ENISA Guidelines

Comparison

Cross Reference of Pseudonymisation Technology Capabilities to Guidance by ENISA

 

 

Does your pseudonymisation technology satisfy new EU technical standards?  Check out the 2018 and 2019 Guidelines below from the EU Agency for Cybersecurity (ENISA) and compare the technology you are using against state-of-the-art techniques for pseudonym generation and supplementing Pseudonymisation with anonymisation techniques to reduce the risk of unauthorized re-identification.

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ENISA Guideline No 1 - Nov 2018: Recommendations on Shaping Technology According to GDPR Provisions - An Overview on Data Pseudonymisation

https://www.enisa.europa.eu/publications/recommendations-on-shaping-technology-according-to-gdpr-provisions
Section   Anonos
BigPrivacy
Vendor B Vendor C Vendor D
Personal identifiers replaced with pseudonyms 2.1.1      
Pseudonyms do not allow the direct derivation of personal identifiers 2.1.1      
Personal data can no longer be attributed to a specific data subject without the use of additional information 2.1.2      
Reversal of Pseudonymisation is non-trivial in absence of additional information 2.1.2      
Additional information kept separately using technical and organizational controls to limit access 2.1.2      
Pseudonyms applied to direct and indirect identifiers 2.1.2, 2.1.3      
Resistance against re-identification via singling out 2.1.2, 2.1.3      
Resistance against re-identification via linkage attacks 2.1.2, 2.1.3      
Resistance against re-identification via inference attacks 2.1.3, 2.2      
Anonymisation techniques used to further reduce the possibility of third parties inferring identity 2.2      
Single input results in a decoupled pair of outputs: pseudonymous data and additional information necessary to reidentify 2.3      
Identify of data subjects hidden in the context of a specific data processing operation 2.3      
Any recipient or third-party having access to pseudonymised data cannot trivially derive the original data set and identity of data subjects 2.3      
Support for unlinkability across different data processing domains 2.3      
Support for accuracy by retaining access to both pseudonymised output and additional information necessary to reidentify 2.3      
Does not use Hashing without key or salt to generate pseudonyms 3.2      
Offers keyed hash function (HMAC, SHA2/3, 256+ bit keys) to generate pseudonyms 3.3      
Offers tokens (randomly generated values) as pseudonyms 3.4      
ENISA Guideline No 2 - Nov 2019: Recommendations on Shaping Technology According to Data Protection and Privacy Provisions - Pseudonymisation Techniques and Best Practices

https://www.enisa.europa.eu/publications/pseudonymisation-techniques-and-best-practices
Section   Anonos
BigPrivacy
Vendor A Vendor B Vendor C
Enables a Risk-Based Approach accounting for required protection and utility/scalability Exec Summary      
Advances the State of the Art Exec Summary      
Complies with GDPR Definition of Pseudonymisation 2      
Utilizes one or more Pseudonymisation Functions 2      
Utilizes a Pseudonymisation Secret 2      
Has a Recovery Function for Pseudonymisation Functions 2      
Uses a Pseudonymisation Mapping Table 2      
Attack Resistance 4.3      
Pseudonymisation Secret Discovery Attack Resistant 4.3.1      
Re-Identification (Linkage) Attack Resistant 4.3.2      
Discrimination (Inference) Attack Resistant 4.3.3      
Brute Force Attack Resistant 4.4.1      
Dictionary Search Resistant 4.4.2      
Utility and Data Protection Maximization 4.5      
Pseudonymisation Techniques 5.1      
Does not make use of Counters 5.1.1      
Uses Cryptographic Random Number Generator 5.1.2      
Does not use Cryptographic Hash Function with or without salts, peppers 5.1.3      
Uses MAC - keyed hash (HMAC) 5.1.4      
Pseudonymisation Policies 5.2      
Supports Deterministic Pseudonymisation 5.2.1      
Supports Fully Randomized - RDDIDs - both row and field level 5.2.3      
Offers Recovery Function (Reversal of Pseudonymisation) 5.4      
Protects Pseudonymisation Secret 5.5      
Advanced Pseudonymisation Techniques 5.6      
Controlled Pseudonym Linkability 5.6      
K-Anonymity 5.6      
Aggregation/Generalization/Binning 5.6      
Rounding 5.6      
Masking 5.6      
Prefix/Suffix-Preserving Pseudonymisation 6.2.1      
Format Preserving Pseudonymisation 7.4      
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REFERENCES TO ENISA DO NOT INDICATE ANY RELATIONSHIP, SPONSORSHIP, OR ENDORSEMENT BY ENISA. ALL REFERENCES TO ENISA ARE INTENDED TO CONSTITUTE NOMINATIVE FAIR USE UNDER APPLICABLE TRADEMARK LAWS