Deep Natural Anonymization
Certification: 03/2022
Important: The certificate with the „Cert. No.EP-P-8NSBJG according to version v201701 has expired on 31.03.2024“. Brighter AI is currently in the certification process according to Article 42 GDPR for „processors“, the certification process should be completed by Q3 2024.
DNAT (Deep Natural Anonymization) is a redaction feature for images and videos. It automatically detects personal identifiers (faces and license plates) and generates synthetic replacements reflecting the original attributes. Therefore, DNAT facilitates protecting identities while keeping necessary information for analytics or machine learning.
Deep Natural Anonymization Technology (DNAT)
(a feature of the software brighter Redact Enterprise v3)
Qualification: IT product
EP-P-8NSBJG
22/03/2022 – 31/03/2024
Certification 2022: DNAT Short Public Report [PDF]
brighter AI Technologies GmbH
Litfaß-Platz 2
10178 Berlin
Germany
DNAT is solely used for detecting faces and license plates in images and videos as well as generating synthetic replacements so that industry-leading recognition algorithms are not able to identify the original face or license plate anymore. In cases where realistic human face attributes and license plate layouts are necessary for analytical or software development purposes and machine learning, the quality of the images remains, but the original faces and license plates are not part of the redacted footage anymore. Hereby, DNAT clearly facilitates the anonymization of images and videos.
For the redaction of license plates DNAT provides the option for the customer to use individual and customized output layer. This feature ensures that a synthetic license plate will not exist in reality by accident.
Depending on the redacted images and videos, the use of DNAT may not always result in a complete anonymization of the respective footage. E.g., if a person wears a name tag, it may be possible to identify them even if their image is detected and redacted by the use of DNAT.
Customers should make use of the feature ensuring that a synthetic license plate will not exist in reality by accident (cf. above at BEST).
Brighter Redact Enterprise is a software for the redaction of images and videos, which is to be hosted on customer’s premise. The software provides for several redaction features, including precision blur, selective redaction and deep natural anonymization (DNAT). Only the latter feature is covered by the current certification. DNAT automatically detects faces and license plates in footage and generates synthetic replacements reflecting the original attributes. Therefore, it facilitates protecting identities while keeping necessary information for analytics or machine learning.
Initial Cert 202203
Target of Evaluation (ToE) is DNAT, a feature of the software brighter Redact Enterprise v3. The ToE includes the following components:
The ToE does not include the following:
Prof. Dr. Ralf B. Abel
Oktaviostr. 129
22043 Hamburg
Germany
Marc Neumann
IBS data protection services and consulting GmbH
Zirkusweg 1
Deep Natural Anonymization
Certification: 03/2022
DNAT (Deep Natural Anonymization) is a redaction feature for images and videos. It automatically detects personal identifiers (faces and license plates) and generates synthetic replacements reflecting the original attributes. Therefore, DNAT facilitates protecting identities while keeping necessary information for analytics or machine learning.
Deep Natural Anonymization Technology (DNAT)
(a feature of the software brighter Redact Enterprise v3)
Qualification: IT product
EP-P-8NSBJG
22/03/2022 – 31/03/2024
Certification 2022: DNAT Short Public Report [PDF]
brighter AI Technologies GmbH
Litfaß-Platz 2
10178 Berlin
Germany
DNAT is solely used for detecting faces and license plates in images and videos as well as generating synthetic replacements so that industry-leading recognition algorithms are not able to identify the original face or license plate anymore. In cases where realistic human face attributes and license plate layouts are necessary for analytical or software development purposes and machine learning, the quality of the images remains, but the original faces and license plates are not part of the redacted footage anymore. Hereby, DNAT clearly facilitates the anonymization of images and videos.
For the redaction of license plates DNAT provides the option for the customer to use individual and customized output layer. This feature ensures that a synthetic license plate will not exist in reality by accident.
Depending on the redacted images and videos, the use of DNAT may not always result in a complete anonymization of the respective footage. E.g., if a person wears a name tag, it may be possible to identify them even if their image is detected and redacted by the use of DNAT.
Customers should make use of the feature ensuring that a synthetic license plate will not exist in reality by accident (cf. above at BEST).
Brighter Redact Enterprise is a software for the redaction of images and videos, which is to be hosted on customer’s premise. The software provides for several redaction features, including precision blur, selective redaction and deep natural anonymization (DNAT). Only the latter feature is covered by the current certification. DNAT automatically detects faces and license plates in footage and generates synthetic replacements reflecting the original attributes. Therefore, it facilitates protecting identities while keeping necessary information for analytics or machine learning.
Initial Cert 202203
Target of Evaluation (ToE) is DNAT, a feature of the software brighter Redact Enterprise v3. The ToE includes the following components:
The ToE does not include the following:
Prof. Dr. Ralf B. Abel
Oktaviostr. 129
22043 Hamburg
Germany
Marc Neumann
IBS data protection services and consulting GmbH
Zirkusweg 1
Die deutschlandweit erste Zertifizierung für Auftragsverarbeiter nach Artikel 42 DSGVO.
Die deutschlandweit erste Zertifizierung für Auftragsverarbeiter nach Artikel 42 DSGVO.
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© All Rights Reserved.