12 Data Security Controls: Nine Foundational Elements and Three Critical Decisions

Most organizations maintain a standard list of data security controls. They reference it during audits, present it to leadership, and check off the same boxes year after year. Yet, data breaches continue to happen. The issue isn't a lack of effort—it's that most security frameworks were designed before the threat landscape drastically shifted.

Not a single popular industry control list includes a dedicated entry for artificial intelligence. They fail to account for employees pasting customer records into ChatGPT or autonomous AI agents querying databases without human intervention. Today, these aren't isolated edge cases; they are daily enterprise realities. Let's examine 12 data security controls: foundational elements alongside three new tools still missing from standard frameworks.

Foundational Data Security Controls

Protecting information begins with visibility, basic access control mechanisms, and data loss prevention.

1. Data Discovery and Classification

Every tool on this list depends on this step. It's impossible to enforce policy on data that hasn't been found or to analyze risk without understanding information value. Data discovery determines where sensitive assets live across cloud environments, SaaS applications, local storage, and collaboration platforms. Classification assigns labels based on content and context rather than file type alone.

With massive volumes of data, AI-powered classification has become the standard. The primary requirement is accuracy, as high false-positive rates overload security analysts. The DSPM technology layer turns discovery and classification into an ongoing, enterprise-wide process.

2. Data Access Governance

Most implementations stop at a one-time IAM policy setup, but access governance must be continuous. Employee permissions accumulate, roles change, and folders remain open for public access. Effective governance combines regular privilege audits with data classification context to consistently enforce the principle of least privilege.

3. Data Loss Prevention (DLP)

DLP is the enforcement layer that translates classification rules into action across endpoints, email, web traffic, and cloud applications. When risk thresholds are exceeded, the system blocks transfers, alerts users, or escalates incidents for review. The Forcepoint DLP solution provides unified policy management across all channels, eliminating blind spots and reducing false positives via built-in AI algorithms.

4. Email Security (DLP for Email)

Outbound email remains the most common channel for both accidental and intentional data loss. Effective protection requires agentless control in Microsoft 365 Exchange and Google Workspace, inspecting attachments and message bodies without introducing transmission delays. Forcepoint DLP for Email extends unified policies to email services without requiring agents installed on user devices.

5. Data Encryption at Rest and in Transit

Encryption protects data from unauthorized reading during storage (at rest) and network interception (in transit). The effectiveness of this control relies on strict key management governance and consistent application across all environments, including staging and test tracks.

6. Cloud Data Security

The shared responsibility model in cloud environments leaves the security of the data itself on the customer's side. To manage SaaS environments, a Cloud Access Security Broker (CASB) is deployed, which paired with DSPM delivers complete visibility over data movement. The Forcepoint Cloud App Security solution delivers full data visibility in SaaS and applies DLP policies without altering network architecture.

7. Insider Risk Management and Behavioral Monitoring

Most incidents stem from actions by users who already hold legitimate access. Behavioral monitoring establishes baseline profiles of how employees interact with data and flags anomalies. On average, identifying an insider threat takes 194 days. Dynamic adaptive policies (Risk-Adaptive Protection) automatically tighten or relax controls based on a user's current risk score.

8. Zero Trust Access

Zero Trust is an architectural principle stating that no user or system receives implicit trust. Every connection and session is continuously evaluated against context: identity, device health, location, and data sensitivity.

9. Audit Logging and Compliance Reporting

Regulators require proof that security measures are actively enforced. Automated logging tracks who accessed what data, when, and from where, generating audit-ready reports mapped to GDPR, PCI DSS, HIPAA, and emerging AI regulatory frameworks.

Three Controls Missing from Standard Frameworks

The following three tools bridge the gap between 2020-era security frameworks and modern AI-driven realities.

10. Shadow AI Governance

Studies show that 69% of organizations suspect employees are using unauthorized Generative AI tools. Data shared with public services (source code, financial records, PII) may be retained on third-party servers. The Forcepoint AI Data Security tool discovers all unsanctioned AI applications, plugins, and clients, enabling granular real-time allow, restrict, or block decisions.

11. DLP for Sanctioned AI Apps

Roughly 33% of employees admit to inputting sensitive information into corporate AI tools (ChatGPT Enterprise, Microsoft 365 Copilot, etc.). Standard DLP solutions were never designed to inspect browser prompts or chat interactions. The Forcepoint AI Data Security solution applies existing classification policies to incoming prompts, outgoing responses, and file uploads within AI platforms without requiring asset reclassification.

12. Behavioral Controls for Autonomous AI Agents

Non-human identities outnumber human users by an 82-to-1 ratio. By the end of 2026, 40% of enterprise applications will feature autonomous AI agents. The Forcepoint AI Agent Gateway module inspects every interaction between agents and applications, enforces human approval gates for critical operations, and maintains a complete audit log.

Comparing Data Protection Approaches

Creating a secure environment requires seamlessly integrating all security components into a unified system.

Fragmented Approach

• Interoperability: Tools operate in isolation from one another.
• Response: Incident detection is delayed due to missing cross-channel context.
• Audit: Manual log collection and reporting during compliance audits.

Unified Forcepoint Data Security Cloud Platform

• Interoperability: End-to-end data classification and centralized policy management.
• Response: Dynamic, risk-adaptive access adjustments based on real-time risk scoring.
• Audit: Automated generation of regulatory compliance proof.

An effective data protection system must be self-learning and adapt to environmental changes faster than an operator can detect an anomaly.

Frequently Asked Questions (FAQ)

What is the difference between a security control and a procedure?

A control is a technical or administrative mechanism that enforces an outcome (such as blocking or encryption). A procedure is the documented process governing how that mechanism is configured, maintained, and audited.

What controls are required for GDPR compliance?

GDPR mandates appropriate technical measures: encryption, access controls, auditing, data minimization, and breach detection. DSPM solutions help verify that these controls are in place and properly configured.

How many security controls does an organization need?

The ideal number depends on your data structure and risk profile. It is recommended to cover five primary domains: visibility, access, data loss prevention, behavioral analytics, and AI governance.

Why Partner with Softprom

The Forcepoint Data Security Cloud platform consolidates all 12 security controls into a unified ecosystem, delivering complete data security across hybrid and cloud infrastructures.

Softprom is an official distributor of Forcepoint. We provide expert assistance to IT and InfoSec professionals in architecture design, proof-of-concept (PoC) testing, and full solution deployment.