Database security
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Database Security. Jagdish S. Gangolly School of Business State University of New York at Albany

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Database Security

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Database security

Database Security

Jagdish S. Gangolly

School of Business

State University of New York at Albany

NOTE: These notes are based on the book Security in Computing, by Charles & Shari Pfleeger, and are prepared solely for the students in the course Acc 661 at SUNY Albany. They are not to be used by others without the permission of the instructor.

Acc 661 Auditing of Adv Acctg Info Systems


Database security1

Database Security

  • Security requirements

    • Physical database integrity

    • Logical database integrity

    • Element integrity

    • Auditability

    • Access control

    • User authentication

    • Availability

Acc 661 Auditing of Adv Acctg Info Systems


Example of oracle dbms architecture

Example of Oracle DBMS Architecture

  • Source: http://www.wilsonmar.com/1oraarch.htm

Acc 661 Auditing of Adv Acctg Info Systems


Database integrity auditability

Database Integrity & Auditability

  • Field Checks (Domain)

  • Access control

  • Maintenance of change log

  • Granularity problem

  • Pass-through problem

  • Direct access of data vs. Inference problem

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Database reliability integrity

Database reliability & Integrity

  • Two-phase update: intent phase and commit phase

  • Redundancy/internal consistency

    • Error correction codes

    • Shadow fields

  • Backup and recovery procedures

  • Concurrency/Consistency/Deadlock management

  • Monitors and range comparisons

  • State constraints (eg., commit flag) and Transition constraints (eg., referential integrity)

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Inference problem

Inference Problem

  • Direct vs. Indirect attacks

  • Tracker attacks:

    count((SEX=F)  (RACE=C)  (DORM=Holmes))

    = count(SEX=F) – count((SEX=F) 

    ((RACE  C) (DORM  Holmes)))

  • Linear system vulnerability (inference by solving equations)

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Controls against inference attacks

Controls against Inference Attacks

  • Controls applied against queries

  • Controls applied against individual items in the database

    • Suppression: sensitive data values are not provided (query is rejected)

    • Concealment: answer provided is close, but not the actual value

    • Limited response suppression: Low frequency elements are not displayed

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Approaches to the inference problem

Approaches to the Inference Problem

  • Suppress obviously sensitive information

  • Track what the user knows

  • Disguise data (random perturbation, rounding, …)

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Database security

Acc 661 Auditing of Adv Acctg Info Systems


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