def method2format(output, _format="png", mx=None, raw=False):
"""
Export method to a specific file format
@param output : output filename
@param _format : format type (png, jpg ...) (default : png)
@param mx : specify the MethodAnalysis object
@param raw : use directly a dot raw buffer
"""
try:
import pydot
except ImportError:
error("module pydot not found")
buff = "digraph code {\n"
buff += "graph [bgcolor=white];\n"
buff += "node [color=lightgray, style=filled shape=box fontname=\"Courier\" fontsize=\"8\"];\n"
if raw == False:
buff += method2dot(mx)
else:
buff += raw
buff += "}"
d = pydot.graph_from_dot_data(buff)
if d:
getattr(d, "write_" + _format)(output)
def method2format( output, _format="png", mx = None, raw = False ) :
"""
Export method to a specific file format
@param output : output filename
@param _format : format type (png, jpg ...) (default : png)
@param mx : specify the MethodAnalysis object
@param raw : use directly a dot raw buffer
"""
try :
import pydot
except ImportError :
error("module pydot not found")
buff = "digraph code {\n"
buff += "graph [bgcolor=white];\n"
buff += "node [color=lightgray, style=filled shape=box fontname=\"Courier\" fontsize=\"8\"];\n"
if raw == False :
buff += method2dot( mx )
else :
buff += raw
buff += "}"
d = pydot.graph_from_dot_data( buff )
if d :
getattr(d, "write_" + _format)( output )
def saveSession(self, filepath):
"""Save androguard session."""
try:
session_module.Save(self.session, filepath)
except RuntimeError as e:
androconf.error(str(e))
os.remove(filepath)
androconf.warning("Session not saved")
def saveSession(self, filepath):
'''Save androguard session.'''
try:
session_module.Save(self.session, filepath)
except RuntimeError as e:
androconf.error(str(e))
os.remove(filepath)
androconf.warning("Session not saved")
def saveSession(self, path):
'''Save androguard session.'''
try:
self.session.save(path)
except RuntimeError as e:
androconf.error(str(e))
# http://stackoverflow.com/questions/2134706/hitting-maximum-recursion-depth-using-pythons-pickle-cpickle
androconf.error("Try increasing sys.recursionlimit")
os.remove(path)
androconf.warning("Session not saved")
def saveSession(self, path):
'''Save androguard session.'''
try:
self.session.save(path)
except RuntimeError as e:
androconf.error(str(e))
# http://stackoverflow.com/questions/2134706/hitting-maximum-recursion-depth-using-pythons-pickle-cpickle
androconf.error("Try increasing sys.recursionlimit")
os.remove(path)
androconf.warning("Session not saved")
def __init__(self, _analysis):
self.__analysis = _analysis
try:
from networkx import DiGraph
from networkx import draw_graphviz, write_dot
except ImportError:
error("module networkx not found")
self.__G = DiGraph()
for m in self.__analysis.get_methods():
for bb in m.basic_blocks.get():
for trace in bb.stack_traces.get():
for mre in jvm.MATH_JVM_RE:
if mre[0].match(trace[2].get_name()):
for i in trace[3].gets():
self._add(str(i))
def __init__(self, _analysis) :
self.__analysis = _analysis
try :
from networkx import DiGraph
from networkx import draw_graphviz, write_dot
except ImportError :
error("module networkx not found")
self.__G = DiGraph()
for m in self.__analysis.get_methods() :
for bb in m.basic_blocks.get() :
for trace in bb.stack_traces.get() :
for mre in jvm.MATH_JVM_RE :
if mre[0].match( trace[2].get_name() ) :
for i in trace[3].gets() :
self._add( str(i) )
def method2format(output, _format="png", mx=None, raw=None):
"""
Export method to a specific file format
@param output : output filename
@param _format : format type (png, jpg ...) (default : png)
@param mx : specify the MethodAnalysis object
@param raw : use directly a dot raw buffer if None
"""
try:
import pydot
except ImportError:
error("module pydot not found")
buff = "digraph {\n"
buff += "graph [rankdir=TB]\n"
buff += "node [shape=plaintext]\n"
if raw:
data = raw
else:
data = method2dot(mx)
# subgraphs cluster
buff += "subgraph cluster_" + \
hashlib.md5(output).hexdigest() + " {\nlabel=\"%s\"\n" % data['name']
buff += data['nodes']
buff += "}\n"
# subgraphs edges
buff += data['edges']
buff += "}\n"
d = pydot.graph_from_dot_data(buff)
if d:
getattr(d, "write_" + _format.lower())(output)
def method2format(output, _format="png", mx=None, raw=None):
"""
Export method to a specific file format
@param output : output filename
@param _format : format type (png, jpg ...) (default : png)
@param mx : specify the MethodAnalysis object
@param raw : use directly a dot raw buffer if None
"""
try:
import pydot
except ImportError:
error("module pydot not found")
buff = "digraph {\n"
buff += "graph [rankdir=TB]\n"
buff += "node [shape=plaintext]\n"
if raw:
data = raw
else:
data = method2dot(mx)
# subgraphs cluster
buff += "subgraph cluster_" + hashlib.md5(output).hexdigest(
) + " {\nlabel=\"%s\"\n" % data['name']
buff += data['nodes']
buff += "}\n"
# subgraphs edges
buff += data['edges']
buff += "}\n"
d = pydot.graph_from_dot_data(buff)
if d:
getattr(d, "write_" + _format.lower())(output)
def create_system_method_one_score() :
try :
import fuzzy
except ImportError :
error("please install pyfuzzy to use this module !")
import fuzzy.System
import fuzzy.InputVariable
import fuzzy.fuzzify.Plain
import fuzzy.OutputVariable
import fuzzy.defuzzify.COGS
import fuzzy.set.Polygon
import fuzzy.set.Singleton
import fuzzy.set.Triangle
import fuzzy.Adjective
import fuzzy.operator.Input
import fuzzy.operator.Compound
import fuzzy.norm.Min
import fuzzy.norm.Max
import fuzzy.Rule
system = fuzzy.System.System()
input_Length_MS = fuzzy.InputVariable.InputVariable(fuzzify=fuzzy.fuzzify.Plain.Plain())
input_AndroidEntropy_MS = fuzzy.InputVariable.InputVariable(fuzzify=fuzzy.fuzzify.Plain.Plain())
input_JavaEntropy_MS = fuzzy.InputVariable.InputVariable(fuzzify=fuzzy.fuzzify.Plain.Plain())
input_Permissions_MS = fuzzy.InputVariable.InputVariable(fuzzify=fuzzy.fuzzify.Plain.Plain())
# Input variables
# Length
system.variables["input_Length_MS"] = input_Length_MS
input_Length_MS.adjectives[LOW_SCORE] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(0.0, 1.0), (50.0, 1.0), (100.0, 0.0)]) )
input_Length_MS.adjectives[AVERAGE_SCORE] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(50.0, 0.0), (100.0, 1.0), (150.0, 1.0), (300.0, 0.0)]) )
input_Length_MS.adjectives[HIGH_SCORE] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(150.0, 0.0), (200.0, 1.0), (300.0, 1.0), (400.0, 0.0)]) )
input_Length_MS.adjectives[PERFECT_SCORE] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(350.0, 0.0), (400.0, 1.0), (500.0, 1.0)]) )
# Android Entropy
system.variables["input_AndroidEntropy_MS"] = input_AndroidEntropy_MS
input_AndroidEntropy_MS.adjectives[LOW_SCORE] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(0.0, 1.0), (2.0, 1.0), (4.0, 0.0)]) )
input_AndroidEntropy_MS.adjectives[HIGH_SCORE] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(3.0, 0.0), (4.0, 1.0), (30.0, 1.0)]) )
# Java Entropy
system.variables["input_JavaEntropy_MS"] = input_JavaEntropy_MS
input_JavaEntropy_MS.adjectives[LOW_SCORE] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(0.0, 1.0), (2.0, 1.0), (4.0, 0.0)]) )
input_JavaEntropy_MS.adjectives[HIGH_SCORE] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(3.0, 0.0), (4.0, 1.0), (30.0, 1.0)]) )
# Permissions
system.variables["input_Permissions_MS"] = input_Permissions_MS
input_Permissions_MS.adjectives[LOW_SCORE] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(0.0, 1.0), (3.0, 1.0), (4.0, 0.0)]) )
input_Permissions_MS.adjectives[AVERAGE_SCORE] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(3.0, 0.0), (4.0, 1.0), (8.0, 1.0), (9.0, 0.0)]) )
input_Permissions_MS.adjectives[HIGH_SCORE] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(8.0, 0.0), (10.0, 1.0), (12.0, 1.0), (13.0, 0.0)]) )
input_Permissions_MS.adjectives[PERFECT_SCORE] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(12.0, 0.0), (13.0, 1.0), (20.0, 1.0)]) )
# Output variables
output_method_score = fuzzy.OutputVariable.OutputVariable(
defuzzify=fuzzy.defuzzify.COGS.COGS(),
description="method one score",
min=0.0,max=100.0,
)
output_method_score.adjectives[NULL_METHOD_SCORE] = fuzzy.Adjective.Adjective(fuzzy.set.Singleton.Singleton(0.0))
output_method_score.adjectives[AVERAGE_METHOD_SCORE] = fuzzy.Adjective.Adjective(fuzzy.set.Singleton.Singleton(50.0))
output_method_score.adjectives[HIGH_METHOD_SCORE] = fuzzy.Adjective.Adjective(fuzzy.set.Singleton.Singleton(80.0))
output_method_score.adjectives[PERFECT_METHOD_SCORE] = fuzzy.Adjective.Adjective(fuzzy.set.Singleton.Singleton(100.0))
system.variables["output_method_one_score"] = output_method_score
add_system_rule(system, "android entropy null", fuzzy.Rule.Rule(
adjective=[system.variables["output_method_one_score"].adjectives[NULL_METHOD_SCORE]],
operator=fuzzy.operator.Input.Input( system.variables["input_AndroidEntropy_MS"].adjectives[LOW_SCORE] ))
)
add_system_rule(system, "java entropy null", fuzzy.Rule.Rule(
adjective=[system.variables["output_method_one_score"].adjectives[NULL_METHOD_SCORE]],
operator=fuzzy.operator.Input.Input( system.variables["input_JavaEntropy_MS"].adjectives[LOW_SCORE] ))
)
add_system_rule(system, "permissions null", fuzzy.Rule.Rule(
adjective=[system.variables["output_method_one_score"].adjectives[NULL_METHOD_SCORE]],
operator=fuzzy.operator.Input.Input( system.variables["input_Permissions_MS"].adjectives[LOW_SCORE] ))
)
add_system_rule(system, "permissions average", fuzzy.Rule.Rule(
adjective=[system.variables["output_method_one_score"].adjectives[AVERAGE_METHOD_SCORE]],
operator=fuzzy.operator.Input.Input( system.variables["input_Permissions_MS"].adjectives[AVERAGE_SCORE] ))
)
add_system_rule(system, "permissions high", fuzzy.Rule.Rule(
adjective=[system.variables["output_method_one_score"].adjectives[HIGH_METHOD_SCORE]],
operator=fuzzy.operator.Input.Input( system.variables["input_Permissions_MS"].adjectives[HIGH_SCORE] ))
)
add_system_rule(system, "permissions perfect", fuzzy.Rule.Rule(
adjective=[system.variables["output_method_one_score"].adjectives[PERFECT_METHOD_SCORE]],
operator=fuzzy.operator.Input.Input( system.variables["input_Permissions_MS"].adjectives[PERFECT_SCORE] ))
)
add_system_rule(system, "length permissions perfect", fuzzy.Rule.Rule(
adjective=[system.variables["output_method_one_score"].adjectives[PERFECT_METHOD_SCORE]],
operator=fuzzy.operator.Compound.Compound(
fuzzy.norm.Min.Min(),
fuzzy.operator.Input.Input( system.variables["input_Length_MS"].adjectives[PERFECT_SCORE] ),
fuzzy.operator.Input.Input( system.variables["input_Permissions_MS"].adjectives[PERFECT_SCORE] ) )
)
)
add_system_rule(system, "length AndroidEntropy perfect", fuzzy.Rule.Rule(
adjective=[system.variables["output_method_one_score"].adjectives[HIGH_METHOD_SCORE]],
operator=fuzzy.operator.Compound.Compound(
fuzzy.norm.Min.Min(),
fuzzy.operator.Input.Input( system.variables["input_Length_MS"].adjectives[PERFECT_SCORE] ),
fuzzy.operator.Input.Input( system.variables["input_AndroidEntropy_MS"].adjectives[HIGH_SCORE] ) )
)
)
add_system_rule(system, "length JavaEntropy perfect", fuzzy.Rule.Rule(
adjective=[system.variables["output_method_one_score"].adjectives[HIGH_METHOD_SCORE]],
operator=fuzzy.operator.Compound.Compound(
fuzzy.norm.Min.Min(),
fuzzy.operator.Input.Input( system.variables["input_Length_MS"].adjectives[PERFECT_SCORE] ),
fuzzy.operator.Input.Input( system.variables["input_JavaEntropy_MS"].adjectives[HIGH_SCORE] ) )
)
)
return system
def create_system_risk() :
try :
import fuzzy
except ImportError :
error("please install pyfuzzy to use this module !")
import fuzzy.System
import fuzzy.InputVariable
import fuzzy.fuzzify.Plain
import fuzzy.OutputVariable
import fuzzy.defuzzify.COGS
import fuzzy.defuzzify.COG
import fuzzy.defuzzify.MaxRight
import fuzzy.defuzzify.MaxLeft
import fuzzy.defuzzify.LM
import fuzzy.set.Polygon
import fuzzy.set.Singleton
import fuzzy.set.Triangle
import fuzzy.Adjective
import fuzzy.operator.Input
import fuzzy.operator.Compound
import fuzzy.norm.Min
import fuzzy.norm.Max
import fuzzy.Rule
import fuzzy.defuzzify.Dict
system = fuzzy.System.System()
input_Dangerous_Risk = fuzzy.InputVariable.InputVariable(fuzzify=fuzzy.fuzzify.Plain.Plain())
input_Money_Risk = fuzzy.InputVariable.InputVariable(fuzzify=fuzzy.fuzzify.Plain.Plain())
input_Privacy_Risk = fuzzy.InputVariable.InputVariable(fuzzify=fuzzy.fuzzify.Plain.Plain())
input_Binary_Risk = fuzzy.InputVariable.InputVariable(fuzzify=fuzzy.fuzzify.Plain.Plain())
input_Internet_Risk = fuzzy.InputVariable.InputVariable(fuzzify=fuzzy.fuzzify.Plain.Plain())
input_Dynamic_Risk = fuzzy.InputVariable.InputVariable(fuzzify=fuzzy.fuzzify.Plain.Plain())
# Input variables
# Dangerous Risk
system.variables["input_Dangerous_Risk"] = input_Dangerous_Risk
input_Dangerous_Risk.adjectives[LOW_RISK] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(0.0, 1.0), (8.0, 1.0), (12.0, 0.0)]) )
input_Dangerous_Risk.adjectives[AVERAGE_RISK] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(8.0, 0.0), (50.0, 1.0), (60.0, 0.0)]) )
input_Dangerous_Risk.adjectives[HIGH_RISK] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(50.0, 0.0), (85.0, 1.0), (95.0, 0.0)]) )
input_Dangerous_Risk.adjectives[UNACCEPTABLE_RISK] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(85.0, 0.0), (100.0, 1.0)]) )
# Money Risk
system.variables["input_Money_Risk"] = input_Money_Risk
input_Money_Risk.adjectives[LOW_RISK] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(0.0, 1.0), (2.0, 1.0), (3.0, 0.0)]) )
input_Money_Risk.adjectives[UNACCEPTABLE_RISK] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(4.0, 0.0), (5.0, 1.0), (30.0, 1.0)]) )
# Privacy Risk
system.variables["input_Privacy_Risk"] = input_Privacy_Risk
input_Privacy_Risk.adjectives[LOW_RISK] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(0.0, 1.0), (6.0, 1.0), (10.0, 0.0)]) )
input_Privacy_Risk.adjectives[HIGH_RISK] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(6.0, 0.0), (10.0, 1.0), (20.0, 0.0)]) )
input_Privacy_Risk.adjectives[UNACCEPTABLE_RISK] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(15.0, 0.0), (20.0, 1.0), (30.0, 1.0)]) )
# Binary Risk
system.variables["input_Binary_Risk"] = input_Binary_Risk
input_Binary_Risk.adjectives[LOW_RISK] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(0.0, 1.0), (6.0, 1.0), (10.0, 0.0)]) )
input_Binary_Risk.adjectives[AVERAGE_RISK] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(6.0, 0.0), (10.0, 1.0), (15.0, 0.0)]) )
input_Binary_Risk.adjectives[HIGH_RISK] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(10.0, 0.0), (20.0, 1.0), (24.0, 0.0)]) )
input_Binary_Risk.adjectives[UNACCEPTABLE_RISK] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(23.0, 0.0), (30.0, 1.0), (40.0, 1.0)]) )
# Internet Risk
system.variables["input_Internet_Risk"] = input_Internet_Risk
#input_Internet_Risk.adjectives[LOW_RISK] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(0.0, 1.0), (1.0, 1.0)]) )
input_Internet_Risk.adjectives[HIGH_RISK] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(1.0, 0.0), (5.0, 1.0), (30.0, 1.0)]) )
# Dynamic Risk
system.variables["input_Dynamic_Risk"] = input_Dynamic_Risk
input_Dynamic_Risk.adjectives[LOW_RISK] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(0.0, 1.0), (2.0, 1.0), (3.0, 0.0)]))
input_Dynamic_Risk.adjectives[UNACCEPTABLE_RISK] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(4.0, 0.0), (5.0, 1.0), (50.0, 1.0)]) )
# Output variables
output_malware_risk = fuzzy.OutputVariable.OutputVariable(
defuzzify=fuzzy.defuzzify.COGS.COGS(),
description="malware risk",
min=0.0,max=100.0,
)
#output_malware_risk = fuzzy.OutputVariable.OutputVariable(defuzzify=fuzzy.defuzzify.Dict.Dict())
output_malware_risk.adjectives[NULL_MALWARE_RISK] = fuzzy.Adjective.Adjective(fuzzy.set.Singleton.Singleton(0.0))
output_malware_risk.adjectives[AVERAGE_MALWARE_RISK] = fuzzy.Adjective.Adjective(fuzzy.set.Singleton.Singleton(30.0))
output_malware_risk.adjectives[HIGH_MALWARE_RISK] = fuzzy.Adjective.Adjective(fuzzy.set.Singleton.Singleton(60.0))
output_malware_risk.adjectives[UNACCEPTABLE_MALWARE_RISK] = fuzzy.Adjective.Adjective(fuzzy.set.Singleton.Singleton(100.0))
system.variables["output_malware_risk"] = output_malware_risk
# Rules
#RULE 0: DYNAMIC
add_system_rule(system, "r0", fuzzy.Rule.Rule(
adjective=[system.variables["output_malware_risk"].adjectives[NULL_MALWARE_RISK]],
operator=fuzzy.operator.Input.Input( system.variables["input_Dynamic_Risk"].adjectives[LOW_RISK] )
)
)
add_system_rule(system, "r0a", fuzzy.Rule.Rule(
adjective=[system.variables["output_malware_risk"].adjectives[UNACCEPTABLE_MALWARE_RISK]],
operator=fuzzy.operator.Input.Input( system.variables["input_Dynamic_Risk"].adjectives[UNACCEPTABLE_RISK] )
)
)
#RULE 1: MONEY
add_system_rule(system, "r1", fuzzy.Rule.Rule(
adjective=[system.variables["output_malware_risk"].adjectives[NULL_MALWARE_RISK]],
operator=fuzzy.operator.Input.Input( system.variables["input_Money_Risk"].adjectives[LOW_RISK] )
)
)
add_system_rule(system, "r1a", fuzzy.Rule.Rule(
adjective=[system.variables["output_malware_risk"].adjectives[UNACCEPTABLE_MALWARE_RISK]],
operator=fuzzy.operator.Input.Input( system.variables["input_Money_Risk"].adjectives[UNACCEPTABLE_RISK] )
)
)
#RULE 3 : BINARY
add_system_rule(system, "r3", fuzzy.Rule.Rule(
adjective=[system.variables["output_malware_risk"].adjectives[AVERAGE_MALWARE_RISK]],
operator=fuzzy.operator.Input.Input( system.variables["input_Binary_Risk"].adjectives[AVERAGE_RISK] )
)
)
add_system_rule(system, "r3a", fuzzy.Rule.Rule(
adjective=[system.variables["output_malware_risk"].adjectives[HIGH_RISK]],
operator=fuzzy.operator.Input.Input( system.variables["input_Binary_Risk"].adjectives[HIGH_RISK] )
)
)
add_system_rule(system, "r3b", fuzzy.Rule.Rule(
adjective=[system.variables["output_malware_risk"].adjectives[UNACCEPTABLE_MALWARE_RISK]],
operator=fuzzy.operator.Input.Input( system.variables["input_Binary_Risk"].adjectives[UNACCEPTABLE_RISK] )
)
)
# PRIVACY + INTERNET
add_system_rule(system, "r5", fuzzy.Rule.Rule(
adjective=[system.variables["output_malware_risk"].adjectives[HIGH_MALWARE_RISK]],
operator=fuzzy.operator.Compound.Compound(
fuzzy.norm.Min.Min(),
fuzzy.operator.Input.Input( system.variables["input_Privacy_Risk"].adjectives[LOW_RISK] ),
fuzzy.operator.Input.Input( system.variables["input_Internet_Risk"].adjectives[HIGH_RISK] ) )
)
)
add_system_rule(system, "r5a", fuzzy.Rule.Rule(
adjective=[system.variables["output_malware_risk"].adjectives[UNACCEPTABLE_MALWARE_RISK]],
operator=fuzzy.operator.Compound.Compound(
fuzzy.norm.Min.Min(),
fuzzy.operator.Input.Input( system.variables["input_Privacy_Risk"].adjectives[HIGH_RISK] ),
fuzzy.operator.Input.Input( system.variables["input_Internet_Risk"].adjectives[HIGH_RISK] ) )
)
)
add_system_rule(system, "r6", fuzzy.Rule.Rule(
adjective=[system.variables["output_malware_risk"].adjectives[HIGH_RISK]],
operator=fuzzy.operator.Input.Input( system.variables["input_Dangerous_Risk"].adjectives[HIGH_RISK] )
)
)
add_system_rule(system, "r6a", fuzzy.Rule.Rule(
adjective=[system.variables["output_malware_risk"].adjectives[UNACCEPTABLE_RISK]],
operator=fuzzy.operator.Input.Input( system.variables["input_Dangerous_Risk"].adjectives[UNACCEPTABLE_RISK] )
)
)
return system
def create_system_method_one_score():
try:
import fuzzy
except ImportError:
error("please install pyfuzzy to use this module !")
import fuzzy.System
import fuzzy.InputVariable
import fuzzy.fuzzify.Plain
import fuzzy.OutputVariable
import fuzzy.defuzzify.COGS
import fuzzy.set.Polygon
import fuzzy.set.Singleton
import fuzzy.set.Triangle
import fuzzy.Adjective
import fuzzy.operator.Input
import fuzzy.operator.Compound
import fuzzy.norm.Min
import fuzzy.norm.Max
import fuzzy.Rule
system = fuzzy.System.System()
input_Length_MS = fuzzy.InputVariable.InputVariable(
fuzzify=fuzzy.fuzzify.Plain.Plain())
input_AndroidEntropy_MS = fuzzy.InputVariable.InputVariable(
fuzzify=fuzzy.fuzzify.Plain.Plain())
input_JavaEntropy_MS = fuzzy.InputVariable.InputVariable(
fuzzify=fuzzy.fuzzify.Plain.Plain())
input_Permissions_MS = fuzzy.InputVariable.InputVariable(
fuzzify=fuzzy.fuzzify.Plain.Plain())
# Input variables
# Length
system.variables["input_Length_MS"] = input_Length_MS
input_Length_MS.adjectives[LOW_SCORE] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(0.0, 1.0), (50.0, 1.0), (100.0, 0.0)]))
input_Length_MS.adjectives[AVERAGE_SCORE] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(50.0, 0.0), (100.0, 1.0), (150.0, 1.0),
(300.0, 0.0)]))
input_Length_MS.adjectives[HIGH_SCORE] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(150.0, 0.0), (200.0, 1.0), (300.0, 1.0),
(400.0, 0.0)]))
input_Length_MS.adjectives[PERFECT_SCORE] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(350.0, 0.0), (400.0, 1.0), (500.0, 1.0)]))
# Android Entropy
system.variables["input_AndroidEntropy_MS"] = input_AndroidEntropy_MS
input_AndroidEntropy_MS.adjectives[LOW_SCORE] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(0.0, 1.0), (2.0, 1.0), (4.0, 0.0)]))
input_AndroidEntropy_MS.adjectives[HIGH_SCORE] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(3.0, 0.0), (4.0, 1.0), (30.0, 1.0)]))
# Java Entropy
system.variables["input_JavaEntropy_MS"] = input_JavaEntropy_MS
input_JavaEntropy_MS.adjectives[LOW_SCORE] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(0.0, 1.0), (2.0, 1.0), (4.0, 0.0)]))
input_JavaEntropy_MS.adjectives[HIGH_SCORE] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(3.0, 0.0), (4.0, 1.0), (30.0, 1.0)]))
# Permissions
system.variables["input_Permissions_MS"] = input_Permissions_MS
input_Permissions_MS.adjectives[LOW_SCORE] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(0.0, 1.0), (3.0, 1.0), (4.0, 0.0)]))
input_Permissions_MS.adjectives[AVERAGE_SCORE] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(3.0, 0.0), (4.0, 1.0), (8.0, 1.0),
(9.0, 0.0)]))
input_Permissions_MS.adjectives[HIGH_SCORE] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(8.0, 0.0), (10.0, 1.0), (12.0, 1.0),
(13.0, 0.0)]))
input_Permissions_MS.adjectives[PERFECT_SCORE] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(12.0, 0.0), (13.0, 1.0), (20.0, 1.0)]))
# Output variables
output_method_score = fuzzy.OutputVariable.OutputVariable(
defuzzify=fuzzy.defuzzify.COGS.COGS(),
description="method one score",
min=0.0,
max=100.0,
)
output_method_score.adjectives[
NULL_METHOD_SCORE] = fuzzy.Adjective.Adjective(
fuzzy.set.Singleton.Singleton(0.0))
output_method_score.adjectives[
AVERAGE_METHOD_SCORE] = fuzzy.Adjective.Adjective(
fuzzy.set.Singleton.Singleton(50.0))
output_method_score.adjectives[
HIGH_METHOD_SCORE] = fuzzy.Adjective.Adjective(
fuzzy.set.Singleton.Singleton(80.0))
output_method_score.adjectives[
PERFECT_METHOD_SCORE] = fuzzy.Adjective.Adjective(
fuzzy.set.Singleton.Singleton(100.0))
system.variables["output_method_one_score"] = output_method_score
add_system_rule(
system, "android entropy null",
fuzzy.Rule.Rule(adjective=[
system.variables["output_method_one_score"].
adjectives[NULL_METHOD_SCORE]
],
operator=fuzzy.operator.Input.Input(
system.variables["input_AndroidEntropy_MS"].
adjectives[LOW_SCORE])))
add_system_rule(
system, "java entropy null",
fuzzy.Rule.Rule(adjective=[
system.variables["output_method_one_score"].
adjectives[NULL_METHOD_SCORE]
],
operator=fuzzy.operator.Input.Input(
system.variables["input_JavaEntropy_MS"].
adjectives[LOW_SCORE])))
add_system_rule(
system, "permissions null",
fuzzy.Rule.Rule(adjective=[
system.variables["output_method_one_score"].
adjectives[NULL_METHOD_SCORE]
],
operator=fuzzy.operator.Input.Input(
system.variables["input_Permissions_MS"].
adjectives[LOW_SCORE])))
add_system_rule(
system, "permissions average",
fuzzy.Rule.Rule(adjective=[
system.variables["output_method_one_score"].
adjectives[AVERAGE_METHOD_SCORE]
],
operator=fuzzy.operator.Input.Input(
system.variables["input_Permissions_MS"].
adjectives[AVERAGE_SCORE])))
add_system_rule(
system, "permissions high",
fuzzy.Rule.Rule(adjective=[
system.variables["output_method_one_score"].
adjectives[HIGH_METHOD_SCORE]
],
operator=fuzzy.operator.Input.Input(
system.variables["input_Permissions_MS"].
adjectives[HIGH_SCORE])))
add_system_rule(
system, "permissions perfect",
fuzzy.Rule.Rule(adjective=[
system.variables["output_method_one_score"].
adjectives[PERFECT_METHOD_SCORE]
],
operator=fuzzy.operator.Input.Input(
system.variables["input_Permissions_MS"].
adjectives[PERFECT_SCORE])))
add_system_rule(
system, "length permissions perfect",
fuzzy.Rule.Rule(
adjective=[
system.variables["output_method_one_score"].
adjectives[PERFECT_METHOD_SCORE]
],
operator=fuzzy.operator.Compound.Compound(
fuzzy.norm.Min.Min(),
fuzzy.operator.Input.Input(system.variables["input_Length_MS"].
adjectives[PERFECT_SCORE]),
fuzzy.operator.Input.Input(
system.variables["input_Permissions_MS"].
adjectives[PERFECT_SCORE]))))
add_system_rule(
system, "length AndroidEntropy perfect",
fuzzy.Rule.Rule(
adjective=[
system.variables["output_method_one_score"].
adjectives[HIGH_METHOD_SCORE]
],
operator=fuzzy.operator.Compound.Compound(
fuzzy.norm.Min.Min(),
fuzzy.operator.Input.Input(system.variables["input_Length_MS"].
adjectives[PERFECT_SCORE]),
fuzzy.operator.Input.Input(
system.variables["input_AndroidEntropy_MS"].
adjectives[HIGH_SCORE]))))
add_system_rule(
system, "length JavaEntropy perfect",
fuzzy.Rule.Rule(
adjective=[
system.variables["output_method_one_score"].
adjectives[HIGH_METHOD_SCORE]
],
operator=fuzzy.operator.Compound.Compound(
fuzzy.norm.Min.Min(),
fuzzy.operator.Input.Input(system.variables["input_Length_MS"].
adjectives[PERFECT_SCORE]),
fuzzy.operator.Input.Input(
system.variables["input_JavaEntropy_MS"].
adjectives[HIGH_SCORE]))))
return system
def create_system_risk():
try:
import fuzzy
except ImportError:
error("please install pyfuzzy to use this module !")
import fuzzy.System
import fuzzy.InputVariable
import fuzzy.fuzzify.Plain
import fuzzy.OutputVariable
import fuzzy.defuzzify.COGS
import fuzzy.defuzzify.COG
import fuzzy.defuzzify.MaxRight
import fuzzy.defuzzify.MaxLeft
import fuzzy.defuzzify.LM
import fuzzy.set.Polygon
import fuzzy.set.Singleton
import fuzzy.set.Triangle
import fuzzy.Adjective
import fuzzy.operator.Input
import fuzzy.operator.Compound
import fuzzy.norm.Min
import fuzzy.norm.Max
import fuzzy.Rule
import fuzzy.defuzzify.Dict
system = fuzzy.System.System()
input_Dangerous_Risk = fuzzy.InputVariable.InputVariable(
fuzzify=fuzzy.fuzzify.Plain.Plain())
input_Money_Risk = fuzzy.InputVariable.InputVariable(
fuzzify=fuzzy.fuzzify.Plain.Plain())
input_Privacy_Risk = fuzzy.InputVariable.InputVariable(
fuzzify=fuzzy.fuzzify.Plain.Plain())
input_Binary_Risk = fuzzy.InputVariable.InputVariable(
fuzzify=fuzzy.fuzzify.Plain.Plain())
input_Internet_Risk = fuzzy.InputVariable.InputVariable(
fuzzify=fuzzy.fuzzify.Plain.Plain())
input_Dynamic_Risk = fuzzy.InputVariable.InputVariable(
fuzzify=fuzzy.fuzzify.Plain.Plain())
# Input variables
# Dangerous Risk
system.variables["input_Dangerous_Risk"] = input_Dangerous_Risk
input_Dangerous_Risk.adjectives[LOW_RISK] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(0.0, 1.0), (8.0, 1.0), (12.0, 0.0)]))
input_Dangerous_Risk.adjectives[AVERAGE_RISK] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(8.0, 0.0), (50.0, 1.0), (60.0, 0.0)]))
input_Dangerous_Risk.adjectives[HIGH_RISK] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(50.0, 0.0), (85.0, 1.0), (95.0, 0.0)]))
input_Dangerous_Risk.adjectives[
UNACCEPTABLE_RISK] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(85.0, 0.0), (100.0, 1.0)]))
# Money Risk
system.variables["input_Money_Risk"] = input_Money_Risk
input_Money_Risk.adjectives[LOW_RISK] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(0.0, 1.0), (2.0, 1.0), (3.0, 0.0)]))
input_Money_Risk.adjectives[UNACCEPTABLE_RISK] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(4.0, 0.0), (5.0, 1.0), (30.0, 1.0)]))
# Privacy Risk
system.variables["input_Privacy_Risk"] = input_Privacy_Risk
input_Privacy_Risk.adjectives[LOW_RISK] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(0.0, 1.0), (6.0, 1.0), (10.0, 0.0)]))
input_Privacy_Risk.adjectives[HIGH_RISK] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(6.0, 0.0), (10.0, 1.0), (20.0, 0.0)]))
input_Privacy_Risk.adjectives[
UNACCEPTABLE_RISK] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(15.0, 0.0), (20.0, 1.0), (30.0, 1.0)]))
# Binary Risk
system.variables["input_Binary_Risk"] = input_Binary_Risk
input_Binary_Risk.adjectives[LOW_RISK] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(0.0, 1.0), (6.0, 1.0), (10.0, 0.0)]))
input_Binary_Risk.adjectives[AVERAGE_RISK] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(6.0, 0.0), (10.0, 1.0), (15.0, 0.0)]))
input_Binary_Risk.adjectives[HIGH_RISK] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(10.0, 0.0), (20.0, 1.0), (24.0, 0.0)]))
input_Binary_Risk.adjectives[
UNACCEPTABLE_RISK] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(23.0, 0.0), (30.0, 1.0), (40.0, 1.0)]))
# Internet Risk
system.variables["input_Internet_Risk"] = input_Internet_Risk
#input_Internet_Risk.adjectives[LOW_RISK] = fuzzy.Adjective.Adjective( fuzzy.set.Polygon.Polygon([(0.0, 1.0), (1.0, 1.0)]) )
input_Internet_Risk.adjectives[HIGH_RISK] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(1.0, 0.0), (5.0, 1.0), (30.0, 1.0)]))
# Dynamic Risk
system.variables["input_Dynamic_Risk"] = input_Dynamic_Risk
input_Dynamic_Risk.adjectives[LOW_RISK] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(0.0, 1.0), (2.0, 1.0), (3.0, 0.0)]))
input_Dynamic_Risk.adjectives[
UNACCEPTABLE_RISK] = fuzzy.Adjective.Adjective(
fuzzy.set.Polygon.Polygon([(4.0, 0.0), (5.0, 1.0), (50.0, 1.0)]))
# Output variables
output_malware_risk = fuzzy.OutputVariable.OutputVariable(
defuzzify=fuzzy.defuzzify.COGS.COGS(),
description="malware risk",
min=0.0,
max=100.0,
)
#output_malware_risk = fuzzy.OutputVariable.OutputVariable(defuzzify=fuzzy.defuzzify.Dict.Dict())
output_malware_risk.adjectives[
NULL_MALWARE_RISK] = fuzzy.Adjective.Adjective(
fuzzy.set.Singleton.Singleton(0.0))
output_malware_risk.adjectives[
AVERAGE_MALWARE_RISK] = fuzzy.Adjective.Adjective(
fuzzy.set.Singleton.Singleton(30.0))
output_malware_risk.adjectives[
HIGH_MALWARE_RISK] = fuzzy.Adjective.Adjective(
fuzzy.set.Singleton.Singleton(60.0))
output_malware_risk.adjectives[
UNACCEPTABLE_MALWARE_RISK] = fuzzy.Adjective.Adjective(
fuzzy.set.Singleton.Singleton(100.0))
system.variables["output_malware_risk"] = output_malware_risk
# Rules
#RULE 0: DYNAMIC
add_system_rule(
system, "r0",
fuzzy.Rule.Rule(
adjective=[
system.variables["output_malware_risk"].
adjectives[NULL_MALWARE_RISK]
],
operator=fuzzy.operator.Input.Input(
system.variables["input_Dynamic_Risk"].adjectives[LOW_RISK])))
add_system_rule(
system, "r0a",
fuzzy.Rule.Rule(adjective=[
system.variables["output_malware_risk"].
adjectives[UNACCEPTABLE_MALWARE_RISK]
],
operator=fuzzy.operator.Input.Input(
system.variables["input_Dynamic_Risk"].
adjectives[UNACCEPTABLE_RISK])))
#RULE 1: MONEY
add_system_rule(
system, "r1",
fuzzy.Rule.Rule(
adjective=[
system.variables["output_malware_risk"].
adjectives[NULL_MALWARE_RISK]
],
operator=fuzzy.operator.Input.Input(
system.variables["input_Money_Risk"].adjectives[LOW_RISK])))
add_system_rule(
system, "r1a",
fuzzy.Rule.Rule(adjective=[
system.variables["output_malware_risk"].
adjectives[UNACCEPTABLE_MALWARE_RISK]
],
operator=fuzzy.operator.Input.Input(
system.variables["input_Money_Risk"].
adjectives[UNACCEPTABLE_RISK])))
#RULE 3 : BINARY
add_system_rule(
system, "r3",
fuzzy.Rule.Rule(adjective=[
system.variables["output_malware_risk"].
adjectives[AVERAGE_MALWARE_RISK]
],
operator=fuzzy.operator.Input.Input(
system.variables["input_Binary_Risk"].
adjectives[AVERAGE_RISK])))
add_system_rule(
system, "r3a",
fuzzy.Rule.Rule(
adjective=[
system.variables["output_malware_risk"].adjectives[HIGH_RISK]
],
operator=fuzzy.operator.Input.Input(
system.variables["input_Binary_Risk"].adjectives[HIGH_RISK])))
add_system_rule(
system, "r3b",
fuzzy.Rule.Rule(adjective=[
system.variables["output_malware_risk"].
adjectives[UNACCEPTABLE_MALWARE_RISK]
],
operator=fuzzy.operator.Input.Input(
system.variables["input_Binary_Risk"].
adjectives[UNACCEPTABLE_RISK])))
# PRIVACY + INTERNET
add_system_rule(
system, "r5",
fuzzy.Rule.Rule(adjective=[
system.variables["output_malware_risk"].
adjectives[HIGH_MALWARE_RISK]
],
operator=fuzzy.operator.Compound.Compound(
fuzzy.norm.Min.Min(),
fuzzy.operator.Input.Input(
system.variables["input_Privacy_Risk"].
adjectives[LOW_RISK]),
fuzzy.operator.Input.Input(
system.variables["input_Internet_Risk"].
adjectives[HIGH_RISK]))))
add_system_rule(
system, "r5a",
fuzzy.Rule.Rule(adjective=[
system.variables["output_malware_risk"].
adjectives[UNACCEPTABLE_MALWARE_RISK]
],
operator=fuzzy.operator.Compound.Compound(
fuzzy.norm.Min.Min(),
fuzzy.operator.Input.Input(
system.variables["input_Privacy_Risk"].
adjectives[HIGH_RISK]),
fuzzy.operator.Input.Input(
system.variables["input_Internet_Risk"].
adjectives[HIGH_RISK]))))
add_system_rule(
system, "r6",
fuzzy.Rule.Rule(adjective=[
system.variables["output_malware_risk"].adjectives[HIGH_RISK]
],
operator=fuzzy.operator.Input.Input(
system.variables["input_Dangerous_Risk"].
adjectives[HIGH_RISK])))
add_system_rule(
system, "r6a",
fuzzy.Rule.Rule(adjective=[
system.variables["output_malware_risk"].
adjectives[UNACCEPTABLE_RISK]
],
operator=fuzzy.operator.Input.Input(
system.variables["input_Dangerous_Risk"].
adjectives[UNACCEPTABLE_RISK])))
return system
