8 Data-Centric Security Strategies to Determine Risk of a Breach

8 Data-Centric Security Strategies to Determine Risk of a Breach

Data-centric security is growing in popularity as a solution for companies concerned about cyber threats and breaches like phishing scams and ransomware attacks. A data-centric security strategy aims to protect a company’s assets and resources by identifying, analyzing, and mitigating the risks associated with these assets. Here are eight features your data-centric security strategy must provide.

1. Data stewardship

Authorizing access to authorized personnel only is an integral part of protecting an organization’s sensitive information from the breach. Data stewardship is a process of managing and safeguarding data. It ensures that people have access only to the information they should have access to. All-access is limited to people who work in the company. They need to have a valid reason for accessing the information. Data must be encrypted to protect it from unauthorized use, especially when conducting transactions.

2. Data classification

Data classification helps protect organizations because data owners have to know their sensitive information, where it is located, how it was categorized, and when someone is looking for this information.

The owners of the data have to classify their information based on a set of standards determined by the business category in which the information falls. For example, the criteria to organize financial information will differ from those to classify human resources information. While there is no one-size-fits-all approach for data classification, high-level guidelines can help determine how data owners categorize and secure their sensitive information.

3. Data minimization

Data minimization involves limiting the amount of sensitive data that an organization collects and stores as much as possible. A data-centric security strategy consists in creating different security controls based on the sensitivity of the information. Organizations that collect over-sensitive information are at higher risk for this data breach than organizations that collect less sensitive information.

Limiting the collected information not only protects the organization from an accidental or intentional breach but also reduces the amount of regulatory and compliance requirements under which the organization must manage.

4. Data encryption

Data encryption involves encrypting sensitive data to make it inaccessible to unauthorized individuals. The encrypted data can only be decrypted by authorized personnel, which minimizes the risk of an unauthorized person or organization gaining access to this data. Encryption also helps protect against accidental or intentional data loss due to a technical failure or someone intentionally accessing the files and removing them without authorization.

5. Data validation

Data validation is the process of ensuring that the data is correct prior to entering it into the system. This ensures that the data matches the original information and that all fields are filled out correctly.

Data validation helps protect against accidental or intentional data loss due to a technical failure or someone intentionally accessing the files and removing them without authorization. The cloud storage service can help to reduce the risk of a breach in sensitive data. It does this by having copies in multiple locations and requiring attackers to compromise all of them to access the information.

6. Data monitoring

You should have a system in place to monitor your data. The owners of the data should have access to systems that track the security of their sensitive data. These systems should provide reports so that senior management can track the security of their data over time.

A data-centric security strategy reduces the risk of an intentional or unintentional breach by senior management. With this security strategy, senior management communicates to the rest of the organization that they are serious about data protection and policies allow for this protection.

7. Data lineage

Data lineage involves tracking changes made to a piece of data throughout its life cycle and ensuring that only authorized personnel makes these changes. For example, the organization needs to track how someone from another department could access financial information while working on a project.

8. Data audit

Data audit involves monitoring the security control processes and procedures and ensuring that controls are in place to protect the data. This helps ensure that data remains secure throughout its life cycle. It is also important to ensure that business processes adhere to their data security standards to avoid any unnecessary risk associated with lost or stolen information.

Closing Notes

The emerging response to security challenges is the data-centric security of today that has arisen from the rapid advancements of computing technology. Data-centric security fundamentally embraces a new perspective of understanding information security through the lens of data and applying data-centric security strategies to control access to sensitive information appropriately.

While many organizations are still struggling with the basics involved in protecting their sensitive data, senior management must understand what their organization is doing to protect this information and recognize that even basic controls can help reduce the risk of an accidental or intentional breach.

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