Data Protection

Data portability refers to the right granted to individuals to access and transfer their personal data between services, as enshrined in modern data protection laws such as the GDPR. Advocates argue that data portability enhances consumer choice and fosters competition by making it easier to switch providers, thus reducing service provider lock-in. Just as number portability empowered consumers to switch mobile providers without losing their phone number, data portability allows users to move their digital history, preferences, and identity between digital services. However these benefits come with significant risks. Poorly implemented systems and weak controls could allow fraudsters to impersonate users and extract sensitive data. Cybercriminals may spoof new extraction requests or intercept poorly secured transfers, turning a consumer-friendly right into a new attack vector. ...

Data classification is the process of organising data into categories based on sensitivity and criticality to the organization. This process is crucial for effective risk management, as it enables organisations to identify and prioritise the protection of their most valuable and sensitive information assets. By understanding the different levels of risk associated between data types, organisations can implement security controls and procedures to mitigate threats, comply with regulatory requirements, and minimise the impact of data breaches. ...

As organisations increasingly operate in digital environments, they are creating and handling ever-increasing volumes of sensitive data, including customer information, employee records and confidential business data. This will also include personal data, a special category that carries additional legal protections and obligations. A robust data classification and labelling process is therefore essential for managing information security and meeting these legal and regulatory obligations. What is Data Classification? Data classification involves categorising data based on its sensitivity and potential impact if compromised. Examples include: ...

Data loss prevention (DLP) helps organisations protect sensitive information from loss, misuse, or unauthorised access. DLP is a strategy and set of tools designed to prevent sensitive information from leaving an organisation’s control or being accessed by unauthorised users. It works by identifying, monitoring, and protecting data in three states: when it’s being used, when it’s being transferred (such as over a network or email), and when it’s stored on devices or servers. DLP tools use content inspection and security analysis to achieve this. ...

Data protection refers to the practices, safeguards, and rules put in place to protect personal information and ensure that individuals’ privacy rights are respected. Data protection procedures in an organisation will involve the secure handling of data to prevent unauthorised access, disclosure, alteration, or destruction. Effective data protection measures are essential for maintaining trust, and for compliance with legal and regulatory requirements. Related pages Data privacy Data classification Data disposal Worldwide data transfer Data controller Data processor Data subject rights Data breach