![Cont..
• The prototype is used as a research tool for studying
principles and mechanisms of the encryption-based
multilevel model and other multilevel relational database
security models (SeaView, Jajodia–Sandhu, Smith–
Winslett , multilevel relational [MLR], and belief-
consistent models) .](https://image.slidesharecdn.com/chapter5-151224114707/85/Encryption-Based-Multilevel-Model-for-DBMS-5-320.jpg)
![The UPLEVEL Statement
• The UPLEVEL statement executed by a user
with security class level L has the following
general form:
UPLEVEL R GET [A1,A2,...,A n] FROM
[C1,C2,...,C n] WHERE P](https://image.slidesharecdn.com/chapter5-151224114707/85/Encryption-Based-Multilevel-Model-for-DBMS-16-320.jpg)
Encryption-Based Multilevel Model for DBMS
- 1. Chapter 5 Encryption-Based Multilevel Model For DBMS Presented by: Ala Eltayeb
- 2. Outlines Introduction Encryption-Based Multilevel Database Model Manipulation Performance Study Analysis of Experimental Results Summary
- 3. 1. Introduction • Type of encryption in database? Column &row • Encrypt each tuple (row) in the relation (table) with an encryption key that depends on the security level of the tuple (tuple classification). Encryption-Based Multi-level Model Multilevel Relation Model Encryption System
- 4. The Encryption-based multilevel security model Characterizes: I.Utilizing an encryption system as an additional security layer over the multilevel security layer for the relational database. II. Reducing the multilevel database size. III. Improving the response time of data retrieval from the multilevel database.
- 5. Cont.. • The prototype is used as a research tool for studying principles and mechanisms of the encryption-based multilevel model and other multilevel relational database security models (SeaView, Jajodia–Sandhu, Smith– Winslett , multilevel relational [MLR], and belief- consistent models) .
- 6. Why used prototype? 1. To determine the relative performance of the multilevel relational database security models. 2. The performance cost for applying the encryption system in multilevel relational database security.
- 7. 2. Encryption-Based Multilevel Database Model • A symmetric key:-for each unique security level. • The user can use the keys : Security level (key) <= Security level (user) • The classification attributes are removed. • Each attribute is encrypted by using: encryption key that corresponds to the tuple security classification level (tuple level encryption).
- 8. Example :Data store in MLR and encryption-based models
- 9. Several DBMS Support Encryption Algorithms 1. DB2(IBM) - SQL Functions - Stored Procedures 2. ORACLE - Transparent Data Encryption (TDE)
- 11. Manipulation • The data manipulation statements in the encryption-based multilevel database model are : INSERT DELETE SELECT UPDATE UPLEVEL
- 12. The INSERT Statement I = attribute
- 13. The DELETE Statement DELETE FROM R WHERE P I = tuple
- 14. The SELECT Statement I = tuple
- 15. The UPDATE Statement I = tuple
- 16. The UPLEVEL Statement • The UPLEVEL statement executed by a user with security class level L has the following general form: UPLEVEL R GET [A1,A2,...,A n] FROM [C1,C2,...,C n] WHERE P
- 17. UPLEVEL Example user with S security level has used the UPLEVEL command to indicate that he believes the first tuple and insert the second tuple with S security level
- 18. Cont… UPLEVEL SOD GET OBJ FROM M1,DEST FROM M2 WHERE SHIP =“Enterprise”
- 19. 4. Performance Study • Study performance of multilevel relational database security models such as SeaView, Jajodia–Sandhu, Smith– Winslett, MLR, and belief-consistent models and the encryption-based multilevel database. • The impact of changing the size and schema of the relational database on the performance of these models
- 20. Machine that is used for the implementation consists of : • CPU speed of 2.2 GHz • physical RAM size of 3 GB • hard disk size of 320 GB • The software used in the implementation is a Microsoft SQL server 2008 R2 and the experiments’ measurements were captured at the machine using a monitoring tool provided by the Microsoft SQL server.
- 21. The impact of changing the number of tuples on the performance of the encryption algorithms in a multilevel database in the selection query
- 22. Cont.. The experiments investigate the impact of changing : 1) The number of tuples 2) The number of attributes 3) The number of security levels These experiments use the CPU response time (in minutes). Assume that the base value for the number of tuples is 1,000,000, the base number of attributes is three, and the base number of security levels is four.
- 23. ER diagram for the timesheet system
- 24. SELECT Query Select * from Employee where department = ‘Sales’ Supporting encryption in the encryption-based multilevel database model improves the performance of the multilevel relational database because database size is decreased due to removing the extra attributes used for the class levels.
- 25. Impact of changing the number of tuples in the selection query Number of attributes = 3 Number of security levels = 4
- 26. Impact of changing the number of attributes in the selection query Number of tuples = million Number of security levels = 4
- 27. Impact of changing the number of security levels in the selection query Number of attributes = 3 Number of tuples = million
- 28. JOIN Query • Select * from Employee join Departure on Employee.Name = Departure.Name where Employee. department = ‘Sales’
- 29. Impact of changing the number of tuples in the join query Number of attributes = 3 Number of security levels = 4
- 30. Impact of changing the number of attributes in the join query Number of tuples = million Number of security levels = 4
- 31. Impact of varying the number of security levels in the join query Number of attributes = 3 Number of tuples = million
- 32. Cont… Supporting encryption in the encryption-based multilevel database model improves the performance of the multilevel relational database because database size is decreased due to removing the extra attributes used for the class levels.
- 33. Impact of varying the number of tuples in an update query Number of attributes = 3 Number of security levels = 4
- 34. Cont.. Supporting encryption in the encryption-based multilevel database model decreases the performance of a multilevel database because, during the execution of the update statement. The encryption and decryption mechanisms will be included together in the update procedure.
- 35. Hierarchical of Model Performance Smith-Winslett MLR Blief-Consistent Jajodia-Sandhu SeaView High performance
- 36. Analysis of Experimental Results • The performance of the Smith–Winslett model is the best. • The MLR model offers less performance than the Smith– Winslett model because it supports the security classification at the level of each single attribute. • The belief-consistent model has less performance than the MLR model because it supports a combination of the security classification levels for each single attribute to enable the user to assert his beliefs of lower level users’ information.
- 37. Cont… • The Jajodia–Sandhu model has bad performance because of the impact of union operation between single-level relations in the recovery algorithm. • The SeaView model has very bad performance because of the impact of the JOIN operation between vertical single-level relations and union operation between horizontal single-level relations in the recovery algorithm.
- 38. Comparison between MLR and Encryption –Based model The encryption- based multilevel database model has performance better than the performance of the MLR model in retrieving data from the multilevel database. The performance of the encryption-based multilevel database model is less than the performance of the MLR model in updating data because the overhead of supporting the encryption algorithm in the update query is executed.
- 40. Summary The encryption-based multilevel model overview. Comparison the performance of MLR models and encryption- based model. Supporting encryption in multilevel relational database: 1. Improve performance of the retrieving data in the SELECT and JOIN queries. 2.Bad performance because of the extra CPU processing results.