def check_diversity(group, L):
"""check if group satisfy l-diversity
"""
SA_values = set()
for index in group:
str_value = list_to_str(gl_data[index][-1], cmp)
SA_values.add(str_value)
if len(SA_values) >= L:
return True
return False
def check_diversity(group, L):
"""check if group satisfy l-diversity
"""
SA_values = set()
for index in group:
str_value = list_to_str(gl_data[index][-1], cmp)
SA_values.add(str_value)
if len(SA_values) >= L:
return True
return False
def test_case_from_paper(self):
init_tree()
trans = [
["a1"],
["a1", "a2"],
["b1", "b2"],
["b1", "b2"],
["a1", "a2", "b2"],
["a1", "a2", "b2"],
["a1", "a2", "b1", "b2"],
]
result, _ = partition(ATT_TREE, trans, 2)
for i, t in enumerate(result[:]):
result[i] = list_to_str(t)
self.assertEqual(set(result), set(["A", "A", "a1;a2;B", "a1;a2;B", "a1;a2;B", "b1;b2", "b1;b2"]))
def PAA(att_tree, data, K=10, L=5):
"""Using Partition to anonymize SA (transaction) partition,
while applying Anatomize to separate QID and SA
"""
global gl_att_tree, gl_data
gl_att_tree = att_tree
gl_data = data
start_time = time.time()
tran_tree = {}
print "size of dataset %d" % len(gl_data)
result = []
trans = [t[-1] for t in gl_data]
trans_set = partition(att_tree, trans, K)
grouped_data = []
for ttemp in trans_set:
(index_list, tran_value) = ttemp
parent = list_to_str(tran_value, cmp)
try:
tran_tree[parent]
except:
tran_tree[parent] = set()
gtemp = []
for t in index_list:
temp = gl_data[t][:]
leaf = list_to_str(temp[-1], cmp)
tran_tree[parent].add(leaf)
temp[-1] = tran_value[:]
gtemp.append(temp)
grouped_data.append(gtemp)
print "Begin Anatomy"
grouped_result = anatomizer(grouped_data, L)
print("--- %s seconds ---" % (time.time()-start_time))
# transform data format (QID1,.., QIDn, SA set, GroupID, 1/|group size|, SA_list (dict) :original SA (str) sets with prob)
# 1/|group size|, original SA sets with prob (dict) will be used in evaluation
for index, group in enumerate(grouped_result):
length = len(group)
leaf_list = []
SA_list = {}
parent_list = {}
for t in group:
parent = list_to_str(t[-1], cmp)
gen_range = get_range(att_tree, t[-1])
leaf_list = leaf_list + list(tran_tree[parent])
parent_list[parent] = gen_range
# all transactions covered by this group
leaf_list = list(set(leaf_list))
# pdb.set_trace()
for temp in leaf_list:
for p in parent_list.keys():
if temp in tran_tree[p]:
try:
SA_list[temp] += parent_list[p]/length
except:
SA_list[temp] = parent_list[p]/length
# pdb.set_trace()
for t in group:
temp = t[:]
temp.append(index)
temp.append(1.0/length)
temp.append(SA_list)
result.append(temp)
return result
def APA(att_tree, data, K=10, L=5):
"""Using Partition to anonymize SA (transaction) partition,
while applying Anatomizer to separate QID and SA
"""
# Initialization
global gl_att_tree, gl_data
gl_att_tree = att_tree
gl_data = data
start_time = time.time()
result = []
suppress = []
tran_tree = {}
print "size of dataset %d" % len(gl_data)
# Begin Anatomy
print "Begin Anatomy"
anatomy_index = anatomizer(gl_data, L)
# Begin Partition
trans = [t[-1] for t in gl_data]
trans_set = partition(att_tree, trans, K)
for ttemp in trans_set:
(index_list, tran_value) = ttemp
parent = list_to_str(tran_value, cmp)
try:
tran_tree[parent]
except:
tran_tree[parent] = set()
for t in index_list:
leaf = list_to_str(gl_data[t][-1], cmp)
tran_tree[parent].add(leaf)
gl_data[t][-1] = tran_value[:]
# pdb.set_trace()
# Merge groups to achieve l-diversity
residue = []
grouped_index = []
for group in anatomy_index:
if check_diversity(group, L):
grouped_index.append(group[:])
else:
residue.append(group[:])
while len(residue) > 0:
g = residue.pop()
for index, group in enumerate(residue):
if mergeable(g, group, L):
g = g + group
grouped_index.append(g)
residue.pop(index)
break
else:
# add group element to random group, which alread satisfy l-diversity
if len(grouped_index) > 0:
seed = random.randrange(len(grouped_index))
grouped_index[seed] = grouped_index[seed] + g
else:
print "Error: group cannot satisfy l-diversity"
for index in g:
suppress.append(gl_data[index])
if _DEBUG:
print 'NO. of Suppress after Group Merge = %d' % len(suppress)
print 'NO. of groups = %d' % len(grouped_index)
grouped_result = []
for indexes in grouped_index:
gtemp = []
for index in indexes:
gtemp.append(gl_data[index])
grouped_result.append(gtemp)
print("--- %s seconds ---" % (time.time()-start_time))
# transform data format (QID1,.., QIDn, SA set, GroupID, 1/|group size|, SA_list (dict) :original SA (str) sets with prob)
# 1/|group size|, original SA sets with prob (dict) will be used in evaluation
for index, group in enumerate(grouped_result):
length = len(group)
leaf_list = []
SA_list = {}
parent_list = {}
for t in group:
parent = list_to_str(t[-1], cmp)
gen_range = get_range(att_tree, t[-1])
leaf_list = leaf_list + list(tran_tree[parent])
parent_list[parent] = gen_range
# all transactions covered by this group
leaf_list = list(set(leaf_list))
# pdb.set_trace()
for temp in leaf_list:
for p in parent_list.keys():
if temp in tran_tree[p]:
try:
SA_list[temp] += parent_list[p]/length
except:
SA_list[temp] = parent_list[p]/length
# pdb.set_trace()
for t in group:
temp = t[:]
temp.append(index)
temp.append(1.0/length)
temp.append(SA_list)
result.append(temp)
return result
def APA(att_tree, data, K=10, L=5):
"""Using Partition to anonymize SA (transaction) partition,
while applying Anatomizer to separate QID and SA
"""
# Initialization
global gl_att_tree, gl_data
gl_att_tree = att_tree
gl_data = data
start_time = time.time()
result = []
suppress = []
tran_tree = {}
print "size of dataset %d" % len(gl_data)
# Begin Anatomy
print "Begin Anatomy"
anatomy_index = anatomizer(gl_data, L)
# Begin Partition
trans = [t[-1] for t in gl_data]
trans_set = partition(att_tree, trans, K)
for ttemp in trans_set:
(index_list, tran_value) = ttemp
parent = list_to_str(tran_value, cmp)
try:
tran_tree[parent]
except:
tran_tree[parent] = set()
for t in index_list:
leaf = list_to_str(gl_data[t][-1], cmp)
tran_tree[parent].add(leaf)
gl_data[t][-1] = tran_value[:]
# pdb.set_trace()
# Merge groups to achieve l-diversity
residue = []
grouped_index = []
for group in anatomy_index:
if check_diversity(group, L):
grouped_index.append(group[:])
else:
residue.append(group[:])
while len(residue) > 0:
g = residue.pop()
for index, group in enumerate(residue):
if mergeable(g, group, L):
g = g + group
grouped_index.append(g)
residue.pop(index)
break
else:
# add group element to random group, which alread satisfy l-diversity
if len(grouped_index) > 0:
seed = random.randrange(len(grouped_index))
grouped_index[seed] = grouped_index[seed] + g
else:
print "Error: group cannot satisfy l-diversity"
for index in g:
suppress.append(gl_data[index])
if _DEBUG:
print 'NO. of Suppress after Group Merge = %d' % len(suppress)
print 'NO. of groups = %d' % len(grouped_index)
grouped_result = []
for indexes in grouped_index:
gtemp = []
for index in indexes:
gtemp.append(gl_data[index])
grouped_result.append(gtemp)
print("--- %s seconds ---" % (time.time() - start_time))
# transform data format (QID1,.., QIDn, SA set, GroupID, 1/|group size|, SA_list (dict) :original SA (str) sets with prob)
# 1/|group size|, original SA sets with prob (dict) will be used in evaluation
for index, group in enumerate(grouped_result):
length = len(group)
leaf_list = []
SA_list = {}
parent_list = {}
for t in group:
parent = list_to_str(t[-1], cmp)
gen_range = get_range(att_tree, t[-1])
leaf_list = leaf_list + list(tran_tree[parent])
parent_list[parent] = gen_range
# all transactions covered by this group
leaf_list = list(set(leaf_list))
# pdb.set_trace()
for temp in leaf_list:
for p in parent_list.keys():
if temp in tran_tree[p]:
try:
SA_list[temp] += parent_list[p] / length
except:
SA_list[temp] = parent_list[p] / length
# pdb.set_trace()
for t in group:
temp = t[:]
temp.append(index)
temp.append(1.0 / length)
temp.append(SA_list)
result.append(temp)
return result
