What is Security Data? Importance and Types of Cybersecurity Data Insights

By Kasey Hewitt

Posted on Jun 11, 2020

With the cyber threat landscape evolving in complexity, it has become increasingly difficult for organizations to maintain effective security programs. While security solutions can help to secure critical assets, they typically only respond to incidents after they occur. This gives an advantage to cybercriminals as they can see how the organization responds to threats and modify their attack vectors accordingly.

A key component of a successful cybersecurity program is its ability to take a proactive approach to threat detection. With proactive cybersecurity, companies are better able to identify and mitigate vulnerabilities before an attack can be carried out.

One way to enable proactive cybersecurity at your enterprise organization is through the use of security data. Security data compiles cybersecurity signals within network traffic to build intelligence databases that can be used to identify threat indicators. This provides valuable insights into cyber threat vectors and allows organizations to more accurately quantify risk and manage threats.

How security data technology works

At SecurityScorecard, our Security Data leverages different aspects of data collection and analysis to deliver top-quality cybersecurity insights to organizations.

The process begins with a data collection engine that is used to compile and analyze large quantities of data from various IP’s across the internet. These engines then scan the data looking for threat vectors such as malware, ransomware, and botnets. Tracking threat activity allows data engines to identify weaknesses in an organization’s cybersecurity posture - these could include weak ciphers, out-of-date software, and more.

Machine learning algorithms are also used for further threat analysis. By cross-referencing collected data with information from existing threats, machine-learning is able to identify both modified and new versions of known attack vectors. Artificial intelligence also analyzes patterns in cybercriminal behavior to rank vulnerabilities based on the risk they pose to an organization. With insights gained from AI, security teams can prioritize threats in real-time, helping to optimize available resources.

Use cases for cybersecurity data

The visibility gained from security data can be used to enhance multiple aspects of enterprise operations as it allows for informed decision making.

Below are three use cases for cybersecurity data:

1. Enterprise cyber risk management

In the digital age, cybersecurity has become an increasingly important part of enterprise risk management (ERM). Many organizations are now taking an integrated approach to ERM so they can evaluate cyber risk as it relates to their business objectives. However, for these programs to be effective, businesses must be able to maximize the cybersecurity data that is available to them.

With security data platforms, businesses can efficiently manage their cybersecurity and remediate enterprise risk in real-time. Organizations can then easily coordinate risk mitigation procedures across departments, saving both time and money.

2. Third-party risk management

For organizations that rely on vendors to assist with day-to-day operations, they must monitor third-party risk to protect from threats. Insights from security data engines provide context into vendor risk environments which helps businesses streamline management processes. With a holistic view of your vendor ecosystem, you can more accurately report on risk and vendor cyberhealth.

Security data can also help you determine your organization’s risk appetite and assessment scope. These play an important role when creating vendor questionnaires as they dictate how accurately you are able to assess vendor risk as it relates to your business.

3. Cyber due diligence

When purchasing a company or working with a third-party vendor, you incur their cyber risk. That’s why you must have effective cyber due diligence programs in place.

Without ongoing due diligence, organizations can unwillingly expose themselves to threats and damage their reputation. Security data centralizes information on past cybersecurity incidents so you can ensure that the metrics you use to track due diligence are up-to-date and reliable.

During the merger and acquisition phase, this is especially beneficial as it provides insights that can be used to make data-driven business decisions. Security data also highlights how well third-party vendors are managing risk so that you can make improvements if need be.

How SecurityScorecard’s Security Data can help

Having access to cybersecurity data can help you secure critical assets and better manage risk at your organization. With SecurityScorecard’s Security Data, organizations can leverage cybersecurity data to gain insights into their enterprise and third-party ecosystems. SecurityScorecard’s global security intelligence engine continuously collects and analyzes a broad range of highly relevant, cybersecurity signals, allowing you to address threats in real-time.

Security Data also uses machine learning algorithms to quantify and rank threats so that you know which vulnerabilities pose the greatest risk to your business. By continuously monitoring the risk posture of your ecosystem, you can efficiently scale risk management and cybersecurity programs while reducing costs.

With Security Data, organizations can take a proactive approach to cybersecurity by ensuring their security practices align with their business objectives.

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