Top 5 PII Data Masking Techniques

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Top 5 PII Data Masking Techniques Pros and Cons

• Personally Identifiable Information (PII) is
  sensitive data that must be protected from
  unauthorized access. Data masking is an essential
  technique used to safeguard PII by obscuring or
  modifying the original data while maintaining its
  usability. This document outlines the top five
  PII data masking techniques, their benefits, and
  potential drawbacks.
• Substitution
• Substitution replaces PII data masking with
  fictitious but realistic data. For example, names
  and addresses in a database can be replaced with
  randomly generated values.
• Pros
• Maintains data format and consistency.
• Preserves referential integrity in databases.
• Effective for non-reversible masking.
• Cons
• Can be complex to implement properly.
• May require external datasets to generate
  realistic values.

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• Shuffling
• Shuffling rearranges PII data within a dataset,
  ensuring that the data remains realistic but is
  no longer associated with the original subject.
• Pros
• Maintains data distribution and relationships.
• Useful for anonymizing data while retaining
  statistical value.
• Cons
• If not properly randomized, patterns may emerge.
• Not suitable for highly structured datasets where
  relationships must be preserved.
• Encryption
• Encryption transforms PII into an unreadable
  format using cryptographic algorithms, which can
  only be reversed with a decryption key.
• Pros
• Strongest protection against unauthorized access.
• Ensures compliance with security regulations.

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• Not sufficient for strong security measures.
• Can be reversible if patterns are predictable.
• Tokenization
• Tokenization replaces PII with a unique
  identifier (token) that maps to the original data
  stored securely in a separate system.
• Pros
• Enhances security by storing tokens instead of
  actual data.
• Commonly used in payment processing and
  compliance-sensitive industries.
• Cons
• Requires a secure token vault for mapping.
• Implementation complexity increases with large
  datasets.
• Each data masking technique has its strengths and
  weaknesses. The choice of technique depends on
  the level of security required, regulatory
  compliance, and the use case.
• Organizations often use a combination of these
  techniques to ensure comprehensive PII
  protection.
• By carefully selecting and implementing the right
  data masking strategy, businesses can mitigate
  risks associated with data breaches and enhance
  data privacy without compromising usability.