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Data Centric Security

What is Data-centric Security?

Data-centric security prioritizes the protection of data itself, wherever it is stored, accessed, or used. This unique approach involves identifying sensitive data, classifying it based on its data type, and implementing appropriate security controls and policies to protect it.

The focus is on protecting data throughout its lifecycle rather than just securing the perimeter of a network or device. This approach includes various techniques and technologies, such as encryption, access management controls, data masking, and data loss prevention tools. It can be applied to on-premise, cloud-based, and hybrid IT environments.

A data-centric security framework is based on identifying, understanding, controlling, protecting, and auditing data. These aspects are necessary to secure critical data, defend against data loss, and identify changes that indicate malicious intent.

Data breaches continue to rise, and IT environments have become more complex. It is critical to adopt a data-centric security architecture to remove blind spots and comply with relevant data privacy laws. By prioritizing data protection, organizations can reduce the risk of data breaches and cyber-attacks. This, in turn, improves their ability to comply with data protection regulations.

How Data-Centric Security Focuses on Data

Why a Data-centric Security Strategy Matters

Data is the core of the business, driving decisions and defining processes and procedures, making it crucial to protect this data. A data-centric approach to security makes data the focal point for security practices. It prioritizes data protection over networks, servers, and applications. This approach ensures that data remains secure, even if other areas of the network or device are compromised.

Organizations can create a comprehensive security design that protects sensitive information by implementing intentional and high-impact security decisions. This approach does not overlook the security of other areas but applies security measures to them to improve data protection.

A data-centric approach to cyber security is driven by several existing challenges in IT operations and security:

  • Insufficient Network Server and Application Security - even the most secure networks are vulnerable to internal risks. Data-centric security protects against unauthorized access and data spillage by focusing on the defense of the data.
  • Need for Access Limitations - Data-centric security leverage fine-grained access controls. These controls ensure that users can only access sensitive resources they need to complete their tasks. Anything beyond what is necessary is prevented. This is particularly important as not all users should have access to every ounce of data in the organization.
  • Seamless Integration - Data-centric security can be added to existing systems without significant disruption, freeing up resources for other purposes.
  • Need to Protect Data at its Core - With data-centric security, data is considered the most critical asset. Security measures are implemented to protect it wherever it is stored, transmitted, or used. This ensures that the data remains secure even if the network or device is compromised.
  • Compliance Mandates - Data-centric security helps organizations comply with data privacy regulations by implementing appropriate security controls and policies to protect sensitive data.
  • Mitigating Evolving Attacks - Cyberattacks have become more sophisticated and targeted, and attackers now focus on stealing sensitive data. By implementing advanced security controls, data-centric security helps organizations protect against these types of attacks.
  • Defending Company Reputation - Data breaches can significantly impact an organization’s reputation and brand value. By adopting data-centric security, organizations can reduce the risk of data breaches and protect their reputation by demonstrating their commitment to protecting sensitive data.

When a Data Focus For Security Is Necessary

Data security has become essential to any organization’s operations, with the increasing amount of sensitive data used for day-to-day operations. As data breaches become more sophisticated and targeted, organizations must adopt a data-centric security approach to protect sensitive data wherever it is stored, transmitted, or used.

  • Protecting Sensitive Data: Virtually all organizations collect sensitive data. This may include customer information, financial data, and intellectual property that must be protected. Data-centric security helps protect this data by implementing security controls such as encryption, access controls, and data loss prevention tools.
  • Compliance with Data Privacy Regulations: At its core, data-centric security helps organizations comply with data privacy regulations and data governance. Implementing appropriate security controls and policies to protect sensitive data helps in meeting requirements like GDPR, CCPA, and HIPAA.
  • Cloud Security: As more organizations adopt cloud computing, data-centric security becomes critical to protect data stored and processed in the cloud. This includes implementing encryption, access controls, and monitoring solutions to protect data in the cloud.
  • Insider Threats: Insider threats can pose a significant risk to an organization’s data security. Data-centric security helps mitigate this risk by implementing access controls, monitoring solutions, and data loss prevention (DLP) tools to prevent unauthorized access and data exfiltration.
  • Secure Data Sharing: data-centric security helps organizations share data securely by implementing access controls, encryption, and monitoring solutions to ensure that authorized users only access and are protected during transmission.

Dig Security Defends Data

Data-centric cyber security is at the core of how Dig Security operates. Dig focuses on providing a comprehensive, end-to-end data-centric security strategy, unlike other security solutions. With Dig, organizations are able to focus on the most strategic data assets, improving their risk posture. 

Dig is an agentless multi-cloud data security platform that discovers, classifies and protects sensitive data. Using Dig’s data classification engine, you can quickly locate your most critical data and organizational “crown jewels” in structured and unstructured data assets. 

Dig prevents exposure of sensitive data with full data security posture management (DSPM) capabilities, highlighting data misconfigurations, access anomalies and data vulnerabilities that increase the risk of a data breach. In addition, Dig is the first to provide real-time data detection and response (DDR) engine to ensure an immediate handling of newly discovered data related incidents by integrating with existing security solutions. 

By combining static posture assessment with dynamic monitoring, Dig focuses on security squarely on the data. This data-centric approach reduces the probability of data breaches and decreases the impact if they occur.