HomeSecurityHow Does Database Security Risk Assessment Guard Sensitive Information?

How Does Database Security Risk Assessment Guard Sensitive Information?

web hosting server database Companies store a lot of user, client, employee, and corporate data.

This same information is often dispersed across versatile complex systems such as hybrid and multi-cloud infrastructures — making it challenging to know where it is at all times, let alone protect it from cyber threats.

With all the recent data leaks, breaches, and hacking activity headlining the news, it’s evident that cybersecurity has a major role in protecting information, but also that threat actors are after sensitive data to make a quick profit.

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To avoid major financial losses and damages to reputation, organizations have been using database security risk assessment, a cybersecurity system for data protection that identifies and catalogs data to conclude whether they’re at risk.

How does it work, exactly?

Here, we cover the key steps of database security risk assessment and protection.

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Identification of Sensitive Data

protecting sensitive data with cybersecurity Nowadays, information is scattered in the cloud and hybrid environments as well as on-premises. Regardless of the location, IT teams need to have a clear overview of the data at all times.

Therefore, the first step in successful database security risk assessment is in pinpointing:

  • Where is the data stored within the network
  • Which files contain critical data — those documents that contain more personal information are at greater hacking risk
  • Who has access to the information

Special attention is paid to sensitive information. Depending on the business, this might refer to medical records, social security numbers, credit card numbers, birthdays, or home addresses.

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Security tools for risk assessment use regular activity (such as who normally accesses specific data) to map what is normal for a company. This is a starting point, and facilitates the identification of suspicious (unusual and potentially unauthorized) activity.

Recognizing Potential Risks

Another thing that’s necessary is to identify which risks could compromise sensitive data and critical systems. By risk, we mean anything that could harm the business and result in stolen and leaked information.

Common cyber exploits that target data are:

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  • Ransomware — malware that locks information and seeks ransom in exchange for the key that unlocks critical files
  • Phishing — scams that aim mostly at unsuspected employees via email
  • Insider threats — such as an employee misusing their credentials for malicious activities that can damage the company

The architecture and data management of every business is unique. In this step, it’s necessary to decide whether the company is at risk from those or other types of exploits.

Most companies consult the MITRE Framework to make sure their system is patched against known vulnerabilities and to protect themselves from the zero-day exploits that have been added to the growing library of hacking techniques.

Analyzing the Discovered Information in Context

Once all the information is cataloged and the context/possible risk mapped, it’s necessary to compare that with any new information that has been generated about the security posture of the company.

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Does the data point to a possible incident taking place or is it at risk of hacking due to unpatched vulnerabilities?

For instance, depending on the data that a company has, the tool answers questions such as: Does someone who is not supposed to have access to certain data management have entry into the network?

To determine that, the context of the organization is taken into consideration — including the time the information is accessed and who is attempting to use privileges and credentials.

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Even more, a potential incident is linked to the information about the data that is being managed within the system.

That is, security analysts can easily see on the dashboard which data is being compromised and targeted during specific hacking activity.

Reducing Hacking Risk

ramsomware hacker data breach warning security Mitigation is the last step that follows assessing if the information is at risk of cyber threats.

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Once IT teams have all the reports they need to determine which vulnerabilities are putting data at risk and which information might be affected, it’s necessary to fix the gaps in the security.

Teams have to either respond to the incident, improve the security (add solutions, or configure them to suit the company), or apply the patches that have been provided by other vendors.

Introduce employee training if the issue is centered around human error. This might include falling for phishing scams, having weak passwords, or not knowing how to use certain security tools at hand or configure components in the cloud.

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Essentially, IT teams need to manage security and do regular cybersecurity hygiene.

Repeating Steps With Automation

Data risk management is governed by AI-powered tools that enable 24/7 protection and risk assessment. For example, Data Security Fabric (DSF) is a solution that can run in the background at all times and protect information.

DSF is adjusted for the companies that have been using the cloud and will continue the growth using such environments.

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Nowadays, security teams don’t have the time to manually track suspicious user activity that might result in breached data.

However, due to multiple databases that are often in silos, automation is necessary to identify and make sense of the information in the specific context of the business in question.

What’s more, artificial intelligence also allows security analysts to discover and mitigate weaknesses early, before they escalate into data breaches.

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Modern Architectures Seek Enhanced Security

security systems Database security risk assessment starts with identifying all the information a business holds within the network.

That information is then cataloged and assessed for risk (possible data leaks, unauthorized access, or a major breach).

The next step is protecting the information that is likely to be exploited by hackers.

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These steps do not occur in sequence, but are often overlapping, intertwining, and are continuously repeated.

Within modern structures such as clouds that are rapidly changing, it’s getting more challenging than ever before to protect the information that is circling the network.

New hacking exploits, remote, work, and databases filled with sensitive user data require security that can keep up with the pace.

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