1 Internship at Microsoft Research? 12 week research projects, undertaken at MSR Cambridge, typically by grad students mid-way through their PhD. Goal:

1

Internship at Microsoft Research?

12 week research projects, undertaken at MSR Cambridge, typically by grad students mid-way through their PhD.

Goal: complete and publish research project with an MSR researcher:

K..Bhargavan, C. Fournet, A. Gordon, and R. Pucella, TulaFale: A security tool for web services, FMCO 2003

C. Fournet, A. Gordon, and S. Maffeis A type discipline for authorization policies, ESOP 2005

Applications for Summer 2006are due by end February 2006http://research.microsoft.com/aboutmsr/jobs/internships/cambridge.aspx

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From Typed Process Calculi to Source-Based Security

Andy Gordon (MSR)

SAS 2005, London September 7-9, 2005

Based on joint work with Cédric Fournet (MSR), Alan Jeffrey (DePaul and Bell Labs), and Sergio Maffeis

(Imperial)

3

Background Process calculi are an effective setting for

modelling security protocols and specifying their properties

Lowe (1995) used CSP to find his famous attack on the Needham-Schroeder public key protocol (1978)

The spi calculus (AG97) began a line of work in which many protocols have been expressed and analyzed within pi calculi

Security types allow the typechecker to prove various security properties automatically

Syntax-driven typing rules can be checked efficiently, with no state space exploration

Properties of arbitrarily many sessions and principals proved relative to arbitrary Dolev-Yao opponent

Inevitably incomplete as D-Y problem undecidable (DLMS99)

4

An Authentication Example

Begin Assertion A begins Sent(A,B,msg)

Message 1 B A: nonce

Message 2 A B: A, {msg,nonce}KAB

End Assertion B ends Sent(A,B,msg)

We specify the authentication of the message via assertions: each end is to have distinct, preceding begin with same label

Attacks (replays, impersonations) show up as violations of these assertions

By assigning KAB the following type, we can check the protocol:

Key (msg:T, Nonce [Sent(A,B,msg)] )

Suppose A and B are principals sharing a symmetric-key KAB

The following should ensure B gets a fresh message from A

http://www.cryptyc.org

2000

2001

2002

2003

2004

2005

2002Abadi/Blanchet Analyzing securityprotocols with secrecy typesand logic programs (POPL 2002)

2001Abadi/Blanchet Secrecy typesfor asymmetric communication(FOSSACS 2001)

1999Abadi Secrecy by typingin security protocols(JACM 1999)

2001Gordon/Jeffrey Typingcorrespondence assertionsfor communicationprotocols (MFPS 2001)

2001Gordon/Jeffrey Authenticityby typing for securityprotocols (CSFW 2001)

2002Gordon/Jeffrey Types and effectsfor asymmetic cryptographicprotocols (CSFW 2002)

2002Lashari A polymorphic type andeffect system for an objectoriented language to typecheck cryptographic protocols (Masters, DePaul)

2005Focardi/Maffei/Placella Inferringauthentication tags (WITS 2005)

2004Bugliesi/Focardi/Maffei Compositionalanalysis of authenticationprotocols (ESOP 2004)

2003Gordon/Pucella Validating a webservices security abstractionby typing (XML Security 2003)

2005Fournet/Gordon/Maffeis A typediscipline for authorizationpolicies (ESOP 2005)

2005Gordon/Jeffrey Secrecy despitecompromise (CONCUR 2005)

2005Haack/Jeffrey Timed spi-calculuswith types (CONCUR 2005)

Secrecy; full trust Authentication; full trust

Applications

Type inferenceAuthorization; timing; partial trust

Other work on security in pi includes:Bodei/Degano/Nielson/NielsonBerger/Honda/Yoshida

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This Talk Two new developments

Checking authorization (is this request allowed?) as well as authentication (who sent this request?)

A type discipline for authorization policies (With C. Fournet and S. Maffeis. ESOP'05)

Allowing a realistic threat model in which some trusted hosts become compromised over time

Secrecy despite compromise: types, cryptography, and the pi-calculus. (With A. Jeffrey. CONCUR'05)

A useful idea in both is the use of inert processes to record events and to express security properties

A Type Disciplinefor Authorization

Joint with C. Fournet and S. Maffeis

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Motivations Authorization policies prescribe conditions that must

be satisfied before performing any privileged action In practice, policies often only formalized in code

Hard to extract, hard to reason about, hard to audit Tied to low-level authentication mechanisms Relationship of code to intended policy left informal

In principle, Policies can be formalized in high-level languages (e.g.

Datalog) separate from the implementation code Policies should be independent of enforcement mechanisms Conformance of an implementation should be verifiable

Our initial motivations Difficulty of auditing use of Java-style stack inspection Authorization for web services

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Our Approach We propose language-based mechanisms to

express the intended policy of an implementation, and to verify conformance to the policy

We use the authorization policy as a specification As opposed to being directly executed The same policy supports alternative implementations

Our implementation language is a spi calculus But the approach would apply to higher-level languages

We use types to verify that annotated code correctly implements a given authorization policy

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Datalog for Authorization

Datalog is a fragment of Prolog without negation, free variables and term constructors

Many policy languages for trust or authorization are based on Datalog or related logics (SD3, Binder, Cassandra, SPKI, XrML, …)

Realistic policies: Becker’s 375 rule formalization of NHS Electronic Health Record system in Cassandra (CSFW’04)

We use Datalog for specificity, but our results hold for any monotonic logic closed under substitutions

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Ex: Conference Reviewing

Extensional database: known facts (closed literals)

These generalize the events, such as Sent(A,B,msg), used in direct correspondence assertions to specify authentication

Rules for deriving new facts

Intensional database: facts derived from rules

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Spi calculus with annotations

Security annotation

s

Zero-bits, only to

keep track of

guarantees

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Authorization Properties Inert processes model events and properties

A statement C models part of the authorization policy

Specifically, a fact L models an authorization event

An expectation expect L models an expected property

The structural equivalence PP’ and reduction PP’ relations are much as usual

There are no rules for these inert processes

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Some Basic Examples

Process P specifying a policy and two facts:

A robustly safe process :

A safe process :

… and the robustly safe version :

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Authorization by Typing

Every ok value must be justified

Every binding occurrence may

add facts in E

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Type System: Results

Verification is efficient Structural type system Low complexity of logical resolution

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Process P specifying a policy and two facts:

A safe process (by typing) :

A robustly safe process (by typing) :

Typing the Examples

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In the Full Version Two distributed implementations of a policy for

conference management One where each delegation is registered online The other enables offline, signature based delegation

with authorization decisions based on certificate chains

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Summary We used inert processes to annotate programs with

expected authorization properties “At this point Report(U,ID,R) will be derivable” Goal: check code annotations against explicit logical policy

Extends work to typecheck direct correspondences Woo and Lam’s direct correspondences are derivable

Much prior work on logics for authorization Ours is amongst the first to relate such logics to code and

to use DY approach to model untrusted parts of system

Limitations: Like many systems, no support for revocation Interpreter + typechecker, but no direct implementation Principals completely distrusted or completely trusted...

Secrecy Despite Compromise

Joint work with A. Jeffrey

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Motivation Our opponent model has assumed a fixed partition

Trusted insiders versus distrusted outsiders

Real situations are more complex Machines become compromised Trusted users turn out to be untrustworthy

How can a type system handle partial compromise of a dynamically changing population of principals?

We approach this question from a simpler setting than spi, Odersky’s polarized pi calculus

Capabilities a? and a! for channel-based input and output

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Security Levels Code annotated with security levels (or

principals) Different regions may run on behalf of different levels Level annotation L attached to each output out a! M :: L Level represents the opponent

Security ordering induced by arc processes Arc L1 L2 is itself an (inert) process Active (top-level) arcs in P induce a preorder P L1 L2 Least and greatest elements and Compound level (L1 , L2) has P (L1 , L2) Li for each i

Security ordering represents compromise Let a level L be compromised iff L Hence L1 L2 means L1 is at risk of compromise by L2

So (L1, L2) is compromised if either L1 or L2 compromised

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Security Hierarchies

a

any process any process

!;new a;(G a | ;a )

a b

(a,b)

a

b

(a,b)

G

a1 an...

an+1 an+m...

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Conditional Secrecy We say M is public if it can be output at

level

We model secrecy invariants as inert processes:

An expectation secret M amongst N is justified if every output of M is at a higher security level than N

Read as “if M becomes public then N is compromised”

The secret message M may include fresh names

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A Basic Example Consider two processes at level L that

exchange a fresh secret s on a private channel k

We want a type system that: Checks secrecy of s while k is secret and L

uncompromised Eventually allows k and s to be made public once L

is compromised – an event modelled by the arc L

A specific formal problem: verify robust safety of

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Conditional Secrecy by Typing

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In the Full Version Types ordered via a subtype relation

Main rule: if Public(T) and Tainted(T’) then T <: T’

Secrecy types are special case of (kinded) channels Kinds take the form {?L1,!L2} We can assert secrecy of channels, eg the k channel

Type Ok{L1 L2} proves that L1 L2 Allows security orderings to be communicated

Type system reflects usage of pair types (split x:T, U) – first element extracted without checking (match x:T, U) – first element matched against known value Full form is (y x:T, U) where {split,match} and y is an

existentially quantified lower bound on x used only in types

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Typing a Crypto Protocol

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Related Work Key or host compromise often modelled using events

Paulson (JCS 98): “oops” events mark key disclosure

Bugliesi, Focardi, Maffei (FMSE’04) allow for compromised hosts in a type system for spi, but assume the set is known statically

Types to govern data declassification are a Hot Topic Myers and Liskov (TOSEM’00) DLM is one of the first system

of security types to consider declassification, though at level of individual expressions, not types

Several recent works (CSFW’05) on temporary modifications of a security ordering, akin to our L1 L2 processes

Many studies of process calculi with security ordering

Our use of an ordering to model runtime compromise is new

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Summary, Conclusions We introduced a mutable security ordering to

model a dynamic, partially compromised set of principals

As with our authorization model, we rely on inert processes to describe events and expected properties

There remains much promise in the area of process calculi with security types

These two systems should combine fairly smoothly They should be applicable to an important open problem;

how to check security properties of the actual source code of crypto protocols and the applications built on them

The End