Differential privacy frameworks are systems or tools that help protect individual data when analysing or sharing large datasets. They add carefully designed random noise to data or results, so that no single person’s information can be identified, even if someone tries to extract it. These frameworks allow organisations to gain useful insights from data while…
Category: Prompt Engineering
Privacy-Preserving Inference
Privacy-preserving inference refers to methods that allow artificial intelligence models to make predictions or analyse data without accessing sensitive personal information in a way that could reveal it. These techniques ensure that the data used for inference remains confidential, even when processed by third-party services or remote servers. This is important for protecting user privacy…
Zero-Knowledge Machine Learning
Zero-Knowledge Machine Learning is a method that allows someone to prove they have trained a machine learning model or achieved a particular result without revealing the underlying data or the model itself. This approach uses cryptographic techniques called zero-knowledge proofs, which let one party convince another that a statement is true without sharing any of…
Secure Model Training
Secure model training is the process of developing machine learning models while protecting sensitive data and preventing security risks. It involves using special methods and tools to make sure private information is not exposed or misused during training. This helps organisations comply with data privacy laws and protect against threats such as data theft or…
Data Audit Framework
A Data Audit Framework is a structured set of guidelines and processes used to review and assess an organisation’s data assets. It helps identify what data exists, where it is stored, how it is used, and whether it meets quality and compliance standards. The framework is designed to ensure that data is accurate, secure, and…
Data Sharing Agreements
A data sharing agreement is a formal document that sets out how data will be shared between organisations or individuals. It outlines the rules, responsibilities, and expectations to make sure that data is handled securely and legally. These agreements help protect privacy, clarify what can be done with the data, and specify who is responsible…
Data Ethics Policy
A data ethics policy is a set of rules and guidelines that an organisation creates to ensure it handles data responsibly and fairly. It covers how data is collected, stored, used, and shared, focusing on respecting privacy, promoting transparency, and preventing harm. Such a policy helps organisations make decisions about data that are honest and…
Data Compliance Framework
A data compliance framework is a structured set of guidelines, processes, and controls that organisations use to ensure they handle data in line with relevant laws and regulations. It helps companies protect personal and sensitive information, manage risks, and avoid legal penalties. By following a data compliance framework, organisations can demonstrate accountability and build trust…
Information Governance
Information governance is the way organisations manage and control their information to ensure it is accurate, secure and used properly. It involves setting policies and procedures for collecting, storing, sharing and deleting information. Good information governance helps organisations meet legal requirements and protect sensitive data.
Data Retention Policies
Data retention policies are official rules that determine how long an organisation keeps different types of data and what happens to that data when it is no longer needed. These policies help manage data storage, protect privacy, and ensure legal or regulatory compliance. By setting clear guidelines, organisations can avoid keeping unnecessary information and reduce…