Data Risk Mitigation

As organizations collect and process more personal data, the risk of privacy violations, data breaches, and regulatory non-compliance continues to grow. This article outlines practical strategies to reduce data privacy risk, from mapping data flows and minimizing collection to automating data subject request responses. By implementing these best practices, businesses can strengthen trust, improve compliance, and safeguard sensitive information in an increasingly complex privacy landscape.

Understanding Security Risks

Digital technology’s proliferation means the biggest businesses collect and store massive amounts of sensitive data, including personal information about customers and employees.

Companies are responsible for protecting this sensitive information from unauthorized access and other data security risks. This blog focuses on data risk mitigation issues, concepts, and strategies to help organizations recognize their vulnerabilities and proactively implement risk management functionalities.

Data Breaches and Cyberattacks

Currently, cyberattacks, data breaches, and phishing scams impact more people than ever and are costlier to deal with. IBM’s Cost of a Data Breach Report 2022 lists the average cost of a single data breach in the United States and around the globe at $9.44 million and $4.35 million respectively.

Companies failing to adequately protect personal, sensitive information from vulnerabilities can expect financial health issues, and run the risk of suffering long-term reputational damage and a loss of customer trust.

As such, strong data security and cybersecurity programs are crucial aspects of risk mitigation.

Common types of cyberattacks include but are not limited to:

• Ransomware and Malware
  All ransomware is malware, but not all malware is ransomware. Malware is software designed specifically to infiltrate and disrupt, damage, or gain unauthorized access to a system. While ransomware falls under the malware umbrella, it’s used to deny victims access to their files or systems and demand a ransom in exchange for returning access.
• Phishing and Social Engineering
  Similar to the relationship between ransomware and malware, phishing is a type of social engineering attack. Social engineering attackers use social skills to psychologically manipulate victims to share sensitive information or take action that helps an attacker.

Identifying Vulnerabilities

One of the first steps in the risk mitigation process is identifying and assessing the organization’s data vulnerabilities and potential risks. Part of this process involves accounting for the amount and type of sensitive data and personally identifiable information (PII) held by an organization so there’s a clear understanding of what data needs to be protected and how.

Generally, there are 4 types of data classifications:

1. Public Data (Least Sensitive) — Any information that can be made freely accessible by anyone or is already available, e.g., public records, press releases, and promotional materials.
2. Internal-Only or Internal Data — Restricted to an organization’s employees or members, e.g., business plans and internal communications.
3. Confidential Data — Sensitive information requiring elevated access permissions within the organization.
4. Restricted Data (Most Sensitive) — Information carrying significant legal and regulatory penalties if accessed improperly.

Classifying data according to these categories allows those responsible for data risk management to quickly determine if sensitivity-based protections are present and appropriately enforced.

Risk Management and Mitigation Strategies

Risk Assessment and Decision-Making

Conducting ongoing cybersecurity risk assessments is essential for mitigating data security issues. However, while essential, these assessments can include massive amounts of data and be deeply complex.

Manual Data Risk Assessment Process:

1. Inventory sensitive data
2. Assign data classifications
3. Review applicable security and privacy controls
4. Assess privacy/security shortcomings and potential risks

Implementing these processes provides clarity about a company’s risk level, leads to better decision-making when it comes to mitigating data risk, and lays the foundation for a comprehensive risk management plan.

Data Governance and Regulatory Compliance

Data governance is the overall set of actions to ensure stakeholder and customer data is secure, private, accurate, available, and usable. The steps to implement a data governance framework include:

1. Define data strategy, goals, and objectives
2. Secure essential stakeholder and executive support
3. Document organizational data policies
4. Establish governance roles and responsibilities
5. Implement and evaluate the data governance strategy

What are Best Practices and Security Measures for Data Risk Mitigation?

Implementing data security policies and procedures for a company-wide data risk mitigation program is essential. Key tools include:

Risk Management Analysis

1. Identify existing risks
2. Assess and evaluate threats
3. Implement measurements for risk handling
4. Continue monitoring and reporting risks

Least Privilege and Access Control Principles

Implement the principle of least privilege to limit data access to only those a user requires for their tasks.

Strong Passwords and Multi-Factor Authentication

Implement strong passwords and multi-factor authentication to fortify data security across the organization.

Data Privacy Training for Employees

Data privacy awareness training helps equip employees with the knowledge and skills needed to handle data securely, covering regulations, best practices, and identifying sensitive data.

The Human Factors in Data Risk Mitigation

Employee Education and Phishing Awareness

Training should focus on practical examples, case studies, and interactive exercises to engage employees on data privacy principles and best practices. Key training topics include:

• Introduction to Data Privacy
• Data Protection Regulations
• Identifying and Handling Sensitive Data
• Security Best Practices
• Social Engineering Awareness

Minimizing Human Error and Insider Threats

Cultivating a security-first environment, supported by automation, helps reduce the chance of human error and insider threats.

Data Risk Mitigation Today

Emerging Threats and Security Risks

Mitigating risk is an ongoing process. Keeping pace with technologies, including AI, can improve data risk management while also anticipating potential risks.

How DataGrail Helps Mitigate Your Data Risk

DataGrail is a privacy platform that aids in regulatory compliance with privacy laws, automating privacy workflows, and providing insights with a comprehensive dashboard. Companies can rely on privacy expertise and industry-leading customer support.