Privacy¶
Privacy¶
- Determine when/how/what information is communicated to others
- Aspects
- Right to be let alone
- Self-identity / personal growth
- Protection intimate relationships
- Data privacy: Detect/control data inference
- DB Security: Control access / protect content
- Challenge: Utilize data while protect individuals privacy
- Idea: Anonymize all attributes that could be used for de-anonymization
Privacy: Risks + Protection¶
- Problem: Growing availability of information
- Who is allowed to see what?
- Goal: Anonymize data
- Protection technique: Formal models
- Specify privacy model
- Derive conditions
- Design algorithms satisfying privacy conditions
- Example: K-anonymity, L-diversity, L-closeness, (c,k)-safety
k-Anonymity¶
- Protection model, ensure anonymity in relational data
- Idea: Generalize, modify, distort identifiers -> no unique identification
- Definition: R(A1, … An), Quasi-identifiers
- R satisfies k-Anonymity <=> each sequence R[QI] at least k times
- Meaning: Matching cannot reduce to fewer than k individuals
- Large k => higher privacy
- Find quasi-identifiers: Hard / impossible
- Algorithm (NP-hard)
- Delete cell values / tuples (generalization causes information loss)
- Generalize cell values (quasi-identifiers)
Attacks¶
- Unsorted matching attack:
- Data often sorted, sort data
- Complementary release attack:
- Two data sets, match with problem attribute
- Homogeneity attack:
- Problem attribute for class is same (little diversity)
- Background knowledge attack:
- Very complex attack (knowledge not known)
L-Diversity¶
- Prevent homogeneity / background knowledge attack
- Sensitive attributes in a class must be L different values
- No perfect anonymization (Binary attribute hard to achieve, distribution not considered)
Curse of Dimensionality¶
- Data many attributes
- Data sparse
- K nearest neighbors are far away
- Result: Loss of information
Sparse data: Deanonymization¶
- no quasi-identifiers
- Netflix: K-Anonymization generalization high data loss
- Idea:
- Calculate similarity Netflix and IMDB
- Most similar record is a match
- No record: Candidates also reveal information
- Information:
- political orientation
- Religious views
Social Networks¶
Social Networks: Advanced anonymization¶