Topositus will make it possible to combine cancer register data together while still maintaining privacy and protecting patient health data. This is the first proof of concept project.
Read about Opdan's research and innovation project
Data which includes various types of information are continuously being collected throughout the society and proper data management is necessary to ensure that no data leakage or theft occurs. This is particularly critical when managing personal data such as patient health data which can be at risk of being misused by nefarious parties.
Nikolai Opdan and his team realised that theoretical mathematical methods could be applied by industry and help address this risk and protect data from being leaked.
– We have implemented a new method called homomorphic encryption which allows for processing encrypted data. Information that is embedded within the data is hidden and unusable when encrypted. Access to this information requires one to process this data through decryption to access this information, which makes it impossible to steal, says Opdan.
Centralised data processing
Opdan further clarifies that their method will allow data to be processed while in its encrypted form, making the hidden information inaccessible and valueless if stolen. This could also allow centralised data processing in the future.
– This method allows data to be stored in its encrypted form at all times, even through the processing process. Data is a very valuable asset for a company and with this method, no one will be able to steal it even if they wanted to. By processing data that is encrypted, you could also process data from other sources and centralise a lot of data processing and allow for cloud-processed data in a more secure way, says Opdan.
According to Opdan, processing of a lot of data in Norway is costly as it must be done within the infrastructure of the country and prohibited to be sent abroad because of its sensitivity such as personal health information. Their method will allow for this centralising of processing and effectively reduce the cost and ability to use more than one data center thereby optimizing the use of the infrastructure.
First proof of concept project in cancer project
Opdan and his team are collaborating with Oslo University Hospital to research a cancer data set to gain more understanding on different cancers using machine learning. However, to be able to do this, more cancer register data is needed which is not possible to be easily acquired and combined today.