DF 2.0: An Automated, Privacy Preserving, and Efficient Digital Forensic Framework That Leverages Machine Learning for Evidence Prediction and Privacy Evaluation.
Robin VermaJayaprakash GovindarajSaheb ChhabraGaurav GuptaPublished in: J. Digit. Forensics Secur. Law (2019)
Keyphrases
- privacy preserving
- machine learning
- privacy preserving data mining
- privacy guarantees
- privacy preservation
- private information
- differential privacy
- multi party
- data privacy
- sensitive information
- privacy preserving data mining algorithms
- preserving privacy
- vertically partitioned data
- privacy concerns
- privacy protection
- privacy requirements
- data perturbation
- personal data
- provide efficient solutions
- privacy issues
- differentially private
- scalar product
- data transformation
- private data
- data mining
- privacy preserving association rule mining
- privacy sensitive
- secure multiparty computation
- data anonymization
- sensitive data
- location privacy
- third party
- naive bayesian classification
- user privacy
- horizontally partitioned data
- data publishing
- personal information
- information security
- record linkage
- database
- partitioned data
- horizontally partitioned
- data warehouse