UPF/UPF/Normalisation.thy

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section\<open>Policy Transformations\<close>
theory
Normalisation
imports
SeqComposition
ParallelComposition
begin
text\<open>
This theory provides the formalisations required for the transformation of UPF policies.
A typical usage scenario can be observed in the firewall case
study~\cite{brucker.ea:formal-fw-testing:2014}.
\<close>
subsection\<open>Elementary Operators\<close>
text\<open>
We start by providing several operators and theorems useful when reasoning about a list of
rules which should eventually be interpreted as combined using the standard override operator.
\<close>
text\<open>
The following definition takes as argument a list of rules and returns a policy where the
rules are combined using the standard override operator.
\<close>
definition list2policy::"('a \<mapsto> 'b) list \<Rightarrow> ('a \<mapsto> 'b)" where
"list2policy l = foldr (\<lambda> x y. (x \<Oplus> y)) l \<emptyset>"
text\<open>
Determine the position of element of a list.
\<close>
fun position :: "'\<alpha> \<Rightarrow> '\<alpha> list \<Rightarrow> nat" where
"position a [] = 0"
|"(position a (x#xs)) = (if a = x then 1 else (Suc (position a xs)))"
text\<open>
Provides the first applied rule of a policy given as a list of rules.
\<close>
fun applied_rule where
"applied_rule C a (x#xs) = (if a \<in> dom (C x) then (Some x)
else (applied_rule C a xs))"
|"applied_rule C a [] = None"
text \<open>
The following is used if the list is constructed backwards.
\<close>
definition applied_rule_rev where
"applied_rule_rev C a x = applied_rule C a (rev x)"
text\<open>
The following is a typical policy transformation. It can be applied to any type of policy and
removes all the rules from a policy with an empty domain. It takes two arguments: a semantic
interpretation function and a list of rules.
\<close>
fun rm_MT_rules where
"rm_MT_rules C (x#xs) = (if dom (C x)= {}
then rm_MT_rules C xs
else x#(rm_MT_rules C xs))"
|"rm_MT_rules C [] = []"
text \<open>
The following invariant establishes that there are no rules with an empty domain in a list
of rules.
\<close>
fun none_MT_rules where
"none_MT_rules C (x#xs) = (dom (C x) \<noteq> {} \<and> (none_MT_rules C xs))"
|"none_MT_rules C [] = True"
text\<open>
The following related invariant establishes that the policy has not a completely empty domain.
\<close>
fun not_MT where
"not_MT C (x#xs) = (if (dom (C x) = {}) then (not_MT C xs) else True)"
|"not_MT C [] = False"
text\<open>
Next, a few theorems about the two invariants and the transformation:
\<close>
lemma none_MT_rules_vs_notMT: "none_MT_rules C p \<Longrightarrow> p \<noteq> [] \<Longrightarrow> not_MT C p"
apply (induct p)
apply (simp_all)
done
lemma rmnMT: "none_MT_rules C (rm_MT_rules C p)"
apply (induct p)
apply (simp_all)
done
lemma rmnMT2: "none_MT_rules C p \<Longrightarrow> (rm_MT_rules C p) = p"
apply (induct p)
apply (simp_all)
done
lemma nMTcharn: "none_MT_rules C p = (\<forall> r \<in> set p. dom (C r) \<noteq> {})"
apply (induct p)
apply (simp_all)
done
lemma nMTeqSet: "set p = set s \<Longrightarrow> none_MT_rules C p = none_MT_rules C s"
apply (simp add: nMTcharn)
done
lemma notMTnMT: "\<lbrakk>a \<in> set p; none_MT_rules C p\<rbrakk> \<Longrightarrow> dom (C a) \<noteq> {}"
apply (simp add: nMTcharn)
done
lemma none_MT_rulesconc: "none_MT_rules C (a@[b]) \<Longrightarrow> none_MT_rules C a"
apply (induct a)
apply (simp_all)
done
lemma nMTtail: "none_MT_rules C p \<Longrightarrow> none_MT_rules C (tl p)"
apply (induct p)
apply (simp_all)
done
lemma not_MTimpnotMT[simp]: "not_MT C p \<Longrightarrow> p \<noteq> []"
apply (auto)
done
lemma SR3nMT: "\<not> not_MT C p \<Longrightarrow> rm_MT_rules C p = []"
apply (induct p)
apply (auto simp: if_splits)
done
lemma NMPcharn: "\<lbrakk>a \<in> set p; dom (C a) \<noteq> {}\<rbrakk> \<Longrightarrow> not_MT C p"
apply (induct p)
apply (auto simp: if_splits)
done
lemma NMPrm: "not_MT C p \<Longrightarrow> not_MT C (rm_MT_rules C p)"
apply (induct p)
apply (simp_all)
done
text\<open>Next, a few theorems about applied\_rule:\<close>
lemma mrconc: "applied_rule_rev C x p = Some a \<Longrightarrow> applied_rule_rev C x (b#p) = Some a"
proof (induct p rule: rev_induct)
case Nil show ?case using Nil
by (simp add: applied_rule_rev_def)
next
case (snoc xs x) show ?case using snoc
apply (simp add: applied_rule_rev_def if_splits)
by (metis option.inject)
qed
lemma mreq_end: "\<lbrakk>applied_rule_rev C x b = Some r; applied_rule_rev C x c = Some r\<rbrakk> \<Longrightarrow>
applied_rule_rev C x (a#b) = applied_rule_rev C x (a#c)"
by (simp add: mrconc)
lemma mrconcNone: "applied_rule_rev C x p = None \<Longrightarrow>
applied_rule_rev C x (b#p) = applied_rule_rev C x [b]"
proof (induct p rule: rev_induct)
case Nil show ?case
by (simp add: applied_rule_rev_def)
next
case (snoc ys y) show ?case using snoc
proof (cases "x \<in> dom (C ys)")
case True show ?thesis using True snoc
by (auto simp: applied_rule_rev_def)
next
case False show ?thesis using False snoc
by (auto simp: applied_rule_rev_def)
qed
qed
lemma mreq_endNone: "\<lbrakk>applied_rule_rev C x b = None; applied_rule_rev C x c = None\<rbrakk> \<Longrightarrow>
applied_rule_rev C x (a#b) = applied_rule_rev C x (a#c)"
by (metis mrconcNone)
lemma mreq_end2: "applied_rule_rev C x b = applied_rule_rev C x c \<Longrightarrow>
applied_rule_rev C x (a#b) = applied_rule_rev C x (a#c)"
apply (case_tac "applied_rule_rev C x b = None")
apply (auto intro: mreq_end mreq_endNone)
done
lemma mreq_end3: "applied_rule_rev C x p \<noteq> None \<Longrightarrow>
applied_rule_rev C x (b # p) = applied_rule_rev C x (p)"
by (auto simp: mrconc)
lemma mrNoneMT: "\<lbrakk>r \<in> set p; applied_rule_rev C x p = None\<rbrakk> \<Longrightarrow>
x \<notin> dom (C r)"
proof (induct p rule: rev_induct)
case Nil show ?case using Nil
by (simp add: applied_rule_rev_def)
next
case (snoc y ys) show ?case using snoc
proof (cases "r \<in> set ys")
case True show ?thesis using snoc True
by (simp add: applied_rule_rev_def split: if_split_asm)
next
case False show ?thesis using snoc False
by (simp add: applied_rule_rev_def split: if_split_asm)
qed
qed
subsection\<open>Distributivity of the Transformation.\<close>
text\<open>
The scenario is the following (can be applied iteratively):
\begin{itemize}
\item Two policies are combined using one of the parallel combinators
\item (e.g. P = P1 P2) (At least) one of the constituent policies has
\item a normalisation procedures, which as output produces a list of
\item policies that are semantically equivalent to the original policy if
\item combined from left to right using the override operator.
\end{itemize}
\<close>
text\<open>
The following function is crucial for the distribution. Its arguments are a policy, a list
of policies, a parallel combinator, and a range and a domain coercion function.
\<close>
fun prod_list :: "('\<alpha> \<mapsto>'\<beta>) \<Rightarrow> (('\<gamma> \<mapsto>'\<delta>) list) \<Rightarrow>
(('\<alpha> \<mapsto>'\<beta>) \<Rightarrow> ('\<gamma> \<mapsto>'\<delta>) \<Rightarrow> (('\<alpha> \<times> '\<gamma>) \<mapsto> ('\<beta> \<times> '\<delta>))) \<Rightarrow>
(('\<beta> \<times> '\<delta>) \<Rightarrow> 'y) \<Rightarrow> ('x \<Rightarrow> ('\<alpha> \<times> '\<gamma>)) \<Rightarrow>
(('x \<mapsto> 'y) list)" (infixr "\<Otimes>\<^sub>L" 54) where
"prod_list x (y#ys) par_comb ran_adapt dom_adapt =
((ran_adapt o_f ((par_comb x y) o dom_adapt))#(prod_list x ys par_comb ran_adapt dom_adapt))"
| "prod_list x [] par_comb ran_adapt dom_adapt = []"
text\<open>
An instance, as usual there are four of them.
\<close>
definition prod_2_list :: "[('\<alpha> \<mapsto>'\<beta>), (('\<gamma> \<mapsto>'\<delta>) list)] \<Rightarrow>
(('\<beta> \<times> '\<delta>) \<Rightarrow> 'y) \<Rightarrow> ('x \<Rightarrow> ('\<alpha> \<times> '\<gamma>)) \<Rightarrow>
(('x \<mapsto> 'y) list)" (infixr "\<Otimes>\<^sub>2\<^sub>L" 55) where
"x \<Otimes>\<^sub>2\<^sub>L y = (\<lambda> d r. (x \<Otimes>\<^sub>L y) (\<Otimes>\<^sub>2) d r)"
lemma list2listNMT: "x \<noteq> [] \<Longrightarrow> map sem x \<noteq> []"
apply (case_tac x)
apply (simp_all)
done
lemma two_conc: "(prod_list x (y#ys) p r d) = ((r o_f ((p x y) o d))#(prod_list x ys p r d))"
by simp
text\<open>
The following two invariants establish if the law of distributivity holds for a combinator
and if an operator is strict regarding undefinedness.
\<close>
definition is_distr where
"is_distr p = (\<lambda> g f. (\<forall> N P1 P2. ((g o_f ((p N (P1 \<Oplus> P2)) o f)) =
((g o_f ((p N P1) o f)) \<Oplus> (g o_f ((p N P2) o f))))))"
definition is_strict where
"is_strict p = (\<lambda> r d. \<forall> P1. (r o_f (p P1 \<emptyset> \<circ> d)) = \<emptyset>)"
lemma is_distr_orD: "is_distr (\<Otimes>\<^sub>\<or>\<^sub>D) d r"
apply (simp add: is_distr_def)
apply (rule allI)+
apply (rule distr_orD)
apply (simp)
done
lemma is_strict_orD: "is_strict (\<Otimes>\<^sub>\<or>\<^sub>D) d r"
apply (simp add: is_strict_def)
apply (simp add: policy_range_comp_def)
done
lemma is_distr_2: "is_distr (\<Otimes>\<^sub>2) d r"
apply (simp add: is_distr_def)
apply (rule allI)+
apply (rule distr_or2)
by simp
lemma is_strict_2: "is_strict (\<Otimes>\<^sub>2) d r"
apply (simp only: is_strict_def)
apply simp
apply (simp add: policy_range_comp_def)
done
lemma domStart: "t \<in> dom p1 \<Longrightarrow> (p1 \<Oplus> p2) t = p1 t"
apply (simp add: map_add_dom_app_simps)
done
lemma notDom: "x \<in> dom A \<Longrightarrow> \<not> A x = None"
apply auto
done
text\<open>
The following theorems are crucial: they establish the correctness of the distribution.
\<close>
lemma Norm_Distr_1: "((r o_f (((\<Otimes>\<^sub>1) P1 (list2policy P2)) o d)) x =
((list2policy ((P1 \<Otimes>\<^sub>L P2) (\<Otimes>\<^sub>1) r d)) x))"
proof (induct P2)
case Nil show ?case
by (simp add: policy_range_comp_def list2policy_def)
next
case (Cons p ps) show ?case using Cons
proof (cases "x \<in> dom (r o_f ((P1 \<Otimes>\<^sub>1 p) \<circ> d))")
case True show ?thesis using True
by (auto simp: list2policy_def policy_range_comp_def prod_1_def
split: option.splits decision.splits prod.splits)
next
case False show ?thesis using Cons False
by (auto simp: list2policy_def policy_range_comp_def map_add_dom_app_simps(3) prod_1_def
split: option.splits decision.splits prod.splits)
qed
qed
lemma Norm_Distr_2: "((r o_f (((\<Otimes>\<^sub>2) P1 (list2policy P2)) o d)) x =
((list2policy ((P1 \<Otimes>\<^sub>L P2) (\<Otimes>\<^sub>2) r d)) x))"proof (induct P2)
case Nil show ?case
by (simp add: policy_range_comp_def list2policy_def)
next
case (Cons p ps) show ?case using Cons
proof (cases "x \<in> dom (r o_f ((P1 \<Otimes>\<^sub>2 p) \<circ> d))")
case True show ?thesis using True
by (auto simp: list2policy_def prod_2_def policy_range_comp_def
split: option.splits decision.splits prod.splits)
next
case False show ?thesis using Cons False
by (auto simp: policy_range_comp_def list2policy_def map_add_dom_app_simps(3) prod_2_def
split: option.splits decision.splits prod.splits)
qed
qed
lemma Norm_Distr_A: "((r o_f (((\<Otimes>\<^sub>\<or>\<^sub>A) P1 (list2policy P2)) o d)) x =
((list2policy ((P1 \<Otimes>\<^sub>L P2) (\<Otimes>\<^sub>\<or>\<^sub>A) r d)) x))"
proof (induct P2)
case Nil show ?case
by (simp add: policy_range_comp_def list2policy_def)
next
case (Cons p ps) show ?case using Cons
proof (cases "x \<in> dom (r o_f ((P1 \<Otimes>\<^sub>\<or>\<^sub>A p) \<circ> d))")
case True show ?thesis using True
by (auto simp: policy_range_comp_def list2policy_def prod_orA_def
split: option.splits decision.splits prod.splits)
next
case False show ?thesis using Cons False
by (auto simp: policy_range_comp_def list2policy_def map_add_dom_app_simps(3) prod_orA_def
split: option.splits decision.splits prod.splits)
qed
qed
lemma Norm_Distr_D: "((r o_f (((\<Otimes>\<^sub>\<or>\<^sub>D) P1 (list2policy P2)) o d)) x =
((list2policy ((P1 \<Otimes>\<^sub>L P2) (\<Otimes>\<^sub>\<or>\<^sub>D) r d)) x))"
proof (induct P2)
case Nil show ?case
by (simp add: policy_range_comp_def list2policy_def)
next
case (Cons p ps) show ?case using Cons
proof (cases "x \<in> dom (r o_f ((P1 \<Otimes>\<^sub>\<or>\<^sub>D p) \<circ> d))")
case True show ?thesis using True
by (auto simp: policy_range_comp_def list2policy_def prod_orD_def
split: option.splits decision.splits prod.splits)
next
case False show ?thesis using Cons False
by (auto simp: policy_range_comp_def list2policy_def map_add_dom_app_simps(3) prod_orD_def
split: option.splits decision.splits prod.splits)
qed
qed
text \<open>Some domain reasoning\<close>
lemma domSubsetDistr1: "dom A = UNIV \<Longrightarrow> dom ((\<lambda>(x, y). x) o_f (A \<Otimes>\<^sub>1 B) o (\<lambda> x. (x,x))) = dom B"
apply (rule set_eqI)
apply (rule iffI)
apply (auto simp: prod_1_def policy_range_comp_def dom_def
split: decision.splits option.splits prod.splits)
done
lemma domSubsetDistr2: "dom A = UNIV \<Longrightarrow> dom ((\<lambda>(x, y). x) o_f (A \<Otimes>\<^sub>2 B) o (\<lambda> x. (x,x))) = dom B"
apply (rule set_eqI)
apply (rule iffI)
apply (auto simp: prod_2_def policy_range_comp_def dom_def
split: decision.splits option.splits prod.splits)
done
lemma domSubsetDistrA: "dom A = UNIV \<Longrightarrow> dom ((\<lambda>(x, y). x) o_f (A \<Otimes>\<^sub>\<or>\<^sub>A B) o (\<lambda> x. (x,x))) = dom B"
apply (rule set_eqI)
apply (rule iffI)
apply (auto simp: prod_orA_def policy_range_comp_def dom_def
split: decision.splits option.splits prod.splits)
done
lemma domSubsetDistrD: "dom A = UNIV \<Longrightarrow> dom ((\<lambda>(x, y). x) o_f (A \<Otimes>\<^sub>\<or>\<^sub>D B) o (\<lambda> x. (x,x))) = dom B"
apply (rule set_eqI)
apply (rule iffI)
apply (auto simp: prod_orD_def policy_range_comp_def dom_def
split: decision.splits option.splits prod.splits)
done
end