Use Cases
Privasea has deep domain expertise in cryptography and privacy-enhancing solutions. Here are a few of the use cases where we believe our technologies and skills are used the best.
Healthcare Data Sharing
One of the benefits of e-health records is that they can be encrypted and securely shared with healthcare professionals who are involved in a patient's care, such as doctors, therapists, and trainers. This allows these professionals to access the necessary information to provide care to the patient without having to physically see them in person, which can be especially useful in situations where a patient is unable to come into the office for an in-person visit.
We use PRE technology to ensure patients can control their own personal health data. PRE contains both encryption and authorization functions. By encrypting e-health records, it is possible to reduce the risk of privacy leakage. When a consultation is needed, patients can authorize doctors/hospitals through the PRE network. This means that the information contained in the e-health records can only be accessed by those who have been granted permission to do so, helping to protect the privacy of the patient and their personal health information.
Data Analysis On Encrypted Dataset
Fully Homomorphic Encryption (FHE) is a useful method for efficiently analyzing large datasets and extracting meaningful insights from encrypted databases.
It can be particularly useful for analyzing trends and patterns in functional data, such as time series data or other data that varies over a continuous domain. We can use techniques such as batching in second-generation FHE to handle large-scale data operations, or functional bootstraping in third-generation FHE to deal with diverse non-linear operations.
It allows for statistical analysis methods for efficient measurement of Key Performance Indicators (KPIs) in a large dataset. The FDFB method involves the use of functional data analysis techniques to estimate the distribution of a functional variable, such as a KPI, across a population.
Safe Biometrics Algorithm
Privasea enables sharing biometric information securely. Usually an advanced recognition algorithm is used to validate if biometric information is a match or not. However, when the matching algorithm runs the biometric information is usually transferred in a readable format. Using FHE the biometric data remains encrypted so only the matching algorithm can read it and determine whether to grant access or not.
It’s safe even if the server got hacked or your edge device get stolen!
Find Joint Clients For Banks
PSI is a cryptographic protocol that allows two parties to compute the intersection of their datasets without revealing any other information (i.e. the information except for the overlaps).
This is useful in cases where the two parties have sensitive data that they want to compare or combine, but they do not want to reveal their database to each other.Private financial information is of a sensitive nature.
Yet, banks and financial institutions occasionally need to cooperate with each other to find common denominators among a customer. For instance, to detect fraudulent or criminal transactions and behaviour. PSI ensures this can be done without compromising personal data. Additionally, banks and financial institutions can cooperate with each other to draw more value out of their data. Advanced analytics is hence powered by the PSI.
