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ON FOUR DEFINITIONS OF DATA INTEGRITY

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Reconcile 5 definitions of data integrity. Scope is limited to data integrity ... 19. PANELISTS. John Dobson. Carl Landwehr. LouAnna Notargiacomo. Marv Schaefer ... – PowerPoint PPT presentation

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Title: ON FOUR DEFINITIONS OF DATA INTEGRITY


1
Title
FIVE
ON FOUR DEFINITIONS OF DATA INTEGRITY Ravi
Sandhu George Mason University
2
OBJECTIVE
  • Reconcile 5 definitions of data integrity
  • Scope is limited to data integrity as opposed to
    system integrity
  • None of the definitions is wrong or right

3
THE FIVE DEFINITIONS
more general
  • 1. Courtney Expectation of data quality
  • 2. Sandhu-Jajodia Safeguards against improper
    data modification
  • 3. ITSEC, CTCPEC Safeguards against unauthorized
    data modification
  • 4. Biba (or BLP) Ensure one directional
    information flow in a lattice
  • 5. Network arena Safeguards against message
    modification

less general
4
THE FIVE DEFINITIONS
OBJECTIVES
Liveness and Safety
  • 1. Expectation of data quality
  • 2. Improper data modification
  • 3. Unauthorized data modification
  • 4. One directional information flow
  • 5. No modification

Safety Only
5
THE FIVE DEFINITIONS
ENFORCEMENT IS PRIMARILY BY
External actions of users Internal actions of
the TCB
  • 1. Expectation of data quality
  • 2. Improper data modification
  • 3. Unauthorized data modification
  • 4. One directional information flow
  • 5. No modification

Internal actions of the TCB
6
THE FIVE DEFINITIONS
POLICY
  • 1. Expectation of data quality
  • 2. Improper data modification
  • 3. Unauthorized data modification
  • 4. One directional information flow
  • 5. No modification

Must be articulated by the System Owners
Is built in
7
THE FIVE DEFINITIONS
ENFORCEMENT MECHANISMS
  • 1. Expectation of data quality
  • 2. Improper data modification
  • 3. Unauthorized data modification
  • 4. One directional information flow
  • 5. No modification

Prevention Detection
Detection
8
THE DATA QUALITY DEFINITION
Integrity -- The property that data, an
information process, computer equipment, and/or
software, people, etc., or any collection of
these entities, meet an a priori expectation of
quality that is satisfactory and adequate in some
specific circumstance. Bob Courtney NIST
Invitational Workshop on Data Integrity, 1989
9
THERMOSTAT MODEL
10
BINARY OR GRADED?
  • Binary view Data has integrity if its actual
    state differs from the ideal state by less than
    the tolerable limits of deviation
  • Graded view Data has integrity in inverse
    relationship to the extent that its actual state
    differs from the ideal state

IN OTHER WORDS THIS IS A NON-ISSUE
11
CLARK-WILSON MODEL
Internal and external consistency of CDIs
USERS
TPs
IVPs
CDIs
UDIs
12
CLARK-WILSON RULES
  • C1 IVPs validate CDI state
  • C2 TPs preserve valid state
  • C3 Suitable (static) separation of duties
  • C4 TPs write to log
  • C5 TPs validate UDIs
  • E1 CDIs changed only by authorized TP
  • E2 Users authorized to TP and CDI
  • E3 Users are authenticated
  • E4 Authorizations changed only by security officer

13
CLARK-WILSON MODEL
  • Concerned with improper modification of data
  • Does not address liveness, except to require that
    integrity verification procedures verify
    correspondence of data to external reality
  • It is one approach to
  • meeting the improper data modification aspects
    of data integrity
  • with a small liveness attachment

14
TYPE ENFORCEMENT(Boebert and Kain)
  • Type enforcement can be used to implement a
    number of mechanisms related to improper
    modification of data
  • well-formed transformation procedures
  • data encapsulation
  • separation of duties
  • assured pipelines
  • Type enforcement does not directly support
    liveness requirements

15
OTHER ACCESS CONTROL MODELS
  • HRU, TAM, SPM
  • can be used to implement a number of mechanisms
    related to improper modification of data
  • do not directly support liveness requirements

16
DRAFT FEDERAL CRITERIA
  • Integrity - Correctness and appropriateness of
    the content and/or source of a piece of
    information.
  • The Courtney and Federal Criteria definitions are
    close enough that they can be reconciled fairly
    easily
  • Courtney's definition is more general, because it
    is phrased in terms of data quality, which is a
    more general notion than the specific attributes
    of correctness and appropriateness

17
DOES INTEGRITY SUBSUME SECRECY?
Top Secret Contents
Label Secret
  • By Courtney and Federal Criteria definitions this
    is an integrity violation (if we expect labels to
    be correct)

18
HOMEWORK ASSIGNMENT
Unclassified Contents
Label Secret
  • Is this an integrity violation?

19
PANELISTS
  • John Dobson
  • Carl Landwehr
  • LouAnna Notargiacomo
  • Marv Schaefer
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