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Low-equivalence in figure 4 we formalize the low-equivalence relation. for complex types, i.e., pairs and environments, low-equivalence is defined structurally by demanding the parts of the complex type to be low-equivalent w.r.t. the corresponding type. any values are low-equivalent w.r.t. a secret type. integers are low-equivalent w.r.t. a public integer type if they are equal. low-equivalence for keys is slightly different since keys are not annotated with a security level--only a key level--whose meaning is defined by well-formed values as different sets. even though it is semantically meaningful to add a security level to key types--the values of keys can be indirectly affected by computation--we have chosen not to. instead, a public key is considered to be of low security and a secret key of high security. thus, public keys are lowequivalent if they are equal, and any two secret keys are low-equivalent. the most interesting rule is the rule defining low-equivalence w.r.t. a public encryption type le-enc-l1 ; and le-enc-l2 ; . these two rules define the difference in meaning between encryption with a secret and a public key. first, in both rules, the encrypted values must be low-equivalent w.r.t. the low-equivalence relation of encrypted values. second, there must exist a pair of low-equivalent keys w.r.t. the key type of the encryption type that decrypt the encrypted value to two values. this is where the rules differ. since ciphertexts created by public keys can be decrypted by anyone with access to the public keys, we have to demand that the inside of the encrypted value contains only public values. this is done in the le-enc-l2 ; rule, which demands that the inside is not only low-equivalent w.r.t. its type , but low-equivalent w.r.t. tolow ; , which is defined as follows: tolow t ; t l tolow key p ; key p tolow 1 , 2 tolow 1 ; , tolow 2 the le-enc-l1 ; rule can be seen as encoding the power of the attackers. for encryption with secret keys the demand is only that the resulting values should be lowequivalent w.r.t. the primitive type of the encryption type. this way, we demand low-equivalence inside encrypted values and make certain that that the result of decrypting low-equivalent encrypted values will result in low-equivalent values and that secret values are not stored inside encrypted values that are created by public keys. subtyping the subtyping is entirely standard; it allows public information to be seen as secret with the exception of invariant subtyping for keys. the subtyping relation for primitive types, : , and the subtyping relation for security levels defines the corresponding join operators. the subtyping relation can be found in [3]. expression type rules the type rules for expressions are of the form , pc e : figure 5 defines typing rules for non-standard expressions, while the rest of the rules can be found in [3]. the generation of a new key with the requested security level results in a key with that security level if the requested level is not below the context type. the reason for this is that we assume that the public-key stream is publicly observable. encryption with secret keys will always result in public encrypted values. encryption with public keys is possible on any value but produces a result that is as secret as the original value. both the type rule for key generation and the type rule for.
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Boersma, paul and bruce hayes. 2001. empirical tests of the gradual learning algorithm. linguistic inquiry 32 1 ; : 4586. bresnan, joan, shipra dingare and christopher manning. 2001. soft constraints mirror hard constraints: voice and person in english and lummi. in m. butt and t.h. king eds ; , proceedings of the lfg 01 conference. csli publications. jger, gerhard. 2004. maximum entropy models and stochastic optimality theory. unpublished manuscript, university of potsdam. gale, william a. and kenneth ward church. 1991. a program for aligning sentences in bilingual corpora. in proceedings of the 29th meeting of annual the association for computational linguistics, pp. 177184. geman, stuart and mark johnson. 2002. dynamic programming for parsing and estimation of stochastic unification-based grammars. in proceedings of the 40th annual meeting of the association for computational linguistics acl'02 ; , pp. 279286. philadelphia. gildea, daniel. 2003. loosely tree-based alignment for machine translation. in proceedings of the 41st annual meeting of the association for computational linguistics acl'03 ; , sapporo, japan, pp. 8087. grimshaw, jane. 1991. extended projection. unpublished manuscript, brandeis university. goldwater, sharon and mark johnson. 2003. learning ot constraint rankings using a maximum entropy model. in j. spenader, a. eriksson and . dahl eds ; , proceedings of the stockholm workshop on `variation within optimality theory'. april 2627, 2003 at stockholm univ. sweden, pp. 111120. koehn, philipp. 2002. europarl: a multilingual corpus for evaluation of machine translation. unpublished manuscript, university of southern california. kuhn, jonas. 2001. generation and parsing in optimality theoretic syntax issues in the formalization of ot-lfg. in p. sells ed. ; , formal and empirical issues in optimality-theoretic syntax, pp. 313366. csli publications, stanford. kuhn, jonas. 2003. optimality-theoretic syntax a declarative approach. csli publications, stanford, ca. kuhn, jonas. 2004. experiments in parallel-text based grammar induction. in proceedings of the 42nd annual meeting of the association for computational linguistics acl 2004 ; , pp. 470477. kuhn, jonas. 2005a. an architecture for parallel corpus-based grammar learning. in b. fisseni, h.-c. schmitz, b. schrder and p. wagner eds ; , sprachtechnologie, mobile kommunikation und linguistische ressourcen. beitrge zur gldv-tagung 2005 in bonn, pp. 132144. peter lang, frankfurt main. kuhn, jonas. 2005b. parsing word-aligned parallel corpora in a grammar induction context. in proceedings of acl 2005 workshop on parallel text. ann arbor, michigan. miller, scott, robert bobrow, robert ingria and richard schwartz. 1994. hidden understanding models of natural language. in proceedings of the 32nd annual meeting of the association for computational linguistics acl 1994 ; , pp. 2532. och, franz josef and hermann ney. 2003. a systematic comparison of various statistical alignment models. computational linguistics 29: 1951. ratnaparkhi, adwait. 1999. learning to parse natural language with maximum entropy models. machine learning 34: 151175.
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