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Protecting Data Privacy in Cloud Computing with Relational Semantic Hiding Databases (RSHDB)

Relational Semantic Hiding Databases (RSHDB) offer a novel solution for safeguarding data privacy and integrity in cloud environments. As organizations increasingly rely on cloud computing for IT management, the need for robust data protection mechanisms becomes paramount. This research by Jyh-haw Yeh at Boise State University explores RSHDB's ability to obscure sensitive information while maintaining usability. By leveraging RSHDB, businesses can benefit from cost-effective cloud services without compromising on data security.

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Protecting Data Privacy in Cloud Computing with Relational Semantic Hiding Databases (RSHDB)

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  1. Relational Semantic Hiding Databases (RSHDB)

    Protecting data privacy and integrity in clouds By Jyh-haw Yeh Computer Science Boise state University
  2. Cloud Computing Cloud computing paradigm provides a new concept of IT management. Business purchases IT services from Clouds Cost saving Unlimited computing power Charged by usage More secure? Better resource utilization, thus green computing
  3. Cloud Computing Cloud computing also has some known problems Trust issues Data privacy and integrity Non-transparency of data locations Liability issue
  4. Outsourcing Databases Database-as-a-service is an emerging service starts to appear in cloud industry. Clients has the flexibility to design an application as a database that is suitable for their business. Outsource the database to clouds. Clouds is able to execute queries over the database upon client’s requests. Clouds (may not be trusted) have the total control of data. Data privacy/integrity is a big concern .
  5. Encrypted Databases An extreme approach to protect data privacy: Encrypt the whole database and then outsource the encrypted database to clouds. This approach works if a practical fully homomorphic encryption (FHE) algorithm exists. FHE: arithmetic, rational comparisons can be applied directly to ciphers. No practical and efficient FHE exists.
  6. RSHDB RSHDB (relational semantic hiding databases) is a proposed database system that is able to hide semantics from DBAs. Suitable for business to outsource their business applications as a RSHDB instance to Clouds. Enable the DBAs or DBMS in clouds to operate on the RSHDB databases without knowing private business information.
  7. RSHDB: Idea of Hiding Semantics Idea of semantic hiding in RSHDB: An XYZ company has a PAYROLL database, in which a record in a table EMPLOYEE shows that John SmithSALARY is 63,000. An ?company has a ?database, in which a record in a table ?shows that ??is 63,000.
  8. RSHDB: Basic Operations Basic database operations: Arithmetic: addor multiply numeric data. Equality test: test the equality of two data items. Rational comparison: decide A> B or A < B. Substring matching: decide whether a string A is a substring in another string B Other database operations: sorting, searching, aggregate functions, set operations are extension/combination of basic operations.
  9. RSHDB: Data Types Data types: NC-type: Numeric with Comparison only. NCA-type: Numeric with both Comparison and Arithmetic. SC-type: String with Comparison only. SCS-type: String with both Comparison and Substring matching.
  10. RSHDB: Design Goal Partially encrypts the database so that the cloud is able to execute queries over encrypted data. Encrypt enough information (but not all) to hide semantics from data operators. Minimize the impacts for the DBMS, the SQL, the hosting clouds, and the clients.
  11. RSHDB: Encryption Strategy Use a secure deterministic encryption for all semantic telling information: database, table, attribute names. String type data is also semantic telling: always encrypted. SC-type: order-preserved encryption (less secure) SCS-type: char-by-char (less secure) order-preserved encryption. word-by-word order-preserved encryption.
  12. RSHDB: Encryption Strategy Numeric data itself reveal less semantics. NC-type: order-preserved encryption. Example: bdate data NCA-type: no practical homomorphic encryption available for this type of data. Leave the data in clear Homomorphic encoding (not too much help for security) Example: salary data
  13. Impacts The DBMS: Need to be semantic hiding aware The SQL: New data types for DDL The hosting clouds: More storage space for encrypted data. Install semantic hiding aware DBMS The clients: Install an query API: Perform encryption Convert SQL query to semantic hiding query Perform decryption Return the result to the clients
  14. Example Database
  15. Example Database
  16. Semantic Hiding Query (SHQ) The sensitive information or data is encrypted in SHQ. To make a query to a RSHDB, the SQL query must be a SHQ. Example Retrieve the name and salary of each employee in ‘Research’ department whose salary is more than $50,000, sort the report in ascending order of names.
  17. SHQ Example select EMPLOYEE.NAME, EMPLOYEE.SALARY from EMPLOYEE, DEPARTMENT where EMPLOYEE.DEPT_NO = DEPARTMENT.DEPT_NO AND DEPT_NAME = ‘Research’ AND EMPLOYEE.SALARY > 50000 asc EMPLOYEE.NAME; --------------------------------------------------------------------------- select T.A1, T.A6 from T, R where T.A3 = R.B2 AND R.B1 = Y21 AND T.A6 > 50000 asc T.A1;
  18. SHQ Result Query API decrypts the result and return to the clients
  19. Research Issues Storage requirement. Is order-preserved encryption secure enough? More secure encryption + order-preserved hashing? Guessing the semantics from the range and format of NCA-type data in clear. Adding noises? RSHDB’s DBMS has a weaker domain constraint enforcement. All encrypted data are in type of bit-string
  20. Research Issues Char-by-char versus word-by-word encryption for SCS-type data. Flexibility, security and space. Who should develop the query API? Performance downgrade: Implementation and simulation Real world databases and queries
  21. Future Work Designing algorithms for data integrity protection for outsourced database. Completeness Non-forgery Freshness Adding data integrity protection to RSHDB is challenging.
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