Data must be protected at all stage of its lifecycle, from its generation until its disposal.
- Generation: data creation (from another system or customer)
- Retention: keep the data for a certain length of time
- Disposition: orderly, planned process of handling data that may still have use
- Disposal: destruction, removal, or transfer to another organization (archive etc)
Protection requirements for the data may change over its lifecycle: not everything needs to be protected at all time.
Data Collection Legal Issues
Country dependent. There may be legal requirements such as:
Allowed uses of data (only collecting data that we need)
- Third-parties (terms)
- Data accuracy: responsibility to keep data accurate and up to date as much as possible
Data retention: how long we keep the data, and why, and how to keep it safe
- Right to be forgotten
Data Misuse and Abuse Risks
What are the ways that data could be misused?
- Improper use by an employee
- Hacker stealing it
A list of threats and risks must be created.
- Data aggregation: data that were not sensible or personal in isolation becomes, in aggregation, sensible
- Data inference: learning from watching some piece of data (marketing learns about people’s behaviors through when/how/what people buy, for example)
- Improper changes: data can’t be trusted anymore because we are being provided wrong information (could be a liability in a financial report, for example)
- (Pseudo-)Randomization: substitutes value for another so that it’s not easily identifiable (obfuscation)
- Tokenization: identification numbers associated with a user that few people know the association of
- Masking: data masked during input (password) or output (credit card numbers partially masked)
- Encryption: for safe storage and transmission of data