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Decentralized Robustness

Decentralized Robustness. Stephen Chong Andrew C. Myers Cornell University CSFW 19 July 6 th 2006. Information flow. Strong end-to-end security guarantees Noninterference [Goguen and Meseguer 1982] Enforceable with type systems [Volpano, Smith, and Irvine 1996] and many others

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Decentralized Robustness

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  1. Decentralized Robustness • Stephen Chong • Andrew C. Myers • Cornell University • CSFW 19 • July 6th 2006

  2. Information flow • Strong end-to-end security guarantees • Noninterference [Goguen and Meseguer 1982] • Enforceable with type systems • [Volpano, Smith, and Irvine 1996]and many others • But programs declassify information • Breaks noninterference! • Need semantic security conditions that hold in presence of declassification

  3. Robustness • Intuition: An attacker should not be able to control the release of information • Zdancewic and Myers [CSFW 2001] • Defined semantic security condition • An “active” attacker should not learn more information than a “passive” attacker. • Myers, Sabelfeld, and Zdancewic [CSFW 2004] • Language-based setting • Data to declassify and decision to declassify should not be influenced by attacker • Type system for enforcement • Track integrity • High-integrity = not influenced by attacker

  4. Issues with robustness Bob Charlie • May be many attackers • Different attackers have different powers • How to ensure a system is robust against an unknown attacker? • Different users trust different things Alice Damien

  5. Decentralized robustness • Define robustness against all attackers • Generalization of robustness • Not specialized for a particular attacker • Uses decentralized label model [Myers and Liskov 2000] to characterize the power of different attackers • Enforce robustness against all attackers • Complicated by unbounded, unknown attackers • Sound type system • Implemented in Jif 3.0 • Decentralized robustness = robustness + DLM

  6. Attackers • Language-based setting • An attacker A may • view certain memory locations • knows program text • inject code at certain program points • (and thus modify memory) • Power of attacker is characterized by security labels RA and WA • RA is upper bound on info A can read • WA is lower bound on info A can write • Defn: Program c has robustness w.r.t. attacks by A with power RA and WA if A’s attacks cannot influence information released to A. security lattice ℒ most restrictive RA WA least restrictive

  7. Example Alice Bob Charlie // Charlie can readpub, can’t readsalary[i], totalSalary, avgSalary // pub⊑ RCharlie avgSalary⋢ RCharlie … // Charlie can modify employeeCount // WCharlie⊑ employeeCount totalSalary = i = 0; while (i < employeeCount) { totalSalary += salary[i]; i += 1; } avgSalary := totalSalary / i; pub := declassify(avgSalary, (Alice or Bob) to (Alice or Bob or Charlie)); employeeCount := 1; from to

  8. Decentralized label model • Allows mutually distrusting principals to independently specify security policies [Myers and Liskov 2000] • This work: full lattice and integrity policies • Security labels built from reader policies and writer policies • Reader policies o→r • Owner o allows r (and implicitly o) to read information • Any principal that trusts o adheres to policy • (i.e., allows at most o and r to read) • Any principal not trusting o gives policy no credence • Confidentiality policies • Close reader policies under conjunction and disjunction

  9. Integrity policies • Writer policies o←w • Owner o allows w (and implicitly o) to have influenced (written) information • Any principal that trusts o adheres to policy • (i.e., allows at most o and w to have written) • Any principal not trusting o gives policy no credence • Integrity policies • Close writer policies under conjunction and disjunction

  10. Semantics of policies • Confidentiality • readers(p, c) is set of principals that principal p allows to read based on confidentiality policy c • c is no more restrictive than d (written c ⊑Cd) if for all p, readers(p, c) ⊇ readers(p, d) • ⊑C forms a lattice: meet is disjunction, join is conjunction • Integrity • writers(p, c) is set of principals that principal p has allowed to write based on integrity policy c • c is no more restrictive than d (written c ⊑Id) if for all p, writers(p, c) ⊆ writers(p, d) • ⊑I forms a lattice: meet is conjunction, join is disjunction • Dual to confidentiality

  11. Labels • A label 〈c, d〉 is a pair of a confidentiality policy c and an integrity policy d • 〈c, d〉 ⊑ 〈c′, d′〉 if and only if c ⊑Cc′ andd ⊑Id′ • Labels are expressive and concise language for confidentiality and integrity policies

  12. Attacker power in the DLM • For arbitrary principals p and q, need to describe what p believes is the power of q • Define label Rp→q as least upper bound of labels that p believes q can read. • ℓ ⊑ Rp→qif and only if q ∈readers(p,ℓ) • Define label Wp←q as greatest lower bound of labels that p believes q can write. • Wp←q ⊑ ℓif and only if q ∈writers(p,ℓ) Rp→q Wp←q

  13. Robustness against all attackers • Defn: Command c has robustness against all attackers if: • for all principals p and q, • c has robustness with respect to • attacks by q with power Rp→q and Wp←q

  14. Enforcement • Enforcing robustness [Myers, Sabelfeld, Zdancewic 2004] • “If declassification gives attacker A info, then A can’t influence data to declassify, or decision to declassify.” • Enforcing robustness against all attackers • “For all p and q, if p believes declassification gives q info, then p believes q can’t influenced data to declassify, or decision to declassify.” • More formally: • For all principals p and q, • if ℓfrom ⋢ Rp→qand ℓto ⊑ Rp→qthen • Wp←q ⋢pcandWp←q ⋢ ℓfrom • Can’t use MSZ type system for all possible attackers • Would require different type system for each p and q!

  15. A sound unusable typing rule ℓto ⊔ pc⊑ Γ(v) Γ, pc ⊢ e:ℓfrom ∀p, q. if ℓfrom ⋢ Rp→qand ℓto ⊑ Rp→qthenWp←q ⋢pc ∀p, q. if ℓfrom ⋢ Rp→qand ℓto ⊑ Rp→qthenWp←q ⋢ ℓfrom Γ, pc ⊢ v := declassify(e, ℓfrom to ℓto) ⇒ For all principals p and q, if ℓfrom ⋢ Rp→qand ℓto ⊑ Rp→qthen Wp←q ⋢pcandWp←q ⋢ ℓfrom

  16. Sound typing rule ℓto ⊔ pc⊑ Γ(v) Γ, pc ⊢ e:ℓfrom ℓfrom ⊑ ℓto ⊔ writersToReaders(pc) ℓfrom ⊑ ℓto ⊔ writersToReaders(ℓfrom) Γ, pc ⊢ v := declassify(e, ℓfrom to ℓto) • Conservatively converts writers of a label into readers. • Used to compare integrity against confidentiality. • ∀ℓ.∀p. writers(p, ℓ)⊆ • readers(p, writersToReaders(ℓ)) ⇒ For all principals p, • readers(p, ℓfrom) ⊇ readers(p, ℓto) ∩ writers(p, pc) • and readers(p, ℓfrom) ⊇ readers(p, ℓto) ∩ writers(p, ℓfrom) ⇒ For all principals p and q, if ℓfrom ⋢ Rp→qand ℓto ⊑ Rp→qthen Wp←q ⋢pcandWp←q ⋢ ℓfrom

  17. Conclusion Damien • Decentralized robustness = robustness + DLM • Defined robustness against all attackers • Semantic security condition • Generalizes robustness to arbitrary attackers • Decentralized label model expresses attackers’ powers • Sound type system • Implemented in Jif 3.0 • Available at http://www.cs.cornell.edu/jif • Paper also considers downgrading integrity • Qualified robustness [Myers, Sabelfeld, and Zdancewic 2004] is generalized to qualified robustness against all attackers

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