Data Security Best Practices: Mitigate Risk

Advanced data security best practices for modern enterprises

Your enterprise data is growing exponentially. And while cloud computing revolutionizes how you manage it, this digital transformation introduces new security challenges you need to address head-on.

Today’s organizations face sophisticated cyberattacks that evolve faster than traditional security measures to protect data can adapt. From targeted phishing campaigns and ransomware to advanced persistent threats, you need robust protection for sensitive information across all environments, along with strong recovery capabilities to quickly bring your business back up and running.

In 2024, cloud-based data breaches cost organizations an average of $5.17 millionopens in a new tab. With strict global privacy regulations like GDPR and CCPA demanding enhanced security measures, protecting your data isn’t just about security, but also about business survival.

Your modern enterprise environment can compound these challenges. As you expand across multicloud and hybrid infrastructures, support remote teams, and integrate IoT devices, you need data protection techniques beyond basic management practices and a strategic approach that aligns data security best practices with your core business objectives.

Aligning data security with strategic business objectives

When cybersecurity becomes integral to your organizational culture, you create a foundation where stakeholders understand their role in protecting critical assets. This cultural shift ensures security receives the attention and resources it needs at every level of your business.

Risk-based frameworks and prioritization

To build an effective security strategy, it’s essential to engage with stakeholders across your organization to identify priority risks that could impact your business objectives. Start with a thorough risk evaluation that assesses the likelihood and potential impact of each threat, using specialized tools to categorize risks by severity and frequency. This assessment helps you develop targeted mitigation strategies that protect your business from disruption.

Leading frameworks, such as the NIST Cybersecurity Framework (CSF)opens in a new tab and ISO 27001opens in a new tab, offer proven methodologies for identifying and managing cybersecurity risks. While the NIST CSF provides flexibility in implementation, ISO 27001 delivers a structured path to establishing an Information Security Management System (ISMS). You'll need to adapt either framework to your specific risk profile.

Your risk-based strategy should focus resources where they matter most. For example, an organization might identify outdated software as a high-risk vulnerability due to known exploits. By prioritizing these updates over minor configuration changes, they protected their most sensitive data while maximizing their security investment.

Data classification and contextual security controls

Advanced data classification helps inform and strengthen your cybersecurity governance. By categorizing data based on sensitivity and usage context and defining your criteria for accepting and avoiding cyber risk for various classifications of data, you can implement precise security measures. Context-based classification also gives you insights into data origin, timestamps, and user interactions, enabling targeted protection strategies.

Implement attribute-based access control (ABAC) to ensure only authorized personnel can access sensitive information based on specific user and data attributes. Complement this with just-in-time access, providing critical data access only when needed, significantly reducing unauthorized exposure risks.

How to secure data: Architecting a resilient security infrastructure

Building a strong data security posture requires proactive and adaptive strategies that help you manage evolving threats. Integrating real-time threat detection and response capabilities creates a dynamic infrastructure that evolves with your security needs. Understanding how to ensure data security through a multi-layered approach enables you to detect, respond to, and recover from security incidents while maintaining business continuity.

Zero Trust architectures and beyond

When implementing Zero-Trust architectures in your complex, hybrid environments, you'll need advanced network access control systems and strategic network segmentation for your most sensitive areas. Here are some key ways to protect data:

Micro-segmentation

Divide your network into smaller, isolated segments, each protected by stringent security controls that limit lateral movement and contain potential breaches. For example, if you're a financial institution, you might segment your network into distinct zones with strict access controls for customer data, transaction processing, and internal communications.

Continuous authentication

Verify user identities throughout their session, not just at log in. You can implement biometric verification or behavioral analytics to continuously assess user activity patterns, automatically adjusting access rights when anomalies are detected.

Context-aware policies

Adapt access permissions based on user role, device security posture, and location. For instance, you might allow employees to access sensitive applications only when connected through a secure VPN on a corporate device while restricting access from personal devices or unsecured networks.

These techniques create an end-to-end Zero Trust architecture that fortifies your network against lateral movement and data exfiltration. Consider how this works in practice: when your employee attempts to access a customer database, the Zero Trust model requires not only valid credentials but also checks on contextual device health, location, and access time. If a compromised account tries to access other systems, your segmented architecture automatically denies access until the verification process is completed.

Cloud-native security controls and multicloud strategies

Managing security across multiple cloud environments demands a sophisticated approach to policy implementation. By establishing unified security standards, you build an integrated framework that streamlines audits, enhances compliance, and aligns all teams with essential security protocols. Here are some tips on how to achieve this:

Cloud-native encryption: Use each cloud provider's native encryption capabilities to protect data throughout its lifecycle. This includes encrypting data at rest in storage, in transit between services, and during processing, ensuring complete protection across your environments.
Identity services: Deploy a centralized identity and access management (IAM) solution with single sign-on (SSO) and multifactor authentication (MFA). This approach streamlines user access, providing detailed audit trails and granular control over permissions across all cloud platforms.
Threat detection: Implement cloud-native threat detection tools that provide real-time monitoring and analytics across your environments. These tools use advanced algorithms to identify patterns of suspicious behavior, correlate security events, and alert your team to potential threats before they escalate.

These strategies combine to create a unified security approach while maintaining operational efficiency across your multi-cloud infrastructure.

When selecting cloud security posture management (CSPM) tools, look for platforms that offer deep integration capabilities with all your cloud services and on-premises systems. The ideal solution should provide continuous monitoring, automated compliance checks, and centralized visibility across your technology stack.

Integrating DevSecOps for continuous protection

Incorporating security into your development lifecycle through DevSecOps transforms how your organization approaches security. Rather than treating security as a final checkpoint, it becomes integral to every stage of development. This shift lets your teams identify and address vulnerabilities early, when fixes are less costly and more effective.

DevSecOps fosters an environment where security expertise is shared across teams, creating a collaborative culture where developers, security specialists, and operations staff work together to build secure systems from the ground up.

Strengthening data protection methods: Top 9 checklist

Let's explore nine essential data security practices to enhance your data protection strategy. Each approach offers unique benefits and works with the others to create a layered security model.

Your encryption strategy needs strong algorithms and careful key management. Think of encryption keys as the master keys to your digital kingdom. Their protection is just as vital as the encryption itself. Hardware Security Modules (HSMs) serve as virtual vaults for these keys, protecting them from tampering and unauthorized access.

Implement automated key rotation policies that regularly update encryption keys to minimize risk. This practice ensures that even if an attacker somehow obtains an old key, they can't use it to access current data. It’s similar to changing the locks on your doors periodically—even if someone finds an old key, it won't work anymore.

Centralizing your key management brings all these protective measures under one roof. This approach strengthens security and enables automated monitoring systems to quickly spot and alert you to unusual access patterns or potential breach attempts. Your security team gains a unified view of all key-related activities across your organization.

These three techniques form a powerful trio for protecting sensitive data while maintaining business utility. Tokenization transforms sensitive data into meaningless tokens. Imagine replacing your credit card number with a random string that only your system can link back to the original. This ensures that even if unauthorized users access your systems, they can't extract valuable information.

Data masking takes a different approach, preserving the format while hiding the actual data. For instance, a masked credit card number might show only the last four digits while maintaining the same length and pattern. This allows your applications to function normally while protecting sensitive information.

De-identification goes even further by removing or altering any elements that could identify an individual. This technique proves especially valuable when data needs to be used for analysis or testing while maintaining privacy compliance.

Together, these methods simplify your compliance with PCI-DSS, HIPAA, and GDPR. If a security incident occurs, these protective layers ensure that any accessed data remains worthless to attackers, giving you valuable time to respond and contain the breach.

Your access control strategy needs to evolve beyond simple role-based permissions. By implementing attribute-based access control (ABAC), you gain the flexibility to create nuanced policies based on multiple factors about users, data, and context. Think of it as moving from a simple key card system to an intelligent security checkpoint that evaluates multiple credentials before granting access.

Just-in-time access adds another layer of sophistication by providing temporary elevated permissions only when needed. This drastically reduces your exposure window—similar to how a bank vault might only be accessible during specific times and with multiple authorizations. When the task is complete, permissions automatically return to normal levels.

Dynamic access revocation monitors user behavior and system conditions in real time. If suspicious activities or employment status changes occur, the system can immediately cut off access, protecting your data from potential threats.

Modern data protection requires a continuous approach that captures changes in critical systems as they happen and frequent backups at agreed-upon schedules. This backup strategy ensures you never lose more than a few seconds of data, even in worst-case scenarios.

Immutable backup plays a crucial role here. When you write data to an immutable backup file, it cannot be altered for a specified period. Much like a digital time capsule, once sealed, the contents remain unchanged until the predetermined time expires. This proves invaluable during ransomware attacks, ensuring you always have clean, uncompromised data copies for recovery.

The principle is simple but powerful: the less sensitive data you store, the smaller your attack surface becomes. Start by analyzing your data collection. Do you need to keep all those customer details? Could you anonymize certain fields? Each piece of information you store represents a potential target for attackers.

Automated deletion workflows help enforce your retention policies, systematically removing data that's no longer necessary or has exceeded its required retention period. This reduces risk and helps maintain compliance with privacy regulations that mandate limited data retention.

Modern DLP solutions employ advanced analytics to understand the context and movement patterns of information flowing through your organization. The system identifies sensitive data transfers, whether obvious or embedded within larger documents, such as financial data in employee emails. For example, your DLP system might identify when an employee tries to send sensitive financial data to a personal email, even if the data is embedded within a larger document.

Your DLP strategy requires both preventive and detective controls. Preventive measures stop unauthorized data transfers before they happen, while detective controls alert your security team to suspicious patterns that might indicate an insider threat or compromised account.

Network segmentation works like security checkpoints between different areas of your network. Instead of having one large, open space where a breach in one area threatens everything, you create separate zones with distinct security controls. Each segment operates independently, requiring specific credentials and meeting security requirements before allowing communication with other segments.

Micro-segmentation further develops this concept by creating even smaller, more granular boundaries—down to the individual workload level. This detailed control means that even if an attacker compromises one application, they remain confined to that small segment, unable to move laterally through your network.

Consider penetration testing as staging a controlled break-in attempt on your systems. Professional, ethical hackers use the same techniques as malicious actors but report vulnerabilities instead of exploiting them. This proactive approach helps you identify and fix security gaps before real attackers find them.

Automated vulnerability scanning provides continuous monitoring between penetration tests. These tools constantly check for known vulnerabilities, misconfigurations, and security patches that need attention. Combining manual testing and automated scanning creates a robust detection system for potential security weaknesses.

Managing data throughout its lifecycle requires a systematic approach that protects sensitive information while ensuring regulatory compliance. Just as physical assets move through acquisition, use, and disposal stages, digital data follows a similar journey through creation, storage, usage, and destruction – each stage demanding specific security controls and considerations.

During the creation phase, version control becomes essential for tracking every modification to your data. This detailed change history helps maintain data integrity and provides crucial documentation for compliance and audit purposes.

The storage phase demands strengthened security strategies that strike a balance between protection and accessibility. By implementing encryption, access controls, and secure backup systems, you can protect data from unauthorized access while ensuring it remains available for legitimate business needs. Your storage architecture should account for different data types and sensitivity levels, applying appropriate risk-based security controls.

As data moves into active use, security focuses shift to monitoring and controlling how information flows through your organization. Advanced auditing tools track who accesses data, when, and for what purpose, creating a detailed activity log that helps identify potential security incidents before they escalate. These monitoring systems serve as an early warning system, alerting security teams to unusual patterns that might indicate a breach attempt.

The final destruction phase proves just as vital as the initial creation. When data reaches the end of its required retention period, secure disposal methods ensure it cannot be reconstructed or recovered by unauthorized parties. This methodical elimination process helps minimize risk exposure while maintaining compliance with data protection regulations.

This lifecycle approach creates an integrated security framework where each phase builds upon the previous one, ensuring consistent protection from beginning to end.

Detecting and responding to advanced threats

Advanced cyber threats have evolved far beyond simple malware and viruses. Modern attackers employ sophisticated techniques to evade traditional security measures, making continuous monitoring and rapid response capabilities essential for protecting your data.

Using AI and ML for threat detection

Artificial Intelligence (AI) and Machine Learning transform threat detection by analyzing vast amounts of security data to identify patterns that signal potential attacks. These systems learn from historical security incidents to spot subtle indicators that human analysts might overlook. For example, AI systems can correlate seemingly unrelated access attempts across different systems to identify coordinated attacks in progress.

The key to successful AI-driven security lies in proper implementation. Your AI systems should be trained on diverse datasets representing your organization’s unique security landscape. By implementing explainable AI frameworks, your security teams gain clear insights into threat detection, enabling them to respond quickly and effectively to potential security incidents.

Behavior analytics and insider threat mitigation

Modern security systems build detailed profiles of normal user behavior to identify suspicious deviations. When an accounting employee suddenly accesses marketing databases at unusual hours, or a developer’s account shows unusual file transfer patterns, behavior analytics tools raise alerts. Success depends on establishing accurate baseline behaviors for different user roles and departments and continuously refining these baselines as work patterns evolve.

Rapid incident response and forensics

Well-designed incident response plans serve as your roadmap during security events, providing clear procedures for containing potential breaches while preserving valuable evidence. Regular tabletop exercises and full-scale drills help teams refine their response strategies by simulating various scenarios in a controlled environment. These practice sessions build confidence and ensure smooth coordination when real incidents occur.

Digital forensics focuses on investigating cyber threats to identify the root causes of attacks and their perpetrators, and to drive the remediation of issues. Additionally, digital forensics adds another vital dimension to your security strategy. By thoroughly investigating security incidents, your team gains valuable insights that strengthen your defenses and help prevent similar events in the future. This systematic approach to incident analysis and response creates a continuous improvement cycle, enhancing your overall security posture.

Modern data security platforms play a valuable role in incident response and digital forensics. From restoring essential tools and information to a trusted state, to providing a full series of snapshots for file system forensics, and detecting indicators of compromise (IOCs) within backed-up data, these platforms enhance both the effectiveness and efficiency of response efforts. Their value becomes even more pronounced during destructive cyberattacks—especially when traditional defenses have failed and primary systems are isolated as part of containment measures.

Navigating regulatory complexities and compliance

The regulatory landscape for data protection is evolving rapidly as governments respond to emerging privacy concerns and technological advances. Your compliance strategy needs to adapt just as dynamically, incorporating both automated tools and systematic processes to monitor and respond to these changes. Modern compliance management tools help you track updates across multiple regulatory frameworks while maintaining the documentation to demonstrate adherence.

Global compliance frameworks and data residency

The global nature of business today means navigating multiple regulatory frameworks simultaneously. GDPR, CCPA, and HIPAA each bring unique data protection and privacy requirements. Meeting these diverse standards requires a layered approach to data security. By implementing strong encryption and pseudonymization techniques, you protect sensitive information while maintaining its utility for business operations.

Data residency adds another dimension to compliance, as different regions enforce specific requirements regarding where and how you can store their citizens’ data. Building audit trails into your data handling processes creates transparency and accountability, showing how information moves through your systems and who accesses it. This visibility proves invaluable during regulatory audits and helps you maintain ongoing compliance.

Automation plays an important role in maintaining consistent compliance across these various frameworks. By systematizing data management processes, you reduce the risk of human error while ensuring the consistent application of security controls across all data handling activities.

Continuous compliance monitoring and reporting

Modern governance, risk, and compliance (GRC) platforms transform compliance from periodic assessments into ongoing processes. These systems continuously monitor your environment, automatically checking configurations and practices against current regulatory requirements. When they detect potential compliance gaps, they alert your team immediately, allowing for swift remediation before small issues become significant problems.

Integrated dashboards provide real-time visibility into your compliance status across multiple regulatory frameworks. This comprehensive view helps you make informed resource allocation and risk management decisions. The detailed documentation these platforms maintain serves as evidence during audits and a foundation for the continuous improvement of your compliance program.

Future-proofing your data security strategy

You’re implementing data security best practices today, but we need to prepare you for tomorrow’s security landscape. Three transformative technologies are reshaping how you’ll protect your data in the coming years: quantum computing capabilities, intelligent security systems, and adaptable security architectures. Let’s explore how each of these developments will influence your security strategy.

Quantum-resistant cryptography

The advent of quantum computing will fundamentally change your encryption needs. Quantum computers can solve complex mathematical problems exponentially faster than traditional systems, potentially compromising today’s encryption algorithms. By exploring quantum-resistant algorithms now and planning your transition strategy, you can ensure that your sensitive data remains protected as this technology matures.

Autonomous security and AI-driven policy adaptation

AI technology is transforming security systems into intelligent guardians of your data. These advanced platforms automatically analyze behaviors, recognize patterns, and respond to threats. When your AI security system identifies suspicious activity, it immediately adjusts controls and blocks potential threats, providing swift protection while informing your security team.

Security mesh architectures

Security mesh architecture (CSMA) introduces a new paradigm in protection by creating an integrated security ecosystem. Unlike traditional approaches that rely on isolated security tools, CSMA enables various security components to work as one cohesive system. This unified approach means that your security policies adapt smoothly as your organization grows, automatically extending protection to new applications and systems.

Advance your data security with Cohesity

The cybersecurity landscape continues to grow more complex every day, demanding sophisticated solutions to protect your valuable data. Throughout this guide, we’ve explored essential data security best practices—from data classification and Zero-Trust architecture to DevSecOps implementation and encryption strategies. Now, let us show you how to implement these data security practices.

We’ve designed our data security solutions at Cohesity with your organization’s complete protection in mind. By integrating advanced security measures to protect enterprise workloads across on-premises, cloud, and SaaS on a unified platform, we help you implement a simple and scalable solution that can strengthen your cyber resilience.

Our platform builds upon Zero Trust principles while simplifying data management, creating an environment that adapts to future security challenges. The world’s largest organizations trust us as their security partner because we understand that protecting data and developing resilience to cyberattacks require more than just tools—it demands a holistic approach that addresses modern security challenges head-on.

Ready to strengthen your data security and cyber resilience? Experience the difference and request your 30-day free trial. Let us help you transform how you protect, manage, and gain insights from your data. Contact us today to begin your journey toward enhanced data security.

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