.

Key Challenges in Building a Cloud Security Strategy

When organizations shift from on-premises to cloud computing, the biggest stumbling block is their lack of expertise in dealing with a decentralized environment.

Some consider agility and performance to be the super-features that led them to adopt the cloud. Anything that impacts the velocity of deployment is met with resistance. As a result, the challenge often lies in finding the sweet spot between achieving efficiency and administering robust security. But in reality, there are several factors that compound the complexity of this challenge.

Lack of Visibility

If your organization lacks insight into its cloud activity, it cannot accurately assess the associated risks. Lack of visibility also introduces multifaceted challenges. Initially, it can be about cataloging active elements in your cloud. Subsequently, it can restrain comprehension of the data, operation, and interconnections of those systems.

Imagine manually checking each cloud service across different HA zones for each provider. You'd be manifesting virtual machines, surveying databases, and tracking user accounts. It's a complex task which can rapidly become unmanageable.

Most major cloud service providers (CSPs) offer monitoring services to streamline this complexity into a more efficient strategy. But even with these tools, you mostly see the numbers—data stores, resources—but not the substance within or their inter-relationship. In reality, a production-grade observability stack depends on a mix of CSP provider tools, third-party services, and architecture blueprints to assess the security landscape.

Human Errors

Surprisingly, the most significant cloud security threat originates from your own IT team's oversights. Gartner estimates that by 2025, a staggering 99% of cloud security failures will be due to human errors.

One contributing factor is the shift to the cloud which demands specialized skills. Seasoned IT professionals who are already well-versed in on-prem security may potentially mishandle cloud platforms. These lapses usually involve issues like misconfigured storage buckets, exposed network ports, or insecure use of accounts. Such mistakes, if unnoticed, offer attackers easy pathways to infiltrate cloud environments.

An organization can likely utilize a mix of service models—Infrastructure as a Service (IaaS) for foundational compute resources, Platform as a Service (PaaS) for middleware orchestration, and Software as a Service (SaaS) for on-demand applications. For each tier, manual security controls might entail crafting bespoke policies for every service. This method provides meticulous oversight, albeit with considerable demands on time and the ever-present risk of human error.

Misconfiguration

OWASP highlights that around 4.51% of applications become susceptible when wrongly configured or deployed. The dynamism of cloud environments, where assets are constantly deployed and updated, exacerbates this risk.

While human errors are more about the skills gap and oversight, the root of misconfiguration often lies in the complexity of an environment, particularly when a deployment doesn’t follow best practices. Cloud setups are intricate, where each change or a newly deployed service can introduce the potential for error. And as cloud offerings evolve, so do the configuration parameters, subsequently increasing the likelihood of oversight.

Some argue that it’s the cloud provider that ensures the security of the cloud. Yet, the shared responsibility model places a significant portion of the configuration management on the user. Besides the lack of clarity, this division often leads to gaps in security postures.

Automated tools can help but have their own limitations. They require precise tuning to recognize the correct configurations for a given context. Without comprehensive visibility and understanding of the environment, these tools tend to miss critical misconfigurations.

Compliance with Regulatory Standards

When your cloud environment sprawls across jurisdictions, adherence to regulatory standards is naturally a complex affair. Each region comes with its mandates, and cloud services must align with them. Data protection laws like GDPR or HIPAA additionally demand strict handling and storage of sensitive information.

The key to compliance in the cloud is a thorough understanding of data residency, how it is protected, and who has access to it. A thorough understanding of the shared responsibility model is also crucial in such settings. While cloud providers ensure their infrastructure meets compliance standards, it's up to organizations to maintain data integrity, secure their applications, and verify third-party services for compliance.

Modern Cloud Security Strategy Principles

Because the cloud-native ecosystem is still an emerging discipline with a high degree of process variations, a successful security strategy calls for a nuanced approach. Implementing security should start with low-friction changes to workflows, the development processes, and the infrastructure that hosts the workload.

Here’s how it can be imagined:

Establishing Comprehensive Visibility

Visibility is the foundational starting point. Total, accessible visibility across the cloud environment helps achieve a deeper understanding of your systems' interactions and behaviors by offering a clear mapping of how data moves and is processed.

Establish a model where teams can achieve up-to-date, easy-to-digest overviews of their cloud assets, understand their configuration, and recognize how data flows between them. Visibility also lays the foundation for traceability and observability. Modern performance analysis stacks leverage the principle of visibility, which eventually leads to traceability—the ability to follow actions through your systems. And then to observability—gaining insight from what your systems output.

Enabling Business Agility

The cloud is known for its agile nature that enables organizations to respond swiftly to market changes, demands, and opportunities. Yet, this very flexibility requires a security framework that is both robust and adaptable. Security measures must protect assets without hindering the speed and flexibility that give cloud-based businesses their edge.

To truly scale and enhance efficiency, your security strategy must blend the organization’s technology, structure, and processes together. This ensures that the security framework is capable of supporting fast-paced development cycles, ensures compliance, and fosters innovation without compromising on protection. In practice, this means integrating security into the development lifecycle from its initial stages, automating security processes where possible, and ensuring that security protocols can accommodate the rapid deployment of services.

Cross-Functional Coordination

A future-focused security strategy acknowledges the need for agility in both action and thought. A crucial aspect of a robust cloud security strategy is avoiding the pitfall where accountability for security risks is mistakenly assigned to security teams rather than to the business owners of the assets. Such misplacement arises from the misconception of security as a static technical hurdle rather than the dynamic risk it can introduce.

Security cannot be a siloed function; instead, every stakeholder has a part to play in securing cloud assets. The success of your security strategy is largely influenced by distinguishing between healthy and unhealthy friction within DevOps and IT workflows. The strategic approach blends security seamlessly into cloud operations, challenging teams to preemptively consider potential threats during design and to rectify vulnerabilities early in the development process. This constructive friction strengthens systems against attacks, much like stress tests to inspect the resilience of a system.

However, the practicality of security in a dynamic cloud setting demands more than stringent measures; it requires smart, adaptive protocols. Excessive safeguards that result in frequent false positives or overcomplicate risk assessments can impact the rapid development cycles characteristic of cloud environments. To counteract this, maintaining the health of relationships within and across teams is essential.

Ongoing and Continuous Improvement

Adopting agile security practices involves shifting from a perfectionist mindset to embracing a baseline of “minimum viable security.” This baseline evolves through continuous incremental improvements, matching the agility of cloud development. In a production-grade environment, this relies on a data-driven approach where user experiences, system performance, and security incidents shape the evolution of the platform.

The commitment to continuous improvement means that no system is ever "finished." Security is seen as an ongoing process, where DevSecOps practices can ensure that every code commit is evaluated against security benchmarks, allowing for immediate correction and learning from any identified issues.

To truly embody continuous improvement though, organizations must foster a culture that encourages experimentation and learning from failures. Blameless postmortems following security incidents, for example, can uncover root causes without fear of retribution, ensuring that each issue is a learning opportunity.

Preventing Security Vulnerabilities Early

A forward-thinking security strategy focuses on preempting risks. The 'shift left' concept evolved to solve this problem by integrating security practices at the very beginning and throughout the application development lifecycle. Practically, this approach embeds security tools and checks into the pipeline where the code is written, tested, and deployed.

Start with outlining a concise strategy document that defines your shift-left approach. It needs a clear vision, designated roles, milestones, and clear metrics. For large corporations, this could be a complex yet indispensable task—requiring thorough mapping of software development across different teams and possibly external vendors.

The aim here is to chart out the lifecycle of software from development to deployment, identifying the people involved, the processes followed, and the technologies used. A successful approach to early vulnerability prevention also includes a comprehensive strategy for supply chain risk management. This involves scrutinizing open-source components for vulnerabilities and establishing a robust process for regularly updating dependencies.

How to Create a Robust Cloud Security Strategy

Before developing a security strategy, assess the inherent risks your organization may be susceptible to. The findings of the risk assessment should be treated as the baseline to develop a security architecture that aligns with your cloud environment's business goals and risk tolerance.

In most cases, a cloud security architecture should include the following combination of technical, administrative and physical controls for comprehensive security:

Access and Authentication Controls

The foundational principle of cloud security is to ensure that only authorized users can access your environment. The emphasis should be on strong, adaptive authentication mechanisms that can respond to varying risk levels.

Build an authentication framework that is non-static. It should scale with risk, assessing context, user behavior, and threat intelligence. This adaptability ensures that security is not a rigid gate but a responsive, intelligent gateway that can be configured to suit the complexity of different cloud environments and sophisticated threat actors.

Actionable Steps

• Enforce passwordless or multi-factor authentication (MFA) mechanisms to support a dynamic security ethos.
• Adjust permissions dynamically based on contextual data.
• Integrate real-time risk assessments that actively shape and direct access control measures.
• Employ AI mechanisms for behavioral analytics and adaptive challenges.
• Develop a trust-based security perimeter centered around user identity.

Identify and Classify Sensitive Data

Before classification, locate sensitive cloud data first. Implement enterprise-grade data discovery tools and advanced scanning algorithms that seamlessly integrate with cloud storage services to detect sensitive data points.

Once identified, the data should be tagged with metadata that reflects its sensitivity level; typically by using automated classification frameworks capable of processing large datasets at scale. These systems should be configured to recognize various data privacy regulations (like GDPR, HIPAA, etc.) and proprietary sensitivity levels.

Actionable Steps

• Establish a data governance framework agile enough to adapt to the cloud's fluid nature.
• Create an indexed inventory of data assets, which is essential for real-time risk assessment and for implementing fine-grained access controls.
• Ensure the classification system is backed by policies that dynamically adjust controls based on the data’s changing context and content.

Monitoring and Auditing

Define a monitoring strategy that delivers service visibility across all layers and dimensions. A recommended practice is to balance in-depth telemetry collection with a broad, end-to-end view and east-west monitoring that encompasses all aspects of service health.

Treat each dimension as crucial—depth ensures you're catching the right data, breadth ensures you're seeing the whole picture, and the east-west focus ensures you're always tuned into availability, performance, security, and continuity. This tri-dimensional strategy also allows for continuous compliance checks against industry standards, while helping with automated remediation actions in cases of deviations.

Actionable Steps

• Implement deep-dive telemetry to gather detailed data on transactions, system performance, and potential security events.
• Utilize specialized monitoring agents that span across the stack, providing insights into the OS, applications, and services.
• Ensure full visibility by correlating events across networks, servers, databases, and application performance.
• Deploy network traffic analysis to track lateral movement within the cloud, which is indicative of potential security threats.

Data Encryption and Tokenization

Construct a comprehensive approach that embeds security within the data itself. This strategy ensures data remains indecipherable and useless to unauthorized entities, both at rest and in transit.

When encrypting data at rest, protocols like AES-256 ensure that should the physical security controls fail, the data remains worthless to unauthorized users. For data in transit, TLS secures the channels over which data travels to prevent interceptions and leaks.

Tokenization takes a different approach by swapping out sensitive data with unique symbols (also known as tokens) to keep the real data secure. Tokens can safely move through systems and networks without revealing what they stand for.

Actionable Steps

• Embrace strong encryption for data at rest to render it inaccessible to intruders. Implement industry-standard protocols such as AES-256 for storage and database encryption.
• Mandate TLS protocols to safeguard data in transit, eliminating vulnerabilities during data movement across the cloud ecosystem.
• Adopt tokenization to substitute sensitive data elements with non-sensitive tokens. This renders the data non-exploitable in its tokenized form.
• Isolate the tokenization system, maintaining the token mappings in a highly restricted environment detached from the operational cloud services.

Incident Response and Disaster Recovery

Modern disaster recovery (DR) strategies are typically centered around intelligent, automated, and geographically diverse backups. With that in mind, design your infrastructure in a way that anticipates failure, with planning focused on rapid failback.

Planning for the unknown essentially means preparing for all outage permutations. Classify and prepare for the broader impact of outages, which encompass security, connectivity, and access.

Define your recovery time objective (RTO) and recovery point objective (RPO) based on data volatility. For critical, frequently modified data, aim for a low RPO and adjust RTO to the shortest feasible downtime.

Actionable Steps

• Implement smart backups that are automated, redundant, and cross-zone.
• Develop incident response protocols specific to the cloud. Keep these dynamic while testing them frequently.
• Diligently choose between active-active or active-passive configurations to balance expense and complexity.
• Focus on quick isolation and recovery by using the cloud's flexibility to your advantage.

Conclusion

Organizations must discard the misconception that what worked within the confines of traditional data centers will suffice in the cloud. Sticking to traditional on-premises security solutions and focusing solely on perimeter defense is irrelevant in the cloud arena. The traditional model—where data was a static entity within an organization’s stronghold—is now also obsolete.

Like earlier shifts in computing, the modern IT landscape demands fresh approaches and agile thinking to neutralize cloud-centric threats. The challenge is to reimagine cloud data security from the ground up, shifting focus from infrastructure to the data itself.

Sentra's innovative data-centric approach, which focuses on Data Security Posture Management (DSPM), emphasizes the importance of protecting sensitive data in all its forms. This ensures the security of data whether at rest, in motion, or even during transitions across platforms.

Book a demo to explore how Sentra's solutions can transform your approach to your enterprise's cloud security strategy.

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