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

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

1 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 2006 are due by end February aboutmsr/jobs/internships/cambridge.aspx Advertisement

2 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 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 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

5 Secrecy; full trust Authentication; full trust Applications Type inference Authorization; timing; partial trust Other work on security in pi includes: Bodei/Degano/Nielson/Nielson Berger/Honda/Yoshida

6 6 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

7 A Type Discipline for Authorization Joint with C. Fournet and S. Maffeis

8 8 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

9 9 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

10 10 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: Beckers 375 rule formalization of NHS Electronic Health Record system in Cassandra (CSFW04) We use Datalog for specificity, but our results hold for any monotonic logic closed under substitutions

11 11 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

12 12 Spi calculus with annotations Security annotations Zero-bits, only to keep track of guarantees

13 13 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 P P and reduction P P relations are much as usual There are no rules for these inert processes

14 14 Some Basic Examples Process P specifying a policy and two facts: A robustly safe process : A safe process : … and the robustly safe version :

15 15 Authorization by Typing Every ok value must be justified Every binding occurrence may add facts in E

16 16 Type System: Results Verification is efficient Structural type system Low complexity of logical resolution

17 17 Process P specifying a policy and two facts: A safe process (by typing) : A robustly safe process (by typing) : Typing the Examples

18 18 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

19 19 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 Lams 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...

20 Secrecy Despite Compromise Joint work with A. Jeffrey

21 21 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, Oderskys polarized pi calculus Capabilities a? and a! for channel-based input and output

22 22 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 L 1 L 2 is itself an (inert) process Active (top-level) arcs in P induce a preorder P L 1 L 2 Least and greatest elements and Compound level (L 1, L 2 ) has P (L 1, L 2 ) L i for each i Security ordering represents compromise Let a level L be compromised iff L Hence L 1 L 2 means L 1 is at risk of compromise by L 2 So (L 1, L 2 ) is compromised if either L 1 or L 2 compromised

23 23 Security Hierarchies a any process ! ;new a;(G a | ;a ) a b (a,b) a b (a,b)(a,b) G a1a1 anan... a n+1 a n+m...

24 24 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

25 25 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

26 26 Conditional Secrecy by Typing




30 30 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 {?L 1,!L 2 } We can assert secrecy of channels, eg the k channel Type Ok{L 1 L 2 } proves that L 1 L 2 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

31 31 Typing a Crypto Protocol

32 32 Related Work Key or host compromise often modelled using events Paulson (JCS 98): oops events mark key disclosure Bugliesi, Focardi, Maffei (FMSE04) 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 (TOSEM00) DLM is one of the first system of security types to consider declassification, though at level of individual expressions, not types Several recent works (CSFW05) on temporary modifications of a security ordering, akin to our L 1 L 2 processes Many studies of process calculi with security ordering Our use of an ordering to model runtime compromise is new

33 33 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

34 The End

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