Database Security and Authorization By Yazmin Escoto Rodriguez Christine Tannuwidjaja

Database Security and Authorization

ByYazmin Escoto RodriguezChristine Tannuwidjaja

Main Types of Security:

Enforce security of portions of a database against unauthorized access - Database Security and Authorization Subsystem

Prevent unauthorized persons from accessing the system itself - Access Control

Control the access to statistical databases - Statistical Database Security

Protect sensitive data that is being transmitted via some type of communications - Data Encryption

Database Security and Authorization Subsystem

Discretionary Security Mechanisms

- concerned with defining, modeling, and enforcing access to information

Mandatory Security Mechanisms for Multilevel Security

- requires that data items and users are assigned to certain security labels

Mandatory Access Control

Elements:OBJECTS CLASSIFICATIONS --class(o)--

SUBJECTS CLEARANCE --clear(s)--

Levels: Top Secret, Secret, Confidential,

Unclassified

Mandatory Access Control

Rules: Simple Property:

subject s is allowed to read data item d if clear(s) ≥ class(d)

*-property:

subject s is allowed to write data item d if clear(s) ≤ class(d)

Simple Property protects information from unauthorized access

*-property protects data from contamination or unauthorized modification

Multilevel Security Databases- example

Set up:

we have: - subject x with clear(x) = TS - subject y with clear(y) = S - subject z with clear(z) = U

Project Name Topic Location TC

Black, TS Databases, TS Los Angeles, TS TS

Silver, S Supply Chain, S New York, S S

Gold, U Inventories, S Atlanta, S S

Indigo, U Telecommunication, U Austin, U U


















Gold, U -, U -, U U



subject z wants to insert the next tuple

< Silver, LP, Omaha>






Silver, U Linear Programming, U Omaha, U U

Polyinstantiation : the existence of multiple data objects with the same key



Gold, U -, U -, U U


subject z wants to replace the null values with certain data items

< Markov Chain, New Jersey>






Gold, U Markov Chain, U New Jersey, U U

Security Relevant Knowledge

Entity Relationship-- describes the structural part of the database

Data Flow Diagram -- represents the functions the system should perform

Classification ConstraintsTo assign to security classifications concepts of schemas:- ones that classify items- ones that classify query results

System Object

What is it?• Entity type• Specialization type• Relationship type

In security it is the target of protection

Notation

O(A1..,An)- Ai (i=1..N) is an attribute and is defined over domain Di

Has an identity property (key attributes)A ⊆ (A1,..,An)

Multilevel Secure Application

MAJOR QUESTION:Which way should the attributes and occurrences of O be assigned to proper security classifications?

CLASSIFICATION

RESULT:

Security object O multilevel security object Om

Performed by means of security constraints

Graphical Extensions to the ER

N

X

P

(U) (Co) (S)

[U..S] [Co..TS]

(TS)

Secrecy Levels

Ranges of Secrecy Levels

Aggregation leading to TS (N..constant)

Inference leading to Co

Evaluation of predicate P

Security dependency

SSN

Name

Dep

Salary

Title

Title

Function

SSN

Date

Client

SubjectEmployee Project

IsAssigned

to

(0,N) (0,M)

ER Diagram

Object Classification Constraints – Simple Constraints

• Let X be a set of attributes of security object O (X {A⊆ 1,…,An}) • SiC (O(X))=C, (C SL) ∈

• Results in a multilevel object Om(A1, C1,…, An, Cn,TC) where Ci=C A∀ i X, C∈ i left unchanged for Ai X∉

• Application to ER: - SiC(Is Assigned to,{Function},S) - assigns property Function of relationship “Is Assigned to” to a

classification of secret.

SSN

Name

Dep

Salary

Title

Title

Function

SSN

Date

Client


IsAssigned

to

(0,N) (0,M)

ER Diagram – classifying properties of security objects

Object Classification Constraints – Content-based Constraints

• Let Ai be an attribute of security object O with domain D i, let P be a predicate defined on Ai and let X {A⊆ i,…,An}

• CbC (O(X), P: Ai θ a) = C or CbC (O(X), P: Ai θ Aj) = C (θ {=,≠,<,>,≤,≥}, a∈ D∈ i, i ≠ j, C SL)∈

• For any instance o of security object O(A1,…,An) for which a predicate evaluates into true the transformation into o(a1,c1,…,an,cn,tc) is performed

• Classifications are assigned in a way that c i = C in the case Ai X, c∈ i left unchanged otherwise

• Application to ER: - CbC (Employee, {SSN, Name}, Salary, ‘≥’, ‘100’, Co)) - represents the semantic that properties SSN and Name of employees with a

salary ≥ 100 are treated as confidential information

SSN

Name

Dep

Salary

Title

Title

Function

SSN

Date

Client


IsAssigned

toP

(0,N) (0,M)


Object Classification Constraints – Complex Constraints

• Let O, O’ be two security objects and the existence of an instance o of O is dependent on the existence of a corresponding occurrence o’ of O’ where the k values of the identifying property K’ of o’ are identical to k values of attributes of o (foreign key)

• Let P(O’) be a valid predicate defined on o’ and let X {A⊆ 1,…,An} be an attribute set of O

• CoC (O(X), P(O’)) = C (C SL)∈

• For every instance o of security object O(A1,…,An) for which a predicate evaluates into true in the related object o’ of O’ the transformation into o(a1,c1,…,an,cn,tc) is performed

• Classifications are assigned in a way that ci = C in the case Ai X, c∈ i left unchanged otherwise

Object Classification Constraints – Complex Constraints (con’t)

• Application to ER: - CoC (Is Assigned to, {SSN}, Project, Subject, ‘=‘, ‘Research’, S) - individual assignment data (SSN) is regarded as secret information in

the case the assignment refers to a project with Subject = ‘Research’

SSN

Name

Dep

Salary

Title

Title

Function

SSN

Date

Client


IsAssigned

toP

P

(0,N) (0,M)


Object Classification Constraints – Level-based Constraints

• Let level (Ai) be a function that returns the classification ci of the value of attribute Ai in object o(a1,c1,…,an,cn,tc) of a multilevel security object Om

• Let X be a set of attributes of Om such that X {A⊆ 1,…,An}

• LbC (O(X)) = level (Ai)

• Result for every object o(a1,c1,…,an,cn,tc) to the assignment cj = ci in the case Aj X∈

• Application to ER: - LbC (Project, {Client}, Subject) - states that property Client of security object Project must always have

the same classification as the property Subject of the Project

SSN

Name

Dep

Salary

Title

Title

Function

SSN

Date

Client


IsAssigned

toP

P

(0,N) (0,M)


Query Result Classification Constraints – Association-based Constraints

• Let O (A1,…An) be a security object with identifying property K

• Let X (X {A⊆ 1,…,An} (K X = {}) be a set of attributes of O⋂• AbC (O (K,X)) = C (C SL)∈

• Results in the assignment of security level C to the retrieval result of each query that takes X together with identifying property K

• Application to ER: - AbC (Employee, {Salary}, Co) - the salary of an individual person is confidential - the value of salaries without the information which employee gets

what salary is unclassified

SSN

Name

Dep

Salary

Title

Title

Function

SSN

Date

Client


IsAssigned

to

(0,N) (0,M)

ER Diagram – classifying query results

[Co]

Query Result Classification Constraints – Aggregation Constraints

• Let count(O) be a function that returns the number of instances referenced by a particular query and belonging to security object O (A1,…,An)

• Let X (X {A⊆ 1,…,An}) be sensitive attributes of O

• AgC (O, (X, count(O) > n = C (C SL, n N)∈ ∈

• Result into the classification C for the retrieval result of a query in the case count(O) > n, i.e. the number of instances of O referenced by a query accessing properties X exceeds the value n

Query Result Classification Constraints – Aggregation Constraints (con’t)

• Application to ER: - AgC (Is Assigned to, {Title}, ‘3’, S) - the information which employee is assigned to what projects is

regarded as unclassified - aggregating all assignments for a certain project and thereby inferring

which team is responsible for what project is considered secret

SSN

Name

Dep

Salary

Title

Title

Function

SSN

Date

Client


IsAssigned

to

(0,N) (0,M)


[Co]

3

Query Result Classification Constraints – Inference Constraints

• Let PO be the set of multilevel objects involved in a potential logical inference

• Let O, O’ be two particular objects from PO with corresponding multilevel representation O (A1,C1,…,An,Cn,TC) and O’ (A’

1,C’1,…,A’

n,C’n,TC’)

• Let X {A⊆ 1,…,An} and Y {A⊆ ’

1,…,A’n})

• IfC (O(X), O’(Y)) = C

• Results into the assignment of security level C to the retrieval result of each query that takes Y together with the properties in X

Query Result Classification Constraints – Inference Constraints (con’t)

• Application to ER: - IfC (Employee, {Dep}, Project, {Subject}, Co) - consider the situation where the information which employee is

assigned to what projects is considered as confidential - from having access to the department an employee works for and to

the subject of a project, users may infer which department may be responsible for the project and thus may conclude which employee are involved

SSN

Name

Dep

Salary

Title

Title

Function

SSN

Date

Client


IsAssigned

to

(0,N) (0,M)


X

[Co]

3

QUESTION?

Documents

Database Security and Authorization By Yazmin Escoto Rodriguez Christine Tannuwidjaja