lattice-based access control models 1 daniel trivellato

Lattice-based Access Control Models 1

Daniel Trivellato

23/09/2008 DTM course - Daniel Trivellato 2

Outline

Review: DAC and the access matrix Mandatory access control and the lattice Multi-level security: the Bell-LaPadula (BLP)

model Applications of BLP


Outline

Review: DAC and the access matrix Information flow policies and the lattice Multi-level security: the Bell-LaPadula (BLP)

model Applications of BLP


Information security objectives

Information security has 3 objectives: confidentiality (or secrecy), related to

disclosure of information integrity, related to modification of information availability, related to denial of access to

information


Access Control (AC)

Goal: protect data and resources from unauthorized use

Policy: defines rules (high-level) describing the accesses to be authorized by the system

Model: formally defines the AC specification and enforcement

Mechanism: implements the policies via low level (software and hardware) functions


AC requirements

Correctness of AC relies on proper user identification/authentication

Mechanism based on the definition of a reference monitor which must be tamper-proof non-bypassable confined in a limited part of the system (security

kernel) verifiable


Discretionary Access Control (DAC) policies

explicit access rules establish who can execute which actions on which resource

users can pass on their rights to other users

granting and revocation of rights regulated by an administrative policy (centralized vs. ownership)


Access matrix model (1/2)

authorization state is represented as a matrix the system state is a triple (S,O,A), where

S is a set of subjects O is a set of objects A is an access matrix, where

rows correspond to subjects columns correspond to objects A[s,o] describes the privileges of s on o


Access matrix - Example

File 1 File 2 File 3 Program 1

Alice

own

read

write

read

write

Bob readread

writeexecute

Charlie readexecute

read


Access matrix model (2/2)

Changes of states via commands calling primitive operations: enter r into A[s,o] delete r from A[s,o] create subject s’ destroy subject s’ create object o’ destroy object o’


DAC weaknesses (1/2)

DAC is very flexible but…

Alice owns a file, she wants Bob to read it, but not Charlie

in DAC, Bob can leak the information to Charlie (even without being aware of it)

how?

Trojan horse: software containing hidden code that

performs (illegitimate) functions not known to the caller

Trojan horses


Trojan horse - Example

Bob invokes

Application (e.g. calendar)

read contactswrite stolen

code

malicious code

File contacts

owner Bob

Alice 06-12345678Charlie 06-23456781

File stolen

owner Daniel

Alice 06-12345678Charlie 06-23456781

(Bob,write,stolen)


DAC weaknesses (2/2)

DAC constraints only direct access, no control on what happens to information after release

Trojan horses exploit access privileges of calling subjects

covert channels (later)


Outline

Review: DAC and the access matrix Mandatory Access Control and the lattice The Bell-LaPadula (BLP) model Applications of BLP


Mandatory Access Control (MAC) policies

goal: prevent the illegitimate flow (leakage) of information

idea: attach security labels to subject and objects

Makes a distinction between users and subjects acting on their behalf we can trust the users, but not the subjects


Military security (1/3)

Initially (‘70s) most research in information security was applied to the military domain

need to protect information that, if known by an enemy, might damage national security

protecting information is costly


Military security (2/3)

different sensitivity levels (hierarchical) are assigned to information unclassified (= public) (restricted) < confidential < secret < top secret

a clearance is assigned to individuals (reflects their trustworhtiness)

Example: in the USA, a ‘secret’ clearance involves checking FBI fingerprint files, ‘top secret’ also involves background checks for the previous 5-15 years of employment


Military security (3/3) an individual has not to be aware of all

information at a given sensitivity level finer grained classification on the basis of the

need to know information about different areas divided into

separate compartments (e.g. nuclear, chemical), possibly overlapping

the classification (security class) of an object is a tuple (sensitivity level,{compartment})


Information flow policies (1/2)

defined by Denning (’76) concerned with the flow of information from

one security class to another information flow as an ordering relation instead of a list of axioms governing users’

accesses, simply require that information transfers obey the ordering relation


Information flow policies (2/2)

SC is a set of security classes may_flow is a relation on SC x SC ‘+’ is a function from SC x SC to SC An information flow policy is a triple

<SC,may_flow,+>

Example: SC = {(S,{nuclear,chemical}), (S,{nuclear}), (S,{chemical})} (S,{nuclear}) may_flow (S,{nuclear,chemical}); (S,{nuclear}) + (S,{chemical}) = (S,{nuclear,chemical})


Information flow - Example Consider a company in which line managers report income to two

different superiors - a business manager and an auditor. The auditor and the business manager are independent. Information may_flow from the workers to the line managers, and from the line managers to the business manager and the auditor.


Orders and lattice (1/2)

partial order of a set: binary relation that is transitive: a ≥ b and b ≥ c then a ≥ c reflexive: a ≥ a anti-symmetric/acyclic: a ≥ b and b ≥ a then a = b

total order: like a chain (either a ≥ b or b ≥ a)

lattice: every subset has a least upper bound, and a greatest lower bound


Orders and lattice (2/2)

Hasse diagrams depict a partial order

(e) is not a lattice


Information flow - Example Consider a company in which line managers report income to two

different superiors - a business manager and an auditor. The auditor and the business manager are independent. Information may_flow from the workers to the line managers, and from the line managers to the business manager and the auditor.

may-flow depicted below is not a lattice


Classification lattice - Example Levels: TS, S and TS > S

lub((TS, {Nuclear}), (S, {Nuclear, Chemical})) = glb((TS, {Nuclear}), (S, {Nuclear, Chemical})) =

(TS, {Nuclear, Chemical})

(S, {Nuclear})

TS, {Nuclear, Chemical}

TS, {Nuclear} TS, {Chemical}S, {Nuclear, Chemical}

TS, {}

S, {}

S, {Nuclear} S, {Chemical}

the partial order on security classes is called dominates(L1,C1) ≥ (L2,C2) iff L1 ≥ L2 and C2 C C1

Compartments: Nuclear, Chemical


Denning’s axioms

under the following assumptions, an information flow policy forms a finite lattice:

1. the set of security classes SC is finite

2. the may-flow relation is a partial order on SC

3. SC has a lower bound w.r.t. may_flow

4. operator + is a totally defined least upper bound operator


Outline



The BLP model

formalizes mandatory policy for secrecy goal: prevent information flow to lower or

incomparable security classes multi-level security

idea: augment DAC with MAC (security labels) to enforce information flow policies

two-step approach1. discretionary access matrix D2. operations authorized by MAC policy, over

which users have no control


BLP mandatory access rules

object o has security label (class) SL(o) subject s has security label (clearance) SL(s) simple security property: subject s can read

object o only if SL(s) ≥ SL(o) *-property: subject s can write object o only if

SL(o) ≥ SL(s)

NO READ UPNO WRITE DOWN

Trojan horses leaking information are blocked


BLP information flow

SUBJECTS OBJECTS

…….....

…….....

…….....

…….....

TS

S

C

U

Info

rma

tion

flow

TS

S

C

U

writ

e

read

writ

e

read

writ

e

read

writ

e

read


BLP - Secure states system modeled as a finite state machine (set of

states and transition of states) a state contains information about the current

authorizations and security labels a transition transforms a state into another state

(adding or removing authorizations) a state is secure if the current authorizations satisfy

the simple and * security properties a system is secure if every state reachable by

executing a finite sequence of transitions is secure


BLP + tranquility

Assume that when a subject request access to a resource the security levels of all subjects and objects are downgraded to the lowest level and access is granted

secure by BLP…but not secure in a meaningful sense!!!

Tranquility property strong: security labels never change during system operation

TOO STRONG! weak: labels never change in such a way as to violate a defined

security policy

e.g. dynamic upgrade of labels principle of least privilege


Exceptions to properties

Data association and aggregation: a set of values seen together is to be classified higher than the single values (e.g. name and salary)

Sanitization and downgrading: a process may produce data less sensitive than those it has read; data may need to be downgraded after some time (embargo)

TRUSTED SUBJECTS!


MAC weaknesses MAC policies remain vulnerable to covert

channels Examples

a low level subject requires a resource (e.g. CPU) that is busy by a high level subject

a high level process can lock shared resources and modify the response times of processes at lower levels (timing channels)

non-interference: the activity of a high level process must have no detectable effect on processes at lower or incomparable level


Outline



Real world examples

MULTICS for the Air Force Data Services Centre (time-sharing OS)

MITRE brassboard kernel SIGMA message system KSOS (Kernelized Secure Operating System) SCOMP (Secure Communications Processor) PSOS (Provably Secure Operating System) SELinux multi-level Database Management Systems


KSOS

a system is multi-level secure if, for any two processes HIGH and LOW, HIGH can do nothing to affect in any way the operation of LOW LOW can know nothing of HIGH

security levels associated with function references and state variables

no result of any function at a low level should depend from a higher level variable/function


SELinux (NSA) a security context contains all security

attributes associated with subject and objects policy decisions are made by a security

server residing in-kernel (no kernel-userspace calls for security decisions)

the server provides a security API to the rest of the kernel, with security model hidden behing this API

mechanisms to isolate different services running on a machine


Multi-level DBMSs

in an OS security class is assigned to files or programs

DBMS can afford a finer grained classification relation attribute tuple element

commercial ML-DBMS (e.g. Oracle) support classification at the level of tuple


ML-DB – Example (element)

Name LN Dept LD Salary LS

Alice U Dept1 U 100K U

Bob S Dept2 S 200K S

Charlie U Dept2 U 150K S


ML-DBMSs - Polyinstantiation

Access control must obey to BLP principlesA. A low level subject requests to insert a tuple already

existing with a higher classificationB. A high level subject requests to insert a tuple

already existing with a lower classification 3 possible solutions:

tell the subject

replace the old tuple

insert a new tuple

A. information leakageB. denial of serviceA. loss of integrityB. information leakageA. polyinstantiated tupleB. polyinstantiated tuple


Polyinstantiation - Example





Request by an U-subject:

UPDATE Employee SET Salary=‘100K’ WHERE Name=‘Charlie’





Charlie U Dept2 U 100K U


Polyinstantiation - Example





Request by a S-subject:

INSERT INTO Employee VALUES (Alice, Dept1, 150K)





Alice S Dept1 S 150K S


ML-DBMSs - Cover stories

Polyinstantiation is blaimed to be one of the main reasons why multi-level DBMSs have not succeeded…it quickly goes out of hand

however, it is useful to support cover stories cover story: incorrect values returned to a low

level subject to protect the real value (useful when returning restricted/null would leak information)


ML-DBMSs - Architecture trusted subject: data stored in a single DB

the DBMS must be trusted

trusted computing base: data are partitioned in different DBs only OS needs to be trusted DBMS access data that can be read at its level

Low subject

High subject

TRUSTED DBMS

TRUSTED OS

ML-DB

….Low

subjectHigh subject

High DBMS

TRUSTED OS

Low DB

……..

Low DBMS

High DB

...

...


Summary

DAC: users have the ability to pass on their rights to other users based on the access matrix model no control on information after release: vulnerable

to information leakage (e.g. Trojan horses) MAC: prevents illegitimate flow of information

by attaching security labels to subjects and objects distinction between users (trusted) and subjects

(i.e. processes, not trusted)


Summary

Lattice: the partial order of security classes forms a lattice structure

BLP: augments DAC with MAC to prevent information flow to lower or incomparable classes NO READ UP NO WRITE DOWN


Exercises

Does DAC prevent information leakage? Why? And what about MAC, does it always prevent information leakage?

Construct a lattice of security classes for security levels public < secret < top-secret and compartments {army, politics, business}

How many security classes can be constructed with n security levels and m compartments?


Exercises

Can a user cleared for (S, {dog, cat, pig}) access to documents classified in the following ways under the military information flow model? (TS, {dog}) (S, {dog}) (S, {dog, cow}) (S, {monkey}) (C, {dog, pig, cat}) (C, { })


Exercises What policy is adopted in the standard

Windows implementations? Consider two subjects s1 and s2, with security

classification TS and S respectively. Are the following operations authorized according to BLP, and if not, why?

1. s1 requests to write a S-object o1 (refer to the tranquility principle)

2. s2 requests to read o1

3. s1 requests to send a TS-object o2 to s2

4. s1 requests to copy the content of o2 to o1


Exercises

What is the security class of an object obtained by aggregating the content of a S- and a TS-object?

Describe a situation in which you may want to allow the security kernel to violate one of the security properties of BLP


References

Ravi S. Sandhu – Lattice-Based Access Control Models (strongly recommended)

Carl E. Landwehr – Formal Models for Computer Security (strongly recommended)

Pierangela Samarati, Sabrina De Capitani di Vimercati - Access Control: Policies, Models, and Mechanisms (recommended)

Ross Anderson – Security Engineering (2nd Edition) (suggested)

Thank you for your [email protected]

lattice-based access control models 1 daniel trivellato

Documents

access privileges

direct access

denial of access

dac constraints

charliein dac

latticemultilevel security

privileges of s

low level software