Privacy Primer for vCon Developers

2.2.1. Key Roles in Data Processing

The following terms are used by the GDPR and in the privacy industry in general to define the three key roles in data processing:¶

1. Data Subject: The individual whose personal information is being processed (also referred to as “consumer” in this RFC and many personal data privacy laws).¶

2. Data Controller: An organization or individual with decision-making authority over data processing who determines the purposes and methods of data processing, bears primary responsibility under privacy laws and is the main target of most privacy and data protection regulations.¶

3. Data Processor: Often a third-party service provider who processes data on behalf of the data controller. Under Health Insurance Portability and Accountability Act (HIPAA), data processors are referred to as "business associates." Data processors may be hired for specialized tasks or to improve efficiency; can subcontract to other processors, creating a chain of responsibility; must operate within the scope defined by the data controller; and are expected to maintain trust and adhere to the controller's guidelines.¶

The relationship between these entities forms a hierarchy of responsibility and trust. The data controller sets the parameters for data use, while processors at various levels must operate within these boundaries. This structure ensures accountability and helps maintain data privacy throughout the information processing chain.¶

2.2.2. What Rights in Their Data do Consumers Have?

Regarding individual rights in data privacy, organizations should focus on six key areas:¶

1. Notice of Data Processing: Organizations must clearly communicate their privacy policies and practices. This includes explaining what personal data is collected and for which purposes, how it is used, stored, and shared, and how consumers can exercise their data privacy rights. This ensures transparency, holds data controllers accountable, and empowers individuals to make informed choices about their personal information.¶

2. Consent: Organizations need to obtain data subjects’ informed and freely given consent for collecting, using, storing, and sharing personal data. Different levels of consent may apply to different kinds of data or in different jurisdictions:¶

   • Consent can be affirmative (“opt-in” consent) or presumed unless stated otherwise (“opt-out” consent). Opt-in consent is usually required for sensitive data processing.¶

   • Consent can be written, oral, or implied.¶

   • In some jurisdictions, such as California, consent must be sought at or before the point of data collection.¶

3. Access: Organizations should offer mechanisms for consumers to access and correct their personal data. This empowers people to ensure their data is accurate and up-to-date.¶

4. Data Choices: In addition to rights to access and correct, data subjects often have the following data privacy rights:¶

   • right to have their information deleted (also referred to as the “right to be forgotten”);¶

   • right to port their data to a different data controller;¶

   • right opt out of certain data practices, such as sale of their data, profiling, targeted/cross contextual behavioral advertising, automated decision-making.¶

5. Non-Discrimination: Organizations must not discriminate against consumers who choose to exercise their data privacy rights.¶

6. Breach Notification: The large amounts of data held by organizations attracts cybercriminals, increasing the risk of data breaches. To mitigate the consequences of data breaches and incentivize advanced data security practices, most jurisdictions require prompt notification of affected individuals when breaches occur (within 30 days of discovery being the industry practice in the U.S.). This holds organizations accountable for data security and allows individuals to take protective actions.¶

By addressing these areas, organizations can respect individual privacy rights and build trust with their customers or users. This approach aligns with many modern data protection regulations and best practices in privacy management.¶

2.2.3. What Data Is Protected?

Data privacy laws protect personal information, though its scope can vary across different laws. In general, the term “personal information” (also known as “personally identifiable information” or “PII”) includes information that makes it possible to identify an individual or information about an “identified” or “identifiable” individual. California extends the scope of PII to include information about a consumer and the consumer’s household, as well as employment data. Examples of PII include:¶

• Basic identifiers: Name, addresses (postal and email), government-issued identification numbers¶

• Digital identifiers: IP address (in some jurisdictions like California).¶

• Financial Data: financial account number or credit or debit card number, often in combination with any required security code or password that would permit access to a data subject’s financial account.¶

• Protected characteristics: Race, religion, disability, sexual orientation, national origin, etc.¶

• Consumer behavior: Purchase history, product interests, consumption patterns.¶

• Biometric data, including voiceprints, faceprints, fingerprints.¶

• Online activity: Browsing and search history, website and app interaction.¶

• Geolocation information¶

• Sensory information: Audio, visual, thermal, and olfactory data.¶

• Professional and educational information.¶

2.2.4. Sensitive Data

An important subset of PII to consider in designing data privacy practices is so-called “sensitive data” which is subject to a higher standard of protection and requires additional privacy and security limitations to safeguard its collection, use and disclosure. For example, it may require an opt-in consent for data collection and processing. In various jurisdictions sensitive information may may now or in the near future (with regard to current bills, such as the American Privacy Rights Act) include the following:¶

• Government-issued identifiers.¶

• Physical or mental health information.¶

• Genetic data.¶

• Financial data.¶

• Biometric information, including faceprints and voiceprints used for identity recognition or verification.¶

• Precise geolocation data (information on a customer’s location within a 1,850-foot radius around the consumer, as defined by California Consumer Privacy Rights Act).¶

• Certain communications data – an individual's private communications, such as voicemails, emails, texts, direct messages or mail, or information identifying the parties to such communications, information contained in telephone bills, voice communications, and any information that pertains to the transmission of voice communications, including numbers called, numbers from which calls were placed, the time calls were made, call duration and location information of the parties to the call, unless the covered entity is an intended recipient of the communication. Communications with businesses may be awarded less protection.¶

• Log-in credentials – a customer’s account log-in, password, or credentials allowing access to an account.¶

• Citizenship and immigration status.¶

• Sexual behavior.¶

• Information revealing an individual's online activities over time and across websites or online services that do not share common branding or over time on any website or online service operated by a covered high-impact social media company.¶

• Information about minors (17 years of age or younger).¶

• Certain communications data – an individual's private communications, such as voicemails, emails, texts, direct messages or mail, or information identifying the parties to such communications, information contained in telephone bills, voice communications, and any information that pertains to the transmission of voice communications, including numbers called, numbers from which calls were placed, the time calls were made, call duration and location information of the parties to the call, unless the covered entity is an intended recipient of the communication. Communications with businesses may be awarded less protection.¶

• Online activity - information revealing an individual's online activities over time and across websites or online services that do not share common branding or over time on any website or online service operated by a covered high-impact social media company.¶

• Calendars, address book information, phone or text logs, photos, audio recordings, or videos intended for private use** typically stored on smartphones and tablets that reveal personal information about an individual's daily habits and social interactions.¶

• Transferred video viewing habit information - information revealing the extent or content of any individual's access, viewing or other use of any video programming, including by a provider of broadcast television service, cable service, satellite service or streaming media service, but only concerning the transfer of such information to a third party and excluding any such data used solely for transfers for independent video measurement.¶

2.2.5. What Data Isn’t Protected?

The distinction between personal and nonpersonal information hinges on identifiability, meaning that personal data is identifiable and thus protected by most privacy laws when it can be reasonably linked to a particular person (or even computer or device). This boundary can be ambiguous, with varying interpretations across jurisdictions. For instance, IP addresses are considered personal information by the EU and FTC, but not by U.S. federal agencies under the Privacy Act.¶ Moreover, sometimes, deidentified data can be reidentified, introducing challenges to personal data protection. When identifying elements are removed from data, it becomes nonpersonal information, generally falling outside the scope of privacy and data protection laws.¶

Some methods of transforming identifiable data into nonpersonal data are deidentification, anonymization, and aggregation. On the other hand, pseudonymization (replacing identifiable data with pseudonyms/unique codes) only temporarily removes identifiable data with the possibility of relatively easy reidentification. In many jurisdictions pseudonymous data falls within the scope of personal data when used in conjunction with additional information that reasonably links the data to an identified or identifiable individual.¶

Many jurisdictions remove publicly available information from the scope of protected PI.¶

Pseudonymized data, where individuals are represented by unique codes, is temporarily nonpersonal but can be reversed to reidentify individuals. This reversibility can be crucial in scenarios like medical trials. In many jurisdictions pseudonymous data falls within the scope of personal data when used in conjunction with additional information that reasonably links the data to an identified or identifiable individual.¶

Many jurisdictions remove publicly available information from the scope of protected PI.¶

2.2.6. Deidentification/Anonymization

Deidentification is the process of removing identifiable data from the dataset/document. It may take the form of information suppression (direct removal of identifying information), generalization (replacing a data element with a more general equivalent), or noise addition (slightly altering select data). Noise addition is the primary mechanism of differential privacy – a mathematical framework designed to ensure the privacy of individuals within a dataset while allowing for the extraction of useful statistical information by adding carefully calibrated noise to the data. This ensures that the inclusion or exclusion of any single individual's data does not significantly affect the outcome of the analysis and adds a level of personal data protection. Sometimes it is possible to reidentify the deidentified data using other available information. In this context, although it is often used interchangeably with the term “deidentification,” the term “anonymization” refers to the more comprehensive irreversible removal of identifiable data. Rigorous deidentification or anonymization techniques should be employed to ensure that reidentification is either impossible or extremely difficult.¶¶

2.2.7. Aggregation/Anonymization

In the data privacy context, data aggregation is a data analytics process whereby combined data from multiple sources or individuals containing PII information is summarized, effectively removing PII from the final product. It can be used to protect individuals' personal information while still allowing organizations to derive valuable insights. While aggregation can obscure individual identities, there are still privacy concerns that should be considered:¶¶

1. Re-identification risk: With enough granular data points, it may be possible to single out individuals even from aggregated datasets. Applying multiple specific filters to aggregate data could potentially identify a unique individual.¶

2. Inference attacks: Aggregated data can reveal patterns that allow inferences about individuals or small groups, even if direct identifiers are removed.¶

3. Unintended data exposure: As aggregated data is often shared between organizations, there's increased risk of unauthorized access or misuse.¶

Anonymization aims to remove or encrypt personal identifiers from datasets. However, true anonymization is challenging:¶

1. De-identification limitations: Simply removing obvious identifiers like names and addresses is often not sufficient to prevent re-identification. Indirect identifiers can still allow individuals to be singled out.¶

2. Data utility trade-offs: More thorough anonymization techniques tend to reduce the usefulness of the data for analysis.¶

3. Evolving re-identification techniques: As technology advances, previously anonymized data may become vulnerable to new re-identification methods.¶

To mitigate these risks, organizations should consider:¶

1. Implementing robust anonymization techniques beyond basic de-identification.¶

2. Carefully assessing the granularity and specificity of aggregated data released.¶

3. Combining anonymization with other privacy-enhancing technologies like differential privacy.¶

4. Conducting regular privacy impact assessments to evaluate potential risks.¶

5. Adhering to relevant privacy regulations and best practices for data handling.¶

While data aggregation and anonymization can enhance privacy protection, they should not be viewed as foolproof solutions. Organizations must remain vigilant and adopt a comprehensive approach to data privacy that considers the evolving nature of re-identification risks and the potential for unintended consequences when working with large datasets.¶

2.3.1. Key Privacy Principles

Data privacy and communications privacy are guided by similar principles, emphasizing consent, transparency, and data minimization while balancing privacy rights with societal interests. These areas aim to safeguard individuals' control over their personal information, whether stored or transmitted. Key principles include:¶

1. Consent: Must be freely given, specific, informed, unambiguous, revocable, and documented. Consent may not be valid in situations with power imbalances or required when processing is necessary to satisfy legal obligations or implement contracts. So-called “dark patterns,” which are practices of seeking consent that effectively obscure, subvert, or impair the consumer’s autonomy, decision-making or choice (for example, confusing user interfaces or hidden disclosures) are prohibited in many jurisdictions.¶

2. Notice/Transparency: Organizations must clearly disclose their data handling practices. Privacy notices should be concise, transparent, and easily understandable. Changes to privacy practices must be promptly communicated.¶

3. Purpose Limitation: Personal data should be collected for specific, explicit, and legitimate purposes, and it should not be used for purposes that are incompatible with those for which it was originally collected.¶

4. Data Minimization/Collection Limitation: Organizations should collect only the minimum amount of personal data necessary to achieve the stated purpose. Excessive or irrelevant data should not be collected.¶

5. Storage Limitation: Personal data should be retained only for as long as necessary to fulfill the purposes for which it was collected, consistent with legal limitations and requirements. Organizations should establish retention policies and securely dispose of data that is no longer needed.¶

6. Security: Appropriate technical, physical and administrative measures must be implemented to protect covered data from unauthorized access and other risks. This may include encryption, access controls, and regular security assessments.¶

7. Individual Rights: Individuals have certain rights regarding their personal data, including the right to access their data, the right to request corrections or deletions (”the right to be forgotten”), the right to object to certain uses of their data, and the right to data portability (the ability to transfer their data from one organization to another).¶

8. Data Integrity: Personal data should be accurate, complete, up-to-date, and trustworthy throughout its lifecycle. The core principles of data integrity include consistency across systems, authenticity verification, and non-repudiation mechanisms.¶¶

9. Accountability: Organizations are responsible for complying with data privacy laws and demonstrating compliance. This may involve conducting privacy impact assessments, appointing a data protection officer, and maintaining records of data processing activities.¶

10. Recordkeeping: Maintain accurate logs of consumers' profiles, data decisions, and data usage, including sales and marketing campaigns and instances of data disclosure to third parties.¶

While data privacy and communications privacy share many principles, there are some distinctions in their regulation. Communications privacy laws often focus more on real-time interception and communication confidentiality, while data privacy laws address a broader range of data handling practices.¶

As the digital landscape evolves, privacy laws must continually adapt to address emerging technologies and practices, ensuring the protection of personal information in our interconnected world.¶