Data Security

Organisations have never had to pay as much for data security as they do today. According to IBM’s 2025 Cost of a Data Breach Report, U.S. companies now pay an average of $10.22 million for each breach. This is an all-time high, up 9% from the previous year.

Social engineering, insider threats, cloud misconfigurations, and supply chain vulnerabilities remain top concerns. Yet, the threat landscape is shifting dramatically as AI brings a new kind of risk. For example, the Harvard Business Review reported that traffic from generative AI has grown by 890%, and incidents of AI-related data breaches have more than doubled in the past year alone.

Data security is the practice of keeping information safe throughout its entire life cycle, ensuring it remains private, accurate, and accessible. That data life cycle includes making, storing, using, sharing, archiving, and finally deleting. The main goal is easy: allow access to those who have permission and deny access to everyone else.

These days, you can find company data on multiple platforms, including on-site servers, cloud-based services, Software as a Service (SaaS) solutions, collaboration tools, remote endpoints, and/or mobile devices. And data can be structured (database records) or unstructured (emails, documents, Slack messages, etc.) In turn, each type of environment and data requires its own specific method of protection.

Data security and cybersecurity are not the same thing. Cybersecurity covers an organisation’s complete digital ecosystem (networks, applications, infrastructure, and endpoints). Data security focuses primarily on protecting the company’s information. Think of cybersecurity as protecting the castle walls, and data security as protecting the prized possessions within those walls.

Ask any CISO, data governance director, or compliance lead — when data security fails, the consequences are severe. A breach can result in financial damage, regulatory violations, and a decline in consumer confidence. Developing a robust data security programme includes the implementation of encryption, access control, monitoring, and security awareness training. Deploying these technologies across the data life cycle enables secure, confident growth.

Data is the most valuable asset in modern businesses. Customer records, intellectual property, financial information, and operational secrets provide an edge over competitors. Losing control of data means losing much more than just files.

Financial Impact

Breaches drain resources fast. Phishing attacks alone cost businesses an average of $4.8 million each time they happen. The cost of stealing intellectual property is the highest at $178 per record. These costs include incident response, legal fees, regulatory fines, and remediation work—diverting funds from growth.

Reputational Damage

A data breach damages trust and reputation, and compliance and legal teams need to invest heavily in reversing the negative sentiment. Customers assume you’re going to keep their information safe. When breaches compromise customer PII in 53% of cases, customers will switch to your competitors. And business partners rethink their contracts with you. Rebuilding a reputation takes years of consistent work.

Business Continuity

Cyber incidents disrupt operations, and CISOs must work tirelessly to restore working order. Ransomware keeps teams from accessing essential systems. It takes an average of 241 days to find and fix a third-party breach. When databases are compromised, customer service grinds to a halt.

Compliance and Legal Exposure

Regulations like GDPR, HIPAA, and CCPA impose multimillion-dollar fines for data protection failures. Beyond financial penalties, enforcement actions trigger audits that expose systemic vulnerabilities and consume executive bandwidth.

Modernisation Pressures

Your data is all over the place thanks to cloud platforms, SaaS apps, and remote work. The number of breaches involving third parties has doubled to 30%. According to Verizon’s 2025 Data Breach Investigations Report, attacks on edge devices and VPNs increased by almost eight times, and vulnerability exploitation increased by 34%. Every new piece of technology comes with new security risks that need to be addressed.

Strong data security provides benefits beyond stopping breaches. It helps CTOs and leadership teams grow and builds trust, while adopting new technologies with confidence. The payoff shows up in operations, compliance efforts, and how the company competes.

• Risk reduction and breach containment: Layered security controls keep attackers from getting too far into your environment and limit the damage when something goes wrong.
• Compliance and evidence generation: Automated logging and monitoring create audit trails that demonstrate compliance with regulations like the GDPR, HIPAA, and CCPA.
• Protection of IP and competitive advantage: Encryption and access controls keep proprietary research, product plans, and trade secrets safe from competitors.
• Customer and partner assurance: Demonstrating strong data protection practices reassures clients and helps with vendor evaluation.
• Digital transformation and remote work: Security frameworks that keep data safe in distributed environments let workers do their jobs from anywhere without putting themselves at risk.
• Safely supporting cloud and SaaS adoption: Proper controls for cloud configurations and SaaS permissions allow the use of modern platforms without compromising sensitive information.
• Reducing insider misuse and accidental leaks: DLP and access controls stop both malicious insiders and well-meaning employees from sharing data inappropriately.
• Improving audit readiness and governance maturity: Consistent rules and automated enforcement lend transparency for leaders and auditors.

Companies use a number of data security controls that work together to keep information safe throughout its life cycle. No single protocol can stop every threat, so layered defences protect against different types of cyber-attacks and use cases. The best strategies use both technical controls and user awareness.

Data Encryption

Data encryption uses algorithms to scramble information so that only people with the right decryption keys can read it. For high-security environments, IT admins encrypt data when it is stored in databases and file storage, when it is sent over networks and email, and when it is being processed. Even if attackers get past your defences and access your encrypted data, they can’t use it without keys. This is an important consideration for CISOs when evaluating ways to contain a breach.

Data Masking and Tokenisation

Data masking hides sensitive information by replacing characters with asterisks or random values. This lets customer service reps see the last four digits of credit cards without showing the full numbers. Tokenisation replaces sensitive data with random tokens stored in separate, secure vaults. This way, the original data never leaves secure systems. Legal and compliance teams use these methods to ensure the business can continue while also meeting PCI DSS and GDPR standards.

Data Erasure and Retention

Secure deletion permanently deletes data when retention periods end, so that old customer records don’t become problems in future breaches. Compliance officers set up retention policies that take into account both the law and risk reduction, and IT admins set up automated workflows to ensure consistent deletion. SecOps teams like that the attack surface is smaller because unnecessary data is removed from production databases, backups, and archives.

Data Backup and Recovery

IT managers keep several copies of important data in different locations and formats, such as offline backups that ransomware can’t encrypt. When something goes wrong, SecOps teams ensure the business can continue by regularly testing recovery plans. CISOs value backup plans that have been tested, allowing companies to refuse ransom demands and get back to business faster without talking to attackers.

Data security threats come in various forms, each posing unique challenges to CISOs and cybersecurity teams. Understanding these threats is crucial for developing comprehensive security strategies.

External Threats

Organisations face numerous external threats that continuously evolve in sophistication and impact:

• Ransomware. Malicious software that encrypts organisational data and demands payment for its release.
• Phishing attacks. Deceptive attempts to steal sensitive information by masquerading as legitimate entities.
• Malware. Harmful software that is designed to damage systems, steal data, or gain unauthorised access.
• Credential theft. Phishing, keyloggers, or hacked password databases are some of the ways that attackers steal login information to gain real access to systems and data.
• Data exfiltration. After breaching access, attackers slowly extract sensitive information from your environment to avoid detection.
• Zero-day exploits. Previously unknown vulnerabilities that attackers leverage before patches are available.

Insider Threats

Insider threats pose a significant risk as they originate from within the organisation. These can be either accidental, such as employees inadvertently sharing sensitive data, or malicious, involving intentional data theft or sabotage.

The challenge SecOp teams face with insider threats is that they can bypass traditional security measures because they have authorised access. Implementing strict access controls, regular security training, and monitoring systems is crucial for mitigating these risks.

Advanced Persistent Threats (APTs)

Advanced persistent threats are sophisticated, long-term cyber campaigns targeting specific organisations or sectors. These attacks are often state-sponsored and aim to maintain covert access to systems for espionage or data theft.

APTs are particularly dangerous due to their stealthy nature. These attacks are often state-sponsored and aim to maintain covert access to systems for espionage or data theft. They primarily target high-value industries, government agencies, and defence contractors.

Cloud-Specific Risks

The shift to cloud computing introduces unique security challenges that IT admins and data governance teams must address:

• Misconfiguration. Improperly configured cloud services leave sensitive data exposed to unauthorised access.
• Data loss. Inadequate backup and recovery procedures in cloud environments lead to permanent data loss.
• Shadow IT. Unauthorised cloud services used by employees that bypass security controls.
• API vulnerabilities. Insecure APIs that can provide attackers with access to cloud-based resources.
• Multi-tenancy risks. Security challenges arising from sharing cloud infrastructure with other organisations.
• Supply chain exposures: Supply chain attacks compromise trusted software providers to reach downstream customers.
• Collaboration platforms: Email, chat tools, and file-sharing platforms create new data loss vectors. Employees paste sensitive information into Slack messages or share confidential documents through personal cloud storage.

The size, data type, and infrastructure of an organisation should all be taken into account when strategising a data security programme. Cybersecurity experts recommend these best practices that universally apply across nearly any industry:

• Data discovery and classification: Identify where sensitive data is stored in your environment and label it based on its sensitivity. This lets you put the right controls on customer PII, financial records, and intellectual property.
• Data ownership and governance structures: Ensure that different types of data have clear owners and that rules govern their handling, storage, and disposal—document who can access what and under what circumstances.
• Least privilege and zero-trust access: Verify every access request, no matter where it comes from. Grant users only the permissions they need to do their jobs.
• Encryption and key management: Use the latest cryptographic standards to protect sensitive data at rest and in transit. Centralise key management and frequently rotate keys to keep them safe.
• DLP across channels: Deploy DLP controls across email, web traffic, cloud apps, and endpoints. Block sensitive data from leaving through unauthorised channels.
• Secure SaaS settings: Check the permissions for cloud storage and settings for sharing SaaS to ensure they don’t accidentally make your data public. Monitor who has privileged access to admin consoles.
• Identity, MFA, and SSO: All users who need to access sensitive systems should use MFA. Single sign-on simplifies access while still keeping strong authentication.
• Telemetry and observability for data access: Keep track of who accesses what data and when. Real-time monitoring can help detect anomalous access patterns indicative of a breach.
• Incident response and tabletop exercises: Establish playbooks for breach scenarios and then test them by simulating incidents. Regular drills show weaknesses before real attacks happen.
• Teach employees how to handle data: Educate teams on phishing, social engineering, and safe data sharing. Increased security awareness reduces the risk of both intentional and unintentional data exposure.
• Regular audits and assessments: Conduct ongoing risk assessments to identify systems and data repositories at risk. Instead of waiting for external audits, evaluate your security controls and compliance posture quarterly.

Most businesses are required to comply with regulatory requirements regarding the data they collect and where they do business. Government agencies and industry groups determine rules for how data must be kept safe and stored. Fines for breaking the rules can be very costly, sometimes even millions of dollars. For instance, an organisation that handles medical and financial records must follow both HIPAA and PCI DSS at the same time. Companies that do business with EU customers must comply with GDPR rules, regardless of where they are based.

Major Frameworks

• GDPR (General Data Protection Regulation): This is a European law that protects people’s privacy. It says that data collection must have clear consent, that people have the right to have their data deleted, and that companies must notify people within 72 hours if their data is stolen. Violations can cost the world up to 4% of its revenue.
• CCPA/CPRA (California Consumer Privacy Act / California Privacy Rights Act): These are California laws that give consumers the right to know what data companies collect, delete it, and not buy it. Other states in the U.S. have passed similar laws.
• HIPAA (Health Insurance Portability and Accountability Act): A federal law that protects PHI and has strict rules for access controls, encryption, and reporting breaches. This applies to healthcare providers, insurance companies, and the people they do business with.
• SOX and GLBA (Financial Services): The Sarbanes-Oxley Act requires public companies to maintain audit trails and protect financial reporting data. The Gramm-Leach-Bliley Act requires banks and other financial institutions to protect customer information and to inform customers about how they share data.
• PCI DSS (Payment Card Industry Data Security Standard): This standard sets rules for any business that handles, stores, or sends credit card information. Includes encryption, access controls, network segmentation, and regular security testing.
• ISO 27001: This international standard for information security management systems helps you manage sensitive data in a structured way. Getting certified demonstrates your commitment to following best security practices.
• NIST CSF and SP 800-53: The National Institute of Standards and Technology frameworks are widely adopted by U.S. federal agencies and contractors. These standards provide complete control over detecting, protecting against, responding to, and recovering from cyber threats.

Compliance teams must develop frameworks that provide written proof of security controls. Companies must keep records of who accessed data, acknowledged policies, performed security assessments, and responded to incidents. Regular audits check that controls work as they should. Automated reporting tools help security teams gather evidence without scrambling when auditors show up.

Today’s CISOs and data governance leaders grapple with a complex array of data security challenges:

• Balancing security with usability: Organisations must implement robust security measures without impeding employee productivity or user experience.
• Adapting to the rapidly evolving threat landscape: With new sophisticated threats constantly emerging, enterprises struggle to keep pace with port hopping, nonstandard ports, and threats hiding within SSL encryption.
• Protecting data across hybrid and multi-cloud environments: Adopting hybrid and multi-cloud strategies introduces security complexities, with 39% of breaches targeting cloud environments. Enterprises face difficulties maintaining consistent security policies and visibility across diverse cloud platforms.
• Managing insider threats effectively: Organisations must identify users, monitor their access to applications and resources, and ensure appropriate permissions across multiple cloud environments.
• Remote and distributed workforce: Employees can access private information from their home offices, coffee shops, and mobile devices. When your employees are all over the place, old perimeter defences aren’t as effective.
• Shadow IT and shadow data: Cloud services and apps that aren’t approved by IT can bypass IT’s controls. Security teams can’t see or control the tools that employees use to store sensitive information.
• Limited visibility and fragmented tools: Companies use dozens of point solutions that don’t work well together. Security teams can’t see how data moves between email, collaboration platforms, cloud storage, and endpoints in a unified way.
• Unclear ownership of data: When it’s not clear who is responsible for different types of data, protection is inconsistent. IT and business units don’t agree on who is responsible for protecting certain datasets.
• Compliance in multi-cloud architectures: Navigating data residency requirements and privacy regulations while maintaining effective threat detection capabilities becomes increasingly complex in fragmented multi-cloud setups.

These challenges require enterprises to implement adaptive, data-centric security approaches that can protect information across its entire life cycle, regardless of where it resides.

To keep data safe, you must have visibility into who is accessing what data, when, and from where. Modern monitoring tools go beyond simple logging to detect issues in real time and collect forensic evidence when something goes wrong.

Data Access Telemetry

Data access telemetry automatically collects and tracks information about how users interact with sensitive data (who accesses what data, when, where, and what actions they take). This includes sharing documents, downloading files, making API calls, and querying databases. Rich metadata records the user’s identity, device type, location, and activities. This level of detail helps security teams find problems before they turn into breaches.

Behavioural Analytics for Insider Threats

User and entity behaviour analytics (UEBA) sets baseline patterns for how employees typically access data. The system notes activities that are out of the ordinary, such as large downloads, access at odd hours, or attempts to access off-limits systems. This catches both accounts that have been hacked and insiders who use real credentials for bad purposes.

SIEM and SOAR Integration

Security information and event management (SIEM) platforms aggregate logs from across your infrastructure into a single pane of glass. Security orchestration, automation, and response (SOAR) tools take it further by automating responses to common threats. Integrating data security telemetry with these systems lets you correlate data access events with network activity and endpoint alerts.

Audit Logs and Evidence

Full audit trails keep track of who did what to what data. Immutable logs stop hackers from hiding their tracks after a breach. During forensic investigations, these critical records can be used as evidence in court. Retention periods must align with the rules and time frames for possible lawsuits.

Compliance Reporting

Automated reporting tools turn raw telemetry data into compliance artefacts. Create proof of access controls, encryption status, and how you handle data whenever you need it. Pre-made templates for GDPR, HIPAA, and PCI DSS make it easier for auditors to do their jobs. Continuous compliance monitoring takes the place of point-in-time assessments.

Breach Notification Triggers

When data security events go beyond set limits, monitoring systems should send out alerts. You need to act right away if you see mass downloads of customer records, unauthorised access to regulated data, or attempts to steal data. Automated workflows let incident response teams know what’s going on and start containment procedures. As soon as you find out about a breach, the clock starts ticking. Speed is vital.

Data Lineage Visibility

Knowing where data comes from, how it moves, and where copies are can help you figure out the severity of a breach. Data lineage tools show governance teams how source systems, databases, analytics platforms, and downstream consumers are connected. When a breach happens, you can quickly identify the leaked datasets and the affected business processes.

The data security landscape is evolving at an incredible pace thanks to technological advancements and changing business dynamics. Here are the key trends shaping data security threats and best practices:

Zero Trust Strategies

Cybersecurity teams are increasingly adopting a “never trust, always verify” approach to security. This model assumes no user or device is trustworthy by default, even within the organisation’s network. SecOps are implementing continuous authentication and authorisation protocols for all users and devices while employing micro-segmentation strategies to limit network access.

AI and Machine Learning in Threat Detection

Artificial intelligence and machine learning are revolutionising cybersecurity by enhancing threat detection and response capabilities. These technologies enable real-time analysis of vast datasets to identify potential threats while providing automated responses to security incidents, significantly reducing reaction time.

Advanced systems now employ predictive analytics to anticipate and prevent future attacks, while behavioural analysis helps detect anomalies in user and system activities before they become serious threats.

Data Security for GenAI Applications

As generative AI tools become more prevalent, data governance teams are developing new security frameworks to protect sensitive data. This includes implementing robust access controls for data used in GenAI systems and employing sophisticated data masking and tokenisation techniques.

Many enterprises are now utilising Retrieval-Augmented Generation (RAG) to leverage public models while protecting private information, alongside continuous monitoring and auditing of data access in GenAI workflows.

Regulatory Changes and Compliance

The regulatory landscape for data privacy and security continues to evolve rapidly. We’re seeing a proliferation of state-level privacy laws in the U.S., such as CCPA and VCDPA, alongside an increased focus on protecting sensitive and health-related data. Compliance teams must navigate growing emphasis on data localisation and sovereignty while adapting to stricter enforcement measures and higher penalties for non-compliance.

Data Observability

Companies are moving away from traditional logging and toward platforms that let them see all of their data. These systems monitor data flows in real time across the whole ecosystem. Cybersecurity teams can see who is accessing what data, how it moves between systems, and where copies are stored. This helps find security holes, fix problems faster, and determine the size of a breach when it happens.

Insider Risk Mainstreaming

Insider threat programmes have gone from niche initiatives to being the norm. Companies now use a mix of behavioural analytics, psychological indicators, and technical monitoring to find employees who are at risk. Programmes can differentiate between careless users who need training and bad actors who require investigation. Cross-functional teams from security, HR, and legal work together on early intervention and response.

Cloud Services and Cloud Security

As cloud adoption grows, organisations are implementing more sophisticated security measures. Modern cloud security strategies emphasise end-to-end encryption for data in transit and at rest, coupled with advanced access management systems. Regular security audits and compliance checks have become standard practice, while organisations increasingly adopt cloud-native security tools and services to protect their digital assets.

Convergence of Security, Privacy, and Governance

Organisations are consolidating data security, privacy compliance, and governance into unified programmes. CISOs are now working closely with Chief Privacy Officers and data governance leaders. A single system can handle security controls, privacy rights management, and retention policies. This convergence reduces friction, eliminates duplicate work, and ensures everyone in the company handles data consistently.

Business Continuity and Disaster Recovery

Organisations are prioritising resilience against cyber-attacks and other disasters through comprehensive planning and preparation. This includes maintaining regular data backups with off-site storage capabilities and implementing automated failover and recovery systems. Regular testing through tabletop exercises ensures organisations can respond effectively to potential incidents, minimising downtime and data loss.

Modern data security requires a layered approach with specialised tools for different challenges. No single solution protects everything, but the right combination creates defence-in-depth. Here are the core solution categories that enterprises deploy to safeguard sensitive information.

• Data Loss Prevention (DLP): DLP platforms monitor and block sensitive data from leaving your organisation through email, endpoints, web traffic, and cloud applications.
• Data Security Posture Management (DSPM) and SaaS Posture: DSPM tools discover where sensitive data lives across cloud environments and identify misconfigurations, overly permissive access, and unencrypted storage.
• Identity and Access Management (IAM) and Privileged Access Management (PAM): IAM controls who accesses which systems through single sign-on and role-based permissions, while PAM secures high-privilege accounts, such as database and cloud administrators.
• Insider Risk Management: These platforms combine behavioural analytics and data access monitoring to flag employees who exhibit risky behaviour, such as making unusual downloads or accessing systems outside their role.
• Classification Tools: Automated classification tags data by sensitivity level so downstream security controls can apply appropriate encryption, access restrictions, and DLP policies.
• Encryption and Key Management: Encryption protects data at rest and in transit, while key management systems generate, store, rotate, and revoke cryptographic keys that enable encryption.
• Cloud Access Security Broker (CASB) and Secure Cloud Access: CASBs sit between users and cloud applications to enforce security policies, detect shadow IT, and prevent data exfiltration to unauthorised apps.
• Security Awareness Training: Interactive training programmes teach employees to recognise phishing, handle sensitive data correctly, and report suspicious activity that technical controls might miss.
• Audit and Compliance Tooling: Compliance management platforms automate evidence collection, generate reports, and map security controls to regulatory requirements like GDPR, HIPAA, and PCI DSS.

When choosing a data security solution, evaluate these critical considerations:

• Coverage: Does it protect all kinds of data (structured and unstructured) across all channels, such as email, endpoints, the cloud, SaaS, and collaboration tools?
• Integration: Look for strong APIs and pre-built connectors that let you easily connect your identity systems, SIEM platforms, and collaboration tools.
• Reporting and auditing features: When regulators request information, built-in compliance reports and audit trails save time. Automated evidence collection beats manual scrambling.
• Compliance alignment: Use solutions that already support your regulatory needs, such as GDPR, HIPAA, or PCI DSS. Pre-mapped controls reduce configuration effort.
• User experience and business enablement: Security that blocks productivity gets bypassed. Solutions should keep data safe without getting in the way of real work.
• Scalability and total cost of ownership: Make sure the platform can handle more data and users without slowing down. Take into account the costs of licensing models, implementation, and ongoing maintenance.
• Vendor roadmap and innovation pace: Understand how quickly a vendor can address new threats, such as AI-powered attacks, and new ways of working together. Check out how often they release new features and updates.

Choose a solution that meets your current needs and sets your business up to handle future problems.

Proofpoint protects your critical data across all of your channels. With a single platform, cross-channel DLP protects sensitive data in email, cloud storage, SaaS apps, and endpoints. You get the same rules no matter where the data goes.

Insider risk management uses behavioural analytics and contextual signals to identify users who are negligent, malicious, or compromised. The platform differentiates between real threats and false positives, so your team can focus on what matters. Built-in compliance reporting makes it easy to prove compliance with GDPR, HIPAA, PCI DSS, and other standards. Automated workflows make it easier for regulators to do their jobs.

Data classification works with existing tagging systems to set the appropriate controls based on data sensitivity. Without rebuilding your taxonomy, you can protect customer PII, intellectual property, and regulated data.

For more information, contact Proofpoint.