Siemens Healthineers Ag

Siemens Healthcare Gmbh

Siemens Aktiengesellschaft

Biosense Webster, Inc.

Ute Rosenbaum

Steffen Fries

Santiago Reinhard Suppan

Jorge Ricardo Cuellar Jaramillo

Anthony Jay

Michael Kelm

Matityahu Amit

Marcus Schafheutle

Srikrishna Prasad

Thomas Gossler

Christian Spitzner

Srividya Tirunellai Rajamani

Manuel Sujith

Amatzia Tov

Shivani Jain

Milan Wutte

Markus Metz

Marco Krenkel

Felix Kupsch

Daniel Nottebrock

One or more example embodiments of the present invention relates to a method for transmission of medical datasets, including providing a medical dataset from an internal data memory, the medical dataset including data elements, each data element of the data elements having a data type, providing a security profile, the security profile including rules for a degree of a data anonymization of data elements of a respective data type, creating an anonymized medical dataset based on the provided medical dataset and the provided security profile, the data elements of the medical dataset are each anonymized based on the respective data type and the security profile, the anonymized medical dataset includes the anonymized data elements and transmitting the anonymized medical dataset to an external data memory.

Methods for transmission of medical datasets

A gateway and a method are provided for securely storing (and/or securely retrieving) medical data the method for storing comprising at least steps of:

Method for securely storing and retrieving medical data

A computer-implemented method for providing anonymized patient datasets, comprises: analyzing statistical population data to ascertain obfuscation parameters; and anonymizing patient datasets including quasi-identifiers as attributes by obfuscating the quasi-identifiers of the patient datasets based on the obfuscation parameters to generate the anonymized patient datasets. A system includes at least one processor and a memory, and is configured to provide the anonymized patient datasets.

Method and system for providing anonymized patient datasets

A computer-implemented method for assessing a person re-identification risk in an application domain is provided. In the application domain, for each of a plurality of persons a corresponding personal record is stored in a database. Each record comprises a set of attributes. Each attribute comprises a corresponding attribute name and a corresponding attribute value.

Structuring data for privacy risks assessments

A computer-implemented method is for dynamic data minimization of a data set for transfer of the minimized data set from a central instance to outside of the central instance, the data set including a second set of individual attributes. The method includes provisioning a whitelist including a first set of attributes being a subset of a second set of attributes. The minimized data set includes the first set of attributes. The method further includes determining an attribute list including a third set of attributes, the third set of attributes including at least the complement of the first set of attributes in relation to the second set of attributes. The method also includes provisioning the attribute list by the central instance for use outside of the central instance.

Method for dynamic data minimization of a data set by means of whitelisting

A method for transfer of a dataset includes provisioning or generating a user-side Diffie Hellman key pair, including a secret user key and a public user key; transferring the public user key to the server; provisioning or generating a server-side Diffie Hellman key pair, including secret server and public server keys; provisioning a dataset on the server; generating a server-side Diffie Hellman key using the secret server key and the public user key, and encrypting the dataset to generate an encrypted dataset, via a resulting server-side Diffie Hellman key generated on the server side; transferring the encrypted dataset to the cloud service; retrieving the public server key and the encrypted dataset from the cloud service; and generating a user-side Diffie Hellman key using the secret user key and the public server key retrieved, and decrypting the encrypted dataset on the user device using the user-side Diffie Hellman key.

Method and system for the secure transfer of a dataset

A client device for the secured activation of functions of a client, a server device for providing a password for the client device, and corresponding methods. The client device has a storage unit for storing a plurality of service keys, each service key defining at least one function of the client and being allocated to a password, a receiving unit for receiving a password from a server, and a processing unit for comparing the plurality of service keys with the received password, for selecting the service key to which the received password is allocated, and for activating at least one function of the client which is contained in the selected service key.

Client device and server device for the secured activation of functions of a client

Growing community of inventors

Kempten, Germany

Ute Rosenbaum