Categorizing Cloud Data: A Business Use Case Overview

Reliance on cloud services to store, process, and manage company data is at an all time high. With SaaS products increasingly taking market share, this dependency is only going to grow.

It's important to establish processes to classify company data into public and non-public categories. This is especially important to understand how to use the data effectively and address security gaps before they are exploited. When working with cloud providers, it's important to keep in mind that you're still responsible for your own data.

Healthcare and finance industries must pay particular attention to what data is collected, how its used and stored, in order to maintain compliance. Wholesale and retail companies alike need to also pay attention, as mishandling of customer data can lead to losses in reputation and/or revenue. Really any industry in our modern world should understand their data and manage it properly.

Effective data categorization enables organizations to apply appropriate security measures and define access levels based on the sensitivity and usage of the data. This post explores common data categories in cloud services, discusses management processes for each, and highlights access as well as security considerations.

This is not the most dazzling topic, but so important to understand if you work with cloud data in any manner. Your data can be a blessing or a curse. Knowing how to properly manage it can lead to efficiencies and potential profits. Not managing it correctly can lead to misuse or in the worst case, breaches.

Public Data

Starting light here, public data refers to information that can be openly shared with the public without any security concerns. This data is non-sensitive and can be disclosed without resulting in harm to the business or stakeholders.

A business might publish public data to market its services, such as website content, product descriptions, promotional materials, or press releases. This type of data enhances brand awareness, supports customer engagement, and helps foster transparency with stakeholders.

Access Considerations

Public data should be accessible to external users, clients, or the general public. Businesses often store this data in public cloud environments, which allow for high availability and scalability.

Security Considerations

Although public data doesn't require strict security measures, it's still important to implement basic protections to maintain its integrity, guarding against unauthorized alterations. You can employ version control and ensure that only authorized personnel can edit or upload the data.

Management Processes for Public Data

Step 1: Data Classification
Identify and label the data that qualifies as public, such as website content, product descriptions, and marketing materials. Ensure that the data does not contain any sensitive information before classifying it as public.

Step 2: Data Storage
Store public data in public cloud environments or content delivery networks (CDNs) to ensure scalability and high availability. Use services optimized for public distribution, such as Amazon S3, Google Cloud Storage, or Azure Blob Storage.

Step 3: Access Controls
Allow unrestricted access to public data, ensuring that it's accessible to anyone without the need for authentication. However, editing rights should be restricted to specific team members or departments (e.g., marketing or content management teams).

Step 4: Monitoring and Auditing
Regularly monitor the integrity of public data to prevent unauthorized modifications or deletions. Implement basic logging mechanisms to track content updates and ensure proper version control.

Step 5: Reviews and Updates
Periodically review public data to ensure it's still accurate and relevant. Outdated information should be updated or removed as necessary to reflect the current status of the business.

Public data management involves the least risk.

Internal Data

Getting a bit more stringent, internal data is sensitive information intended for use within the organization. It usually includes operational, financial, or employee data that, though not highly confidential, should not be made publicly available.

Internal data could consist of reports, internal communications, meeting notes, or business strategies. Departments within a company (e.g., HR, marketing, finance) often generate and use this data to optimize business processes and ensure efficient internal operations.

Access Considerations

Access to internal data should be limited to employees of the organization. This is typically controlled through access control systems, where users are granted permissions based on their job functions.

Security Considerations

To secure internal data, businesses should apply encryption at rest and in transit, use multi-factor authentication (MFA) for access, and monitor user activities for any suspicious behavior. Implementing data loss prevention (DLP) strategies can also minimize the risk of internal leaks. Many cloud service providers like Google Cloud Platform encrypt data at rest by default and offer in transit solutions which are best in class.

Management Processes for Internal Data

Step 1: Data Classification
Classify operational, financial, and employee-related information as internal. Conduct a review to ensure this data doesn't include confidential or restricted items.

Step 2: Data Access Management
Implement role-based access control (RBAC) or better yet attribute based access control (ABAC), for internal data. Grant access to employees based on their roles and departmental needs (e.g., HR, finance, operations). Ensure that only authorized personnel can access or modify internal data.

Step 3: Storage and Backup
Store internal data in secure cloud environments, ensuring that encryption at rest and in transit is applied. Set up automatic backups to ensure data availability in the event of loss or corruption.

Step 4: Data Sharing
For inter-departmental data sharing, implement secure file-sharing methods. In cloud environments you can use virtual private clouds (VPCs), and virtual private networks (VPNs), to ensure safe sharing and transfer between authorized individuals or systems.

Step 5: Data Auditing and Lifecycle Management
Regularly audit access logs to track who is accessing internal data and ensure compliance with internal policies. Set up data lifecycle policies to archive or delete internal data when it is no longer needed, ensuring compliance with company retention policies.

Confidential Data

Now we come to the first high risk category. Confidential data includes sensitive information that, if exposed, could significantly impact the organization, its customers, or its partners. This often includes intellectual property, proprietary business information, contracts, and client data.

Businesses frequently deal with confidential data such as non-disclosure agreements (NDAs), client contracts, product roadmaps, and trade secrets. This data is critical for maintaining a competitive advantage and ensuring legal compliance.

Access Considerations

Access to confidential data should be highly restricted and granted on a need-to-know basis. Typically, senior management, legal teams, or specific project teams handle such data, with additional access controls like conditional access policies, to further protect sensitive information.

Security Considerations

Given its sensitivity, confidential data requires strong encryption protocols, tokenization, and key management practices. Cloud service providers offering encryption key management empower businesses to more efficiently control and audit access. Frequent security assessments, data access logging, and automated alerts for unauthorized access attempts should be a standard practice to ensure confidentiality.

Management Processes for Confidential Data

Step 1: Data Classification
Identify data that contains sensitive business information, intellectual property, or customer contracts. Label this data as confidential and flag it for stricter controls.

Step 2: Access Control
Apply strict access controls based on the principle of least privilege. Use role-based or attribute-based access control to ensure only necessary personnel have access. Definitely setup multi-factor authentication for any users who handle this data.

Step 3: Data Encryption
Encrypt all confidential data both at rest and in transit using industry-standard encryption protocols (AES-256 should be highly considered). Implement key management policies that allow the organization to maintain control over encryption keys and maximize the ability to rotate them.

Step 4: Collaboration and Sharing
Limit the sharing of confidential data to highly secure environments, such as encrypted email services or secure cloud collaboration tools with end-to-end encryption. Use data masking techniques when confidential data needs to be shared externally. Sharing in general should be restricted to an as-needed basis.

Step 5: Data Monitoring and Compliance
Set up real-time monitoring and alerts for unauthorized access attempts to confidential data. Perform regular compliance checks to ensure the data is protected according to internal and external regulatory requirements.

Restricted Data

We now arrive at the final and highest risk category. Restricted data is the most sensitive form of data, usually involving personally identifiable information (PII), health records, payment details, or any data that falls under strict regulatory frameworks such as GDPR, HIPAA, or PCI-DSS.

Maintaining compliance with regulations requires careful analysis of data in this category. In situations where personally identifiable information must be stored (preferably a rare occurrence), each item should be evaluated, labelled and almost never moved to another category.

Businesses in sectors like healthcare, finance, and government often handle restricted data. Examples include patient records, credit card information, and legal documents, which are highly regulated and require top notch care when handling.

Access Considerations

Only a limited number of highly authorized personnel should have access to restricted data, often with granular control mechanisms. Role-based and attribute-based access control are commonly used. Administrators should regularly audit who has access and whether or not it's necessary for their job functions.

Security Considerations

The security of restricted data must absolutely be top priority due to the severe consequences of breaches. Businesses must ensure full compliance with regulatory standards, apply encryption both in transit and at rest, and utilize advanced security protocols such as endpoint security, network segmentation, and zero-trust architecture. Data anonymization and masking techniques are also used to protect sensitive records when used in non-production environments.

For this data, there may be situations where it makes sense to store it on-prem instead of in a cloud provider's storage. Secure policies must be created and maintained regarding how this data is transeferred between on-prem and cloud environments.

Management Processes for Restricted Data

Step 1: Data Classification
Identify restricted data such as personally identifiable information (PII), financial data, or health records. Label this data as restricted and categorize it based on applicable regulatory requirements (e.g., GDPR, HIPAA).

Step 2: Access Restriction
Implement highly restrictive access policies for this data. Use multi-layered access control methods, such as zero-trust architecture, to ensure that only specifically authorized personnel can view or edit restricted data. Implement just-in-time access mechanisms that limit how long users can access data.

Step 3: Regulatory Compliance
Ensure that data handling, storage, and transmission meet the legal and regulatory standards governing restricted data. This may include encryption, pseudonymization, and secure deletion processes.

Step 4: Data Encryption and Key Management
Encrypt restricted data using the highest levels of security, such as end-to-end encryption, and store it in secure environments. Utilize robust key management systems where businesses retain control over encryption keys. Implement tokenization for added security.

Step 5: Data Auditing and Incident Response
Maintain continuous monitoring of restricted data access. Set up automated logs and alerts for any suspicious activities or access attempts. Conduct regular internal audits to check for compliance with data protection policies and ensure that any security vulnerabilities are addressed promptly. Additionally, establish an incident response plan in case of a data breach.

Step 6: Data Retention and Deletion
Follow strict data retention policies for restricted data. Securely delete data after it has fulfilled its regulatory or business purpose. Use data destruction techniques that ensure no recoverable copies of restricted data are left behind, such as data wiping or degaussing.

Closing Thoughts

Like I said, this isn't the most dazzling subject, but still very important. It may seem like a topic only relevant to IT or operations, but data is everywhere and in many forms. No matter what your role is, you would be wise to understand it.