Handling Encryption in an Analysis for Secure Information Flow
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1 Handling Encryption in an Analysis for Secure Information Flow Peeter Laud peeter Tartu Ülikool Cybernetica AS ESOP 2003, p.1/15
2 Overview Some words about the overall approach. Definition of secure information flow. also in computational sense. Ideas behind the analysis. The domains that the analysis uses. The abstraction. Some examples. ESOP 2003, p.2/15
3 Overall approach We have a program language containing encryption. We want to analyse programs for secure information flow. ESOP 2003, p.3/15
4 Overall approach We have a program language containing encryption. We want to analyse programs for secure information flow. Use cryptographic definitions of secure encryption. Use the same domains in defining program semantics. Bit-strings as values. more... (the security parameter) Define secure information flow using cryptographic machinery. ESOP 2003, p.3/15
5 Overall approach We have a program language containing encryption. We want to analyse programs for secure information flow. Use cryptographic definitions of secure encryption. Use the same domains in defining program semantics. Bit-strings as values. more... (the security parameter) Define secure information flow using cryptographic machinery. Devise the analysis. Its proof of correctness has cryptographic nature. ESOP 2003, p.3/15
6 Program language The WHILE-language (simple imperative language). P ::= x := o(x 1,..., x k ) skip P 1 ; P 2 if b then P 1 else P 2 while b do P b, x, x 1,..., x k Var. o Op. Enc, Gen Op. Denotational semantics, defined over program structure. Maps initial state to final state. Program state maps variables to their values. ESOP 2003, p.4/15
7 Security as independence Source of inputs defines a probability distribution D on inputs values of variables in Var S Var Secret inputs Inputs (initial state) Outputs final state) Program P Public outputs values of variables in Var P Var ESOP 2003, p.5/15
8 Security as independence Source of inputs defines a probability distribution D on inputs values of variables in Var S Var Secret inputs Inputs (initial state) Secure information flow: independence of and Outputs final state) Program P Public outputs values of variables in Var P Var ESOP 2003, p.5/15
9 Security as independence Source of inputs defines a probability distribution D on inputs values of variables in Var S Var Secret inputs Inputs (initial state) Secure information flow: independence of and Program P Outputs final state) { (S VarS, [P](S) VarP ) : S D } = { (S VarS, [P](S ) VarP ) : S, S D } Public outputs values of variables in Var P Var ESOP 2003, p.5/15
10 Indistinguishability of distributions Let D 0, D 1 be two distributions over bit-strings. Let A be a class of algorithms. Let A A Consider the following experiment Let b R {0, 1}. Generate x D b. Run A(x). Let b be the output. Let Adv D0,D 1 A = Pr[b = b ] 1/2. D 0 and D 1 are ε- indistinguishable, if Adv D0,D 1 A all A A. ε for ESOP 2003, p.6/15
11 Indistinguishability of distributions Let D 0 = {D 0 n} n N, D 1 = {D 1 n} n N be two families of distributions over bit-strings. Let A be the class of algorithms running in poly-time. Let A A Consider the following experiment Let b n R {0, 1}. Generate x D b n. Run A(n,x). Let b n be the output. Let Adv D0,D 1 A (n) = Pr[b n = b n] 1/2. D 0 and D 1 are indistinguishable, if Adv D0,D 1 A negligible for all A A. f is negligible def 1/f is superpolynomial. is ESOP 2003, p.6/15
12 Definition of security Source of inputs n defines a family of probability distributions D on inputs values of variables in Var S Var Secret inputs Inputs (initial state) Secure information flow: independence of and Outputs final state) Program P n Public outputs { (S n VarS, [P] n (S n ) VarP ) : S n D n } { (S n VarS, [P] n (S n) VarP ) : values of variables in Var P Var S n, S n D n } ESOP 2003, p.7/15
13 Program analysis approach Program text Secure Analysis or Desc. of inputs Maybe not secure Having secure information flow is uncomputable in general. Description of inputs whatever is known about D.... and expressible in the domain of the analysis. ESOP 2003, p.8/15
14 Domain of the analysis Analysis maps the description of the input distribution to the description of the output distribution. Description of D = {D n } n N is (X, K) P(P(Var) P(Var)) P(Var). (X, Y ) X, if X and Y are independent in D. k K, if (the value of) k is distributed like a key. Assume the program does not change the variables in Var S. If (Var S, Var P ) X output, then the program has secure information flow. The analysis is defined inductively over the program structure. ESOP 2003, p.9/15
15 Example: analysing assignments Consider the program x := o(x 1,..., x k ). If (X {x 1,..., x k }, Y ) X input then (X {x 1,..., x k, x}, Y ) X output. ESOP 2003, p.10/15
16 Analysing encryptions problems Let k be distributed like a key in D input. Consider the program l := k + 1. Then {l} is not independent of {k} in D output. Consider the program x := Enc(k, y). Then {x} is not independent of {k} in D output. To check whether x and k come from the same or from different samples of D output, try to decrypt x with k. These two cases should be distinguished as l is usable for decryption but x is not. ESOP 2003, p.11/15
17 Encrypting black boxes Let k Var. Let S be a program state. S([k] E ) denotes a black box that encrypts with k. I.e. S([k] E ) has an input tape and an output tape; When a bit-string w is written on the its tape, [Enc ](S(k), w) is invoked and the result written to the output tape. Indistinguishability can be defined for distributions over black boxes. Independence can be defined, too. Security of ([Gen ], [Enc ]) is defined as the indistinguishability of certain black boxes. ESOP 2003, p.12/15
18 Modified domain of the analysis Let Ṽar = Var {[x] E : x Var}. Description of a distribution D is (X, K) P(P(Ṽar) P(Ṽar)) P(Var). (X, Y ) X if X and Y are independent in D. k K, if the distribution of [k] E according to D is indistinguishable from [[Gen ]()] E. ESOP 2003, p.13/15
19 Analysing encryptions Consider the program x := Enc(k, y). If (X, Y ) X input and k K input and ({[k] E }, X Y {y}) X input then (X {x}, Y ) X output. Generally ({[k] E }, {[k] E }) X input, hence ({x}, {[k] E }) X output. If we have a program l := k + 1, then ({l}, {[k] E }) X output. For analysis of other program constructs see the article. ESOP 2003, p.14/15
20 Concluding remarks Program analysis for computationally secure information flow. Based on abstracting the families of probability distributions over program states by pairs of sets of variables and encrypting black boxes that are independent of one another in it. No (non-trivial) constraints on program structure. Can be implemented. peeter_l/research/csif ESOP 2003, p.15/15
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