Data Risk Assessment

What is Data Risk Assessment?

Data Risk Assessment is the process of evaluating the potential risks associated with an organization’s data assets. It involves identifying the types of data an organization collects, where it is stored, who has access to it, and how it is used.

Why Data Risk Assessment is Crucial

Companies have been collecting and storing an ever-increasing amount of data which is no longer stored just on premises but has expanded into numerous cloud locations. The explosion of data growth has made it difficult for organizations to maintain visibility into their data, leading to a lack of understanding of what data they have and where it is stored. This lack of visibility creates a significant risk for companies, as they cannot adequately protect their sensitive information from data misuse, compliance breaches, and data exfiltration.

Companies cannot effectively manage their risks and secure sensitive information without visibility into their data. As a result, organizations must prioritize data discovery and risk management efforts to ensure that they maintain visibility into their data and protect it from potential threats.

A data risk assessment identifies and prioritizes potential data confidentiality, integrity, and availability risks. An organization can better understand its risk exposure, implement appropriate security controls, and comply with data protection regulations by conducting an assessment as part of its data risk management process. It is essential to any data security strategy and should be performed regularly to ensure ongoing risk management. These assessments can be completed using internal teams and tools or by hiring data risk management services to automate and streamline assessment processes.

When Assessing Risk is Necessary

With the increasing amount of data being generated and stored, the risk of data breaches, cyber-attacks, and regulatory compliance violations is higher than ever. By conducting a data risk analysis, organizations can comprehensively understand their data assets, their vulnerabilities, and the potential impact of a data breach or security incident. This knowledge informs their risk management strategy and helps them prioritize investments in data security measures.

Managing data protection risks is never one size fits all, but instead needs to be determined by the individual organization. Some business processes mandate assessing and managing different types of data risks. Some functions, such as cybersecurity, will be universal across all organizations. While others, such as compliance, will be specific to the industry vertical and types of data stored and processed.

The following list is a sample of different business processes that may lead to assessing data risks:

Compliance: Many regulations require organizations to identify and manage risks for their data. Managing and reducing risks for data can help ensure compliance with regulations such as GDPR, HIPAA, and PCI-DSS.
Cybersecurity: Security assessments help identify and manage cybersecurity risks, such as unauthorized access, data breaches, and ransomware attacks. They identify sensitive data types, such as personally identifiable information (PII) or financial data; organizations can customize their controls to reduce risk most effectively.
Data governance: Data risk management can help organizations ensure the accuracy, completeness, and integrity of their data, which is critical for making informed business decisions.
Cloud migration: Organizations are increasingly moving their data to the cloud, and data risk management helps ensure that data remains secure and compliant during and after the migration process.
Third-party risk management: Organizations often share their data with third-party vendors, creating additional data risks. Data risk management can help identify and manage these risks to protect sensitive data.
Mergers and acquisitions: Mergers and acquisitions involve data transfer between organizations, which creates additional data risks. Data risk management can help ensure that the transfer is secure and compliant.

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What are the Benefits of Assessing Data Risk?

Data risk assessments are crucial for making cost-effective decisions in cyber security. As budgets are not infinite, organizations must make targeted decisions to apply their security efficiently. This is made all the more difficult as organizations face multiple challenges, such as preventing data misuse, compliance breaches, and data exfiltration for widespread data across on-premises and cloud locations.

By conducting data risk assessments, organizations gain an in-depth understanding of their data, its posture, and what risk it is currently in. Without understanding what data they have and its existing risk posture, it is impossible to protect it. Using the information derived from these assessments, they can better align their security controls to address the highest-risk items reducing the likelihood of a data breach or exfiltration event while maintaining compliance with industry regulations.

Improved Data Security: A data risk assessment helps organizations identify and prioritize potential data security risks, allowing them to implement appropriate security measures to mitigate those risks and prevent data breaches.
Regulatory Compliance: Many industries have regulations that require organizations to conduct regular risk assessments. A data risk assessment can help organizations identify compliance gaps and ensure they are meeting regulatory requirements.
Cost Savings: By identifying and mitigating data security risks, organizations can reduce the costs associated with data breaches, such as lost revenue, legal fees, and reputation damage.
Better Decision Making: A data risk assessment gives organizations a comprehensive understanding of their data security posture. This information drives making informed decisions about which data security measures to implement and prioritize.
Improved Customer Trust: By demonstrating a commitment to data security through regular risk assessments, organizations can build trust with their customers and stakeholders, ultimately enhancing their reputation and brand value.
Proactive Approach: Conducting data risk assessments allows organizations to proactively approach data security, identifying and mitigating risks before they become critical issues.

Assessing Risk in Cloud Data

Assessing risk in cloud data has become an essential component of data security management. As organizations continue to store large amounts of sensitive data in the cloud, understanding the risks associated with these data sets becomes more crucial. Risk assessment in cloud data involves:

Evaluating the types of data stored to determine security and privacy requirements.
Identifying potential vulnerabilities and deviations from best practices or organizational requirements.
Assessing an attack’s likelihood and potential impact based on the risk posture.

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By analyzing the security controls to protect the data and identifying gaps in your organization, you can address threats well before they become a reality. Regular risk assessments followed by the implementation of right-fit controls help organizations better protect their cloud data and reduce the risk of data breaches, data exfiltration, non-compliance, and cyber-attacks.

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Dig Distills Risk Posture

Dig helps organizations implement holistic data protection in the cloud with its Data Security Posture Management (DSPM). DSPM sets the foundation for comprehending cloud infrastructure, identifying what data exists in the multi-cloud environment, and determining its security posture. This creates a baseline allowing organizations to know what data can be lost.

Using DSPM, organizations conduct data discovery to identify the content and context of data stored in the cloud. Dig then analyzes the data contents creating a highly accurate classification of what is contained, allowing organizations to prioritize risks effectively. Then using a risk analysis process for sensitive data helps enforce policies and practices across the enterprise and multi-cloud infrastructure.

Understanding the posture of the data is only the beginning. Dig’s platform also delivers Data Detection and Response (DDR) to detect changes in the cloud data security landscape as they happen, identifying risky behaviors and exfiltration attempts.

With DDR, cloud logs are analyzed in real-time, monitoring changes to detect data risks as they occur. Changes such as data moving from encrypted to unencrypted space or data flowing into physical spaces that would cause data sovereignty issues are rapidly detected. Using an advanced threat model, these behaviors are assessed for potential risk, differentiating appropriate utilization of permissions from high-risk behaviors such as data exfiltration.

While DSPM is a more static variety of data risk assessment, DDR provides the dynamic portion to ensure that data remains protected at all times. Without both components in use, organizations only have a partial view of their data landscape at any given time, limiting their ability to manage their data risks.