Not all data is created equal. Therefore, organizations must distinguish between data critical to their operations and those less so. Failure to do so can cause financial, legal, regulatory, and reputational damage.
This article highlights sensitive data and the techniques, strategies, tools, and methods for safeguarding it.
What Qualifies as Sensitive Data, and Why Is Its Protection Critical?
Sensitive data refers to any information that could result in harm or adverse consequences when accessed without authorization. This encompasses personal data such as social security numbers, financial details like credit card or bank information, medical records, and other sensitive information, including trade secrets or intellectual property.
The protection of sensitive data is critical for several reasons:
Privacy: Protecting sensitive data upholds individuals' privacy rights. Negligence in this area can harm individuals, for example, through identity theft or financial fraud.
Compliance: Various industries must adhere to regulations such as the General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and the Health Insurance Portability and Accountability Act (HIPAA), which require safeguarding specific types of data. Failure to comply can lead to significant fines.
Reputation: Data breaches often lead to loss of trust among customers or stakeholders, damaging a company's brand and reputation.
Financial Impact: Data breaches can also result in financial losses besides potential fines. This can occur through theft (as in the case of stolen credit card information) or indirectly through the loss of customers or business partners after a breach.
National Security: Some sensitive data, like classified government information or critical infrastructure details, could pose threats to national security if they fall into the wrong hands.
Given these reasons, businesses and organizations must prioritize protecting sensitive data with robust data security measures, encryption, compliance with regulations, and employee education about data safety.
How Do Businesses Identify and Classify Sensitive Data?
Businesses identify and classify sensitive data through a process that often includes the following steps:
- Inventory of Data: First, the company must compile an inventory of all data within its possession. In doing this, they identify the types of data they are dealing with, where it resides, and who has access to it.
- Classification of Data: Next, the business classifies the data according to its sensitivity. Classifications commonly used include public, internal, confidential, and highly confidential or restricted.
- Public data (business contact information, marketing materials, etc.) can be accessed by anyone.
- Internal data, such as operational data, internal reports, memos, etc., is typically used within the business and not meant for wider circulation.
- Confidential data is more sensitive and should only be accessed by specific personnel (personal data of employees, customers, financial data, or intellectual property).
- Highly confidential or restricted data includes data that, if breached, could have serious legal and financial implications (personally identifiable information (PII), sensitive personal data, trade secrets, legal documentations, compliance data).
- Data Labeling: Once classified, data should be labeled, tagged, or otherwise marked to reflect its level of sensitivity. This makes it easier to identify and apply appropriate security controls.
- Access Controls: Based on classified data, businesses set access controls to ensure that only authorized users can view or manipulate sensitive data, thereby preventing unauthorized access.
- Regular Auditing: After classifying data, periodic audits should be conducted to ensure the data is accurately classified, including updated or new data.
- Training Employees: Companies should train their employees about the importance of data classification, how to classify data, and the measures employed for protecting each type of data.
- Implementation of Policies: Companies must implement policies concerning the handling and sharing of sensitive data within and outside of the organization.
Tools like Data Loss Prevention (DLP) software can automate data identification, classification, and protection.
What Are The Common Types of Sensitive Data In Different Industries?
Sensitive data varies across industries depending on what each considers critical to their operations or holds as confidential information. However, some common types of sensitive data include:
- Healthcare: In the healthcare industry, the most sensitive data includes Protected Health Information (PHI) such as patient health records, medical histories, test results, insurance information, and other related personal data.
- Education: Sensitive data can involve student records in educational institutions, including admission forms, transcripts, disciplinary records, financial aid information, and education records protected under the Family Educational Rights and Privacy Act (FERPA).
- Finance: In the financial sector, sensitive information includes Personal Identifiable Information (PII), credit card information, and banking details. It also includes financial statements, transaction records, and proprietary financial models or strategies.
- IT/Technology: Sensitive data for technology companies might include trade secrets, source codes, algorithms, patent applications, confidential project plans, customer data, and strategic plans.
- Retail/E-Commerce: Sensitive data can involve customers' PII, credit card information, purchase histories, marketing data, and business plans in the retail and e-commerce industries.
- Government: Sensitive data for government institutions includes citizens' PII, classified information relating to national security, public safety information, and other protected government data.
- Legal: Sensitive data in the legal field includes client information, case files, trial strategies, and confidential communications protected by attorney-client privilege.
- Manufacturing: Sensitive data in the manufacturing industry might include proprietary manufacturing processes, design blueprints, supplier contracts, and client information.
The Risks Associated with Sensitive Data Breaches
Sensitive data breaches create cascading risks that can devastate both individuals and organizations. Financial consequences include unauthorized transactions, fraud, and substantial remediation costs, while stolen personal information enables identity theft and criminal impersonation. Beyond immediate monetary losses, breaches inflict severe reputational damage that erodes customer trust and business relationships, often resulting in lost revenue and market share. Organizations face additional pressure from legal and regulatory penalties under frameworks like GDPR, CCPA, and HIPAA, which impose significant fines for inadequate data protection. Operational disruptions frequently cause service downtime and productivity losses, while compromised intellectual property or trade secrets can eliminate competitive advantages and benefit rivals. The aftermath typically requires substantial cybersecurity investments to prevent future incidents, and when employee data is involved, workplace trust and morale suffer, creating internal challenges that compound the external damage.
What Are the Best Practices for Securing Sensitive Data at Rest and Transit?
Protecting sensitive information from unauthorized access requires securing data while it is stored and during transmission.
Best Practices for Securing Data-at-Rest
- Data Encryption: Use strong cryptographic methods like AES to encrypt sensitive data stored on hard drives, databases, or backup storage.
- Access Controls: Enforce permission-based restrictions to regulate access to encrypted data, incorporating multi-factor authentication when required.
- Regular Audits: Conduct regular audits to identify vulnerabilities and ensure the data is adequately secured.
- Data Classification: Classifying data according to its sensitivity helps determine what level of security is required.
- Security Updates: Regularly update and patch hardware and software to protect against potential security vulnerabilities.
- Data Disposal: Safely dispose of old hard drives and backup media to ensure that the data cannot be retrieved.
Best Practices for Securing Data-in-Transit
- Secure Transmissions: Always use secure transmission channels, such as HTTPS for the Internet and SSL/TLS and VPNs for internal networks, to encrypt data during transit.
- E-mail security: Avoid sending sensitive information via email. Use email encryption tools if needed.
- Secure File Transfers: When transferring data between systems, utilize secure file transfer protocols like SFTP or FTPS.
- Network Security: Utilize firewalls, intrusion detection systems (IDS), and intrusion prevention systems (IPS) to safeguard and monitor network traffic.
- Mobile Data Security: Enforce strict security measures for accessing data via mobile devices, including using VPNs and encryption.
Finally, in addition to these best practices, it is important to implement a comprehensive data security policy and train employees to understand the risks and responsibilities of handling sensitive data.
Also, consider investing in a data loss prevention (DLP) solution to monitor, detect, and prevent data breaches.
The Legal and Regulatory Considerations for Handling Sensitive Data
Numerous legal and regulatory considerations accompany the handling of sensitive data. These revolve mainly around protecting individuals’ privacy and aiming to secure data integrity, confidentiality, and availability.
Here are some legal and regulatory aspects that companies must consider:
Data Protection Laws: Different jurisdictions have different data protection laws. Some prominent ones include the EU General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), and the Personal Data Protection Act (PDPA) in Singapore. These laws enforce strict guidelines on how sensitive data should be handled.
Consent: Many laws require companies to obtain explicit consent from individuals before collecting and processing their sensitive data. Additionally, individuals should have the right to withdraw their consent at any time.
Purpose Limitation: Sensitive data must be gathered for defined, clear, and lawful purposes and should not be processed further in a way that conflicts with those purposes.
Data Minimization: Organizations should only collect the minimum amount of data necessary to fulfill their processing purpose.
Storage Limitation: Personal data should be retained in an identifiable form only for as long as necessary to fulfill the purposes for which it is processed.
Security Measures: Adequate security measures, including encryption and pseudonymization techniques, should be in place to protect sensitive data.
Third-Party Disclosures: Considerations must be taken when sharing data with third parties. These parties must comply with the exact legal and regulatory requirements.
Data Transfer: Concerns arise when transferring data across borders, as different countries have different data protection standards. GDPR, for example, has strict rules about transferring data outside the EEA.
Breach Notification: In the event of a data breach, laws like the GDPR and CCPA mandate that companies notify affected individuals and regulatory authorities within a specific time frame.
Record Keeping: Companies must often keep detailed records of their data processing activities.
Data Protection Officer: Some organizations are required to appoint a data protection officer to oversee their data handling practices and ensure they comply with relevant laws.
Failure to comply with these regulations may result in substantial fines, legal action, and severe reputational harm. Therefore, they must be crucial to any organization's data handling policy.
Learn How Fortra DLP Can Protect Your Sensitive Data
Improper handling of sensitive data can lead to severe consequences such as reputational damage, financial losses, legal complications, and regulatory penalties. That's why you need data protection tools that safeguard your most sensitive data, whether that data is stored or being used on an endpoint, moving through the cloud, or even in the hands of a third party. Fortra's Data Loss Prevention, in combination with our other data protection tools, deliver this kind of data security while keeping your employees productive.
Get a demo today to see our tools in action and to see firsthand how it can work for your organization.
