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Introduction Database Security Overview

Introduction Database Security Overview. Readings. This lecture: Textbook: Chapter 5.2 Lecture materials from CSCE 522, Nov. 3, Lecture 20 at http://www.cse.sc.edu/~farkas/csce522-2010/lectures.htm For next class: Textbook: Chapter 10.1, 10.2. Database Security Requirements.

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Introduction Database Security Overview

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  1. Introduction Database Security Overview

  2. Readings • This lecture: • Textbook: Chapter 5.2 • Lecture materials from CSCE 522, Nov. 3, Lecture 20 at http://www.cse.sc.edu/~farkas/csce522-2010/lectures.htm • For next class: • Textbook: Chapter 10.1, 10.2 CSCE 824

  3. Database Security Requirements • Physical database integrity • Logical database integrity • Element integrity • Auditability • Access control • User authentication • Availability CSCE 824

  4. Sensitive data • Inherently sensitive • From a sensitive source • Declared sensitive • Part of a sensitive attribute or record • In relation to previously disclosed information CSCE 824

  5. Types of disclosures • Exact data • Range of data • Negative results • Existence • Probable values CSCE 824

  6. Access control • Operating system • Database Management System • Granularity! CSCE 824

  7. Granularity • Database • Relation • Record • Attribute • Element Advantages vs. disadvantages of supporting different granularity levels CSCE 824

  8. Granularity • Database • Relation • Record • Attribute • Element Advantages vs. disadvantages of supporting different granularity levels CSCE 824

  9. Relation-Level Granularity (Works)= Secret CSCE 824

  10. Tuple-level Granularity Works CSCE 824

  11. Attribute-Level Granularity Works CSCE 824

  12. Cell-Level Granularity Works CSCE 824

  13. Access Control Mechanisms • Security through Views • Stored Procedures • Grant and Revoke • Query modification CSCE 824

  14. Security Through Views • Assign rights to access predefined views CREATE VIEW Outstanding-Student AS SELECT NAME, COURSE, GRADE FROM Student WHERE GRADE > B Problem: Difficult to maintain updates. CSCE 824

  15. Security Through Views Studentrelation CSCE 824

  16. Security Through Views CREATE VIEW Outstanding-Student AS SELECT NAME, COURSE, GRADE FROM Student WHERE GRADE > B Outstanding-Student CSCE 824

  17. Security Through Views CREATE VIEW Fall-Student AS SELECT NAME, COURSE FROM Student WHERE SEMESTER=“Fall 2000” Fall-Student CSCE 824

  18. Stored Procedures • Assign rights to execute compiled programs • GRANT RUN ON <program> TO <user> Problem: Programs may access resources for which the user who runs the program does not have permission. CSCE 824

  19. Grant and Revoke GRANT <privilege> ON <relation> To <user> [WITH GRANT OPTION] ------------------------------------------------------------------------------------------------------------------------------------ • GRANT SELECT * ON Student TO Matthews • GRANT SELECT *, UPDATE(GRADE) ON Student TO FARKAS • GRANT SELECT(NAME) ON Student TO Brown GRANT command applies to base relations as well as views CSCE 824

  20. Grant and Revoke REVOKE <privileges> [ON <relation>] FROM <user> ------------------------------------------------------------------------------------------------------------------------- • REVOKE SELECT* ON Student FROM Blue • REVOKE UPDATE ON Student FROM Black • REVOKE SELECT(NAME) ON Student FROM Brown CSCE 824

  21. Query Modification • GRANT SELECT(NAME) ON Student TO Blue WHERE COURSE=“CSCE 590” • Blue’s query: SELECT * FROM Student • Modified query: SELECT NAME FROM Student WHERE COURSE=“CSCE 580” CSCE 824

  22. Indirect Information Flow Channels • Covert channels • Inference channels CSCE 824

  23. Communication Channels • Overt Channel: designed into a system and documented in the user's manual • Covert Channel: not documented. Covert channels may be deliberately inserted into a system, but most such channels are accidents of the system design. CSCE 824

  24. Covert Channel • Timing Channel: based on system times • Storage channels: not time related communication • Can be turned into each other CSCE 824

  25. Inference Channels Non-sensitive information Sensitive Information + Meta-data = CSCE 824

  26. Inference Channels • Statistical Database Inferences • General Purpose Database Inferences CSCE 824

  27. Statistical Databases • Goal: provide aggregate information about groups of individuals • E.g., average grade point of students • Security risk: specific information about a particular individual • E.g., grade point of student John Smith • Meta-data: • Working knowledge about the attributes • Supplementary knowledge (not stored in database) CSCE 824

  28. Types of Statistics • Macro-statistics: collections of related statistics presented in 2-dimensional tables • Micro-statistics: Individual data records used for statistics after identifying information is removed CSCE 824

  29. Statistical Compromise • Exact compromise: find exact value of an attribute of an individual (e.g., John Smith’s GPA is 3.8) • Partial compromise: find an estimate of an attribute value corresponding to an individual (e.g., John Smith’s GPA is between 3.5 and 4.0) CSCE 824

  30. Methods of Attacks and Protection • Small/Large Query Set Attack • C: characteristic formula that identifies groups of individuals If C identifies a single individual I, e.g., count(C) = 1 • Find out existence of property • If count(C and D)=1 means I has property D • If count(C and D)=0 means I does not have D OR • Find value of property • Sum(C, D), gives value of D CSCE 824

  31. Small/Large Query Set Attack cont. • Protection from small/large query set attack: query-set-size control • A query q(C) is permitted only if N-n  |C|  n , where n  0 is a parameter of the database and N is all the records in the database CSCE 824

  32. Tracker attack q(C) is disallowed C=C1 and C2 T=C1 and ~C2 Tracker C C2 C1 q(C)=q(C1) – q(T) CSCE 824

  33. Tracker attack q(C and D) is disallowed C=C1 and C2 T=C1 and ~C2 C Tracker C2 C1 C and D q(C and D)= q(T or C and D) – q(T) D CSCE 824

  34. Query overlap attack Q(John)=q(C1)-q(C2) C1 C2 Kathy Paul John Eve Max Fred Mitch Protection: query-overlap control CSCE 824

  35. Insertion/Deletion Attack • Observing changes overtime • q1=q(C) • insert(i) • q2=q(C) • q(i)=q2-q1 • Protection: insertion/deletion performed as pairs CSCE 824

  36. Statistical Inference Theory • Give unlimited number of statistics and correct statistical answers, all statistical databases can be compromised (Ullman) CSCE 824

  37. Inferences in General-Purpose Databases • Queries based on sensitive data • Inference via database constraints • Inferences via updates CSCE 824

  38. Queries based on sensitive data • Sensitive information is used in selection condition but not returned to the user. • Example: Salary: secret, Name: public NameSalary=$25,000 • Protection: apply query of database views at different security levels CSCE 824

  39. Database Constraints • Integrity constraints • Database dependencies • Key integrity CSCE 824

  40. Integrity Constraints • C=A+B • A=public, C=public, and B=secret • B can be calculated from A and C, i.e., secret information can be calculated from public data CSCE 824

  41. Database Dependencies Metadata: • Functional dependencies • Multi-valued dependencies • Join dependencies • etc. CSCE 824

  42. Functional Dependency • FD: A  B, that is for any two tuples in the relation, if they have the same value for A, they must have the same value for B. • Example: FD: Rank  Salary Secret information: Name and Salary together • Query1: Name and Rank • Query2: Rank and Salary • Combine answers for query1 and 2 to reveal Name and Salary together CSCE 824

  43. Key integrity • Every tuple in the relation have a unique key • Users at different levels, see different versions of the database • Users might attempt to update data that is not visible for them CSCE 824

  44. Example Secret View Public View CSCE 824

  45. Updates Public User: • Update Black’s address to Orlando • Add new tuple: (Red, 22,000, Manassas) • If • Refuse update: covert channel • Allow update: • Overwrite high data – may be incorrect • Create new tuple – which data it correct • (polyinstantiation) – violate key constraints CSCE 824

  46. Updates Secret user: • Update Black’s salary to 45,000 • If • Refuse update: denial of service • Allow update: • Overwrite low data – covert channel • Create new tuple – which data it correct • (polyinstantiation) – violate key constraints CSCE 824

  47. Inference Problem • No general technique is available to solve the problem • Need assurance of protection • Hard to incorporate outside knowledge CSCE 824

  48. Next Class • Transaction Processing CSCE 824

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