Secure key storage refers to the safe keeping of cryptographic keys so that only authorised users or systems can access them. These keys are often used to encrypt or decrypt sensitive information, so protecting them is crucial for maintaining security. Methods for secure key storage can include hardware devices, dedicated software, or secure parts of…
Quantum-resistant signatures are digital signature methods designed to remain secure even if someone has access to a powerful quantum computer. These signatures use mathematical problems that are believed to be hard for both classical and quantum computers to solve, making them more secure against future threats. They are being developed to protect sensitive data and…
Decentralised identity verification is a way for people to prove who they are online without relying on a single central authority like a government or a big company. Instead, identity information is stored and managed using secure digital technologies, often involving blockchain or similar distributed systems. This approach gives individuals more control over their personal…
Private data querying is a way to search or analyse sensitive data without exposing the actual information to others. It uses specialised techniques to keep the content of the data hidden, even from the person or system performing the query. This helps maintain privacy and security while still allowing useful insights to be gained from…
Secure data aggregation is a process that combines data from multiple sources while protecting the privacy and security of the individual data points. It ensures that sensitive information is not exposed during collection or processing. Methods often include encryption or anonymisation to prevent unauthorised access or data leaks.
Privacy-preserving feature engineering refers to methods for creating or transforming data features for machine learning while protecting sensitive information. It ensures that personal or confidential data is not exposed or misused during analysis. Techniques can include data anonymisation, encryption, or using synthetic data so that the original private details are kept secure.
Encrypted model inference is a method that allows machine learning models to make predictions on data without ever seeing the raw, unencrypted information. This is achieved by using special cryptographic techniques so that the data remains secure and private throughout the process. The model processes encrypted data and produces encrypted results, which can then be…
Federated Differential Privacy is a method that combines federated learning and differential privacy to protect individual data during collaborative machine learning. In federated learning, many users train a shared model without sending their raw data to a central server. Differential privacy adds mathematical noise to the updates or results, making it very hard to identify…
Group signatures are a type of digital signature that allows any member of a group to sign a message on behalf of the group without revealing which individual signed it. The signature can be verified as valid for the group, but the signer’s identity remains hidden from the public. However, a designated authority can reveal…
Blind signatures are a type of digital signature where the content of a message is hidden from the person signing it. This means someone can sign a message without knowing what it says. Blind signatures are often used to keep information private while still allowing for verification and authentication.