Data fences are security measures or rules that restrict how and where data can move or be accessed within a system. They help ensure that sensitive information stays within approved boundaries, such as specific departments, locations, or cloud regions. Data fences are often used to meet legal, regulatory, or business requirements for data privacy and…
Context leakage occurs when information from one part of a system or conversation unintentionally influences another, often leading to confusion, privacy issues, or errors. This typically happens when data meant to remain confidential or isolated is mistakenly shared or accessed in situations where it should not be. In computing and artificial intelligence, context leakage can…
Decentralised trust frameworks are systems that allow people, organisations or devices to trust each other and share information without needing a single central authority to verify or control the process. These frameworks use technologies like cryptography and distributed ledgers to make sure that trust is built up through a network of participants, rather than relying…
Secure data management is the practice of keeping information safe, organised, and accessible only to those who are authorised. It involves using tools and processes to protect data from loss, theft, or unauthorised access. The goal is to maintain privacy, accuracy, and availability of data while preventing misuse or breaches.
Data compliance automation refers to the use of software tools and systems to automatically ensure that an organisation’s data handling practices follow relevant regulations and policies. This might include monitoring, reporting, and managing data according to rules like GDPR or HIPAA. By automating these processes, companies reduce manual work, lower the risk of human error,…
Data compliance metrics are measurements used to track how well an organisation follows rules and regulations for handling data. These metrics help ensure that sensitive information is collected, stored, and processed in ways that meet legal and industry standards. Organisations use these metrics to identify gaps, reduce risks, and prove their data practices are compliant…
Secure data management refers to the processes and tools used to protect information from unauthorised access, loss, or corruption. It involves organising, storing, and handling data so that only permitted users can access or change it. This includes using passwords, encryption, backups, and strict access controls to keep information safe and reliable.
Data compliance frameworks are organised sets of rules, standards and guidelines that help organisations manage and protect personal and sensitive data. They are designed to ensure that companies follow laws and regulations about data privacy and security. Businesses use these frameworks to set clear policies, processes and controls for handling data responsibly and legally.
Secure data collaboration refers to methods and tools that allow people or organisations to work together on shared data without compromising its privacy or integrity. It ensures that only authorised users can access or edit sensitive information, and that the data remains protected during the entire collaboration process. This often involves encryption, access controls, and…
Data compliance automation refers to the use of software tools and technology to help organisations automatically follow laws and policies about how data is stored, used, and protected. Instead of relying on people to manually check that rules are being followed, automated systems monitor, report, and sometimes fix issues in real time. This helps companies…