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Sensitive Data

One of the most critical challenges facing many organizations today is effectively protecting sensitive data. The cornerstone of modern business, sensitive data, when mishandled or left unprotected, can expose a company to enormous risks, including financial loss, legal action, and reputational damage.

Sensitive Data: An Overview

Sensitive data is any kind of information that is protected against unwarranted disclosure. It involves a wide range of categories, including personal data, financial information, proprietary details, health records, or trade secrets. When this sensitive data falls into the wrong hands, it can lead to a severe data breach that could devastate a business or harm an individual.

Personal Data vs. Sensitive Data

While not all sensitive data can be considered personal data, all personal data is sensitive. Personal data is any information that can identify an individual, including their name, email address, or phone number. Sensitive data includes personal data but has a wider scope, which includes data that could cause significant harm if disclosed, such as financial account information, health records, or government-issued identification numbers.

Data Security and Data Breaches

As more businesses rely on digital processes and online transactions, the security of sensitive data has become increasingly important. Data security involves a series of protective digital privacy measures applied to prevent theft or unauthorized access to computers, databases, and websites. If these measures fail or are bypassed, it can result in a data breach—an incident where unauthorized parties access and potentially misuse sensitive data.

Data Classification and Data Privacy

Data classification is a vital aspect of data privacy and protection. It involves categorizing data based on its level of sensitivity, value, and criticality. By classifying data, organizations can apply appropriate protective measures and controls to prevent unauthorized access and maintain data privacy.

Understanding the Types of Sensitive Data

When it comes to sensitive data protection, it's important to realize that not all data is created equal. There are several categories of sensitive data, each with its unique implications for privacy and security. Below, we delve into some of the most common types of sensitive data and the regulations associated with their protection.

Sensitive Data types
Brief Reference of Common Sensitive Data

Financial Information

Financial information includes data related to an individual's or an organization's financial status. It encompasses bank account numbers, credit/debit card details, transaction data, and other financial statements. Given its nature, the unauthorized exposure of financial data can lead to severe consequences like fraud or identity theft.

Protected Health Information (PHI)

Protected Health Information refers to any information about the provision of health care, health status, or payment for health care that can be linked together to identify a specific individual. This could include medical records, lab results, health insurance details, and billing information. If this data is compromised, it can result in significant privacy violations and potential harm to the individual's personal and professional life.

Access Credentials

Access credentials generally include usernames, passwords, PINs, and biometric data. Any credentials used to grant or deny access to specific data, systems, or physical locations. When stolen or misused, these can provide criminals with unauthorized access to critical systems and sensitive data.

While there isn't a single regulation for access credentials, they are often covered under various data protection regulations like GDPR and CCPA based on their usage and context. It is best practice to secure them using stringent access management, encryption, and regular updating.

Trade, Proprietary, and Government Information

Trade secrets, proprietary information, and classified government data represent another category of sensitive data. This could range from a secret recipe in the food industry, patented technology in tech companies, to classified national security information in government databases. Unauthorized disclosure of this type of data can lead to loss of competitive advantage, legal issues, or even national security threats.

Several regulations cover this type of data, and these can vary widely based on the industry and country. Examples include the United States' Defend Trade Secrets Act (DTSA) and the European Union's Trade Secrets Directive.

Personal Identifiable Information (PII)

Personal Identifiable Information refers to any data that can be used to identify a specific individual. Names, addresses, phone numbers, social security numbers, and digital identifiers like IP addresses or cookie IDs fall into this category. The misuse of this data can lead to identity theft, fraud, or other forms of cybercrime.

The types of sensitive data your organization handles will shape your data protection strategies and dictate the regulations with which you need to comply. 

Navigating the Landscape of Data Privacy Regulations

Data privacy regulations are legal frameworks designed to safeguard individuals' personal information from unauthorized access, misuse, and breach. They set forth stringent standards for the collection, storage, processing, and sharing of personal data, placing the burden of responsibility squarely on organizations that handle such sensitive data. Here, we explore some of the most pivotal regulations influencing global data privacy practices today.

Understanding the overlap of sensitive and personal data
Understanding the overlap of sensitive and personal data.

General Data Protection Regulation (GDPR)

A landmark in data privacy regulation, the GDPR became effective in 2018 and impacts any entity, irrespective of geographic location, processing the personal data of individuals within the European Union. GDPR enforces strict principles on personal data handling, from its collection to its eventual erasure, prioritizing transparency, data minimization, and the necessity for explicit consent. Non-compliance can lead to hefty fines, up to 4% of the company's global annual turnover or €20 million, whichever is higher.

California Consumer Privacy Act (CCPA)

The CCPA represents a significant stride in U.S. data privacy legislation. Enacted in 2018, the law grants California residents enhanced control over their personal information, entitling them to know what data businesses collect about them, why it is being collected, and with whom it's shared. Additionally, it provides consumers with the right to opt out of the sale of their personal data and the right to non-discrimination for exercising their CCPA rights.

New York Stop Hacks and Improve Electronic Data Security Act (NY SHIELD)

NY SHIELD, effective from March 2020, expands the obligations of businesses handling New York residents' private data, regardless of whether the business is based in New York. It broadens the definition of 'private information' and requires businesses to implement a robust data security program that includes risk assessments, workforce training, and incident response planning, among other provisions.

Health Insurance Portability and Accountability Act (HIPAA)

HIPAA is a U.S. federal law that sets national standards for the protection of sensitive patient health information. It applies to health plans, health care providers, health care clearinghouses, and any of their business associates. HIPAA's Privacy Rule requires the safeguarding of Protected Health Information (PHI), while its Security Rule mandates physical, technical, and administrative safeguards for electronic PHI.

Payment Card Industry Data Security Standard (PCI-DSS)

PCI-DSS refers to the information security standard created by major credit card companies for any organization that handles their branded credit cards. This industry-accepted standard is a baseline of technical and operational requirements businesses are expected to implement to protect account data and mandates ongoing assessments to ensure compliance. Non-compliance can lead to fines, increased transaction fees, and even the loss of the ability to process cards.

Other Relevant Regulations

Numerous other global data privacy laws, such as Brazil's LGPD (General Data Protection Law), Canada's PIPEDA (Personal Information Protection and Electronic Documents Act), and Australia's Privacy Act, continue to shape the data privacy landscape. Therefore, organizations operating in multiple jurisdictions should ensure they understand and comply with these varying requirements.

Data compliance isn't a mere option but a critical business imperative in the modern data-driven landscape. As regulatory frameworks continue to evolve, businesses should regularly evaluate and enhance their data privacy and security measures to ensure they meet or exceed the prescribed standards.

Sensitive Data Protection: Best Practices

Protecting sensitive data requires a robust, comprehensive approach. Here are some key strategies:

  • Implement strong access controls: Implement the principle of least privilege (PoLP), ensuring that employees have access only to the data they need to perform their duties.
  • Encryption: Encrypting sensitive data while at rest and while in transit protects it from unauthorized access or interception.
  • Regular audits and monitoring: Continually monitor and audit data access and usage to detect and respond to potential breaches promptly.
  • Employee training: Regularly train employees on data security best practices and the importance of handling sensitive data responsibly.
  • Data masking and pseudonymization: Use techniques like data masking and pseudonymization to obscure sensitive data, especially in non-production environments.

Understanding and implementing the principles of sensitive data protection is critical for any organization dealing with customer data, proprietary information, or any other form of sensitive data. By adopting robust data security measures, complying with regulations like GDPR, and implementing comprehensive data classification systems, organizations can effectively protect sensitive data and maintain the privacy of the individuals and entities they serve.

Dig Defends Sensitive Data

Dig Security employs a powerful combination of its Data Detection and Response (DDR) and Data Security Posture Management (DSPM) components to effectively defend sensitive data. Dig’s DDR feature provides real-time ability to detect attacks and respond to reduce the impact and stop data from exfiltrating the organization. Dig identifies unusual patterns that may indicate security threats by monitoring data interactions. The platform promptly responds to these threats, mitigating risks and maintaining compliance. This proactive approach is complemented by the DSPM component, which leverages data discovery and classification techniques to scan and analyze structured and unstructured data. Through data classification and risk analysis, organizations can establish a security baseline and ensure that security measures align with regulatory requirements. By unifying DDR and DSPM, Dig Security provides comprehensive protection for sensitive data, mitigating risks, promptly responding to threats, and fortifying organizations’ data security posture. This integrated approach empowers organizations to meet data compliance requirements and defend against potential breaches, ensuring the confidentiality, integrity, and availability of their valuable data assets.

Contact Dig today to find out how their combined DSPM and DDR can help protect your sensitive data.