Presentation Type
Oral Presentation
Start Date
5-8-2024 1:00 PM
End Date
5-8-2024 3:00 PM
Subjects
Database Management, Database Security
Advisor
Primal Pappachan
Student Level
Doctoral
Abstract
Ensuring privacy for databases is an ongoing struggle. While the majority of work has focused on using access control lists to protect sensitive data these methods are vulnerable to inference attacks. A set of algorithms, referred to as Tattle-Tale, was developed that could protect sensitive data from being inferred however its runtime performance wasn’t suitable for production code. This set of algorithms contained two main subsets, Full Deniability and K-Deniability. My research focused on improving the runtime or utility of the K-Deniability algorithms. I investigated the runtime of the K-Deniability algorithms to identify what was slowing the process down. Aside from investigating the cause of the slow performance I investigated ideas for altering the structure of the algorithms to reduce the number of computational steps while ensuring the same level of protection. I also investigated how approximate denial constraints and analyzing table attributes could achieve the same results as K-Deniability faster.
Creative Commons License or Rights Statement
This work is licensed under a Creative Commons Attribution 4.0 License.
Persistent Identifier
https://archives.pdx.edu/ds/psu/41919
Improving Tattle-Tale K-Deniability
Ensuring privacy for databases is an ongoing struggle. While the majority of work has focused on using access control lists to protect sensitive data these methods are vulnerable to inference attacks. A set of algorithms, referred to as Tattle-Tale, was developed that could protect sensitive data from being inferred however its runtime performance wasn’t suitable for production code. This set of algorithms contained two main subsets, Full Deniability and K-Deniability. My research focused on improving the runtime or utility of the K-Deniability algorithms. I investigated the runtime of the K-Deniability algorithms to identify what was slowing the process down. Aside from investigating the cause of the slow performance I investigated ideas for altering the structure of the algorithms to reduce the number of computational steps while ensuring the same level of protection. I also investigated how approximate denial constraints and analyzing table attributes could achieve the same results as K-Deniability faster.