def changedatafield_attack_randomly(self, id, exist_time):
# attackType就是 case switch的根本决定因素
self.get_rule(" ")
self.refresh_place()
# document_name = "changedatafield_attack_test.csv"
# 从源数据中提取重放数据
begin_time = random.random()
begin_time = self.sourceDataSnippet.shape[0] * (2 / 3) * begin_time
begin_time = self.sourceDataSnippet.iloc[round(begin_time)]['time']
tmp_origin_data = self.sourceDataSnippet
end_time = exist_time + begin_time
for i in range(0, self.sourceDataSnippet.shape[0]):
if tmp_origin_data.iloc[i]['time'] >= begin_time and tmp_origin_data.iloc[i]['time'] <= end_time \
and tmp_origin_data.iloc[i]['can_id'] == id:
# 正式进入random环节
# 从前半部分直接random到后半部分
random_begin_bit = round(random.random() * 32)
length_of_bit = round(random.random() * 32)
random_end_bit = random_begin_bit + length_of_bit - 1
target_binary_bit = tmp_origin_data.iloc[i]['data_in_binary']
descriptionTmp = "before binary is " + target_binary_bit[
random_begin_bit:random_end_bit + 1]
target_binary_bit = list(target_binary_bit)
for love in range(random_begin_bit, random_end_bit + 1):
if (random.random() > 0.5): target_binary_bit[love] = '0'
else: target_binary_bit[love] = '1'
target_binary_bit = "".join(target_binary_bit)
descriptionTmp = descriptionTmp + " end binary is " + target_binary_bit[
random_begin_bit:random_end_bit + 1]
tmp_origin_data.loc[i, 'data_in_binary'] = target_binary_bit
tmp_origin_data.loc[i, 'data_in_hex'] = binary_str_to_hex_str(
target_binary_bit)
tmp_origin_data.loc[i, 'anormal'] = 5
hex_data = binary_str_to_hex_str(target_binary_bit)
for peace in range(0, 8):
tmp_origin_data.loc[i, 'data' +
str(peace)] = hex_data[2 * peace:2 *
peace + 2]
df3 = tmp_origin_data.iloc[i]
self.descriptionStruct.updateBasicInformation(
5, df3['can_id'], df3['time'], descriptionTmp,
df3['data_in_binary'])
# document_name = document_name + str(begin_time) + "_" + str(self.input_num) + ".csv"
document_name = self.document_name
if not os.path.exists(self.store_place):
os.mkdir(self.store_place)
tmp_origin_data.to_csv(self.store_place + "/" + document_name)
self.descriptionStruct.writeIntoCsv()
def writeIntoInnerStruct(self):
# 目标是返回一个dataframe，这个算是最重要的目标喽
# description其实是需要添加的数据？
dict_tmp = {}
dict_tmp['time'] = self.attackTime
dict_tmp['can_id'] = self.attackCanId
dict_tmp['attackType'] = self.attackType
dict_tmp['description'] = self.attackDescription
dict_tmp['data_in_hex'] = binary_str_to_hex_str(self.attackData)
dict_tmp['data_in_binary'] = self.attackData
dataSmallFrame = pd.DataFrame([dict_tmp])
self.dataFrameList = self.dataFrameList.append(dataSmallFrame)
def changedatafield_attack_sensro(self, id, exist_time, basicType):
# 不知道传感器的攻击可以选择到什么粒度，也不知道究竟可以制造哪种类型的攻击呢？
# 这几者都是暂时未知的
# 实际上，sensor的修改尺度是由attackType决定的，这是一个复杂的攻击配置变量
# 这二者的名字是一样的？但是攻击类型是否需要相同呢？暂时是未知的
self.get_rule(" ")
document_name = "changedatafield_attack_test.csv"
# 从源数据中提取重放数据
begin_time = random.random()
begin_time = self.sourceDataSnippet.shape[0] * (2 / 3) * begin_time
begin_time = self.sourceDataSnippet.iloc[round(begin_time)]['time']
tmp_origin_data = self.sourceDataSnippet
end_time = exist_time + begin_time
# 首先得到目标列表，存放的是Rule Class的类
tmp_rule_list = self.myRuleMap.getTargetCanIdRule(id)
final_rule_list = []
for item in tmp_rule_list:
if item.type_of_class == 1:
final_rule_list.append(item)
# 存储好我们接下来要操作的类即可，这种操作是某种程度 to some extent 合理的
# 这里就随便选几个规则，都改一改
for i in range(0, self.sourceDataSnippet.shape[0]):
if tmp_origin_data.iloc[i]['time'] >= begin_time and tmp_origin_data.iloc[i]['time'] <= end_time \
and tmp_origin_data.iloc[i]['can_id'] == id:
# 正式进入random环节
# 从前半部分直接random到后半部分
random_num = round(random.random() *
(len(final_rule_list) - 1)) # 取到这个值即可
ruleSingle = final_rule_list[random_num]
random_begin_bit = int(ruleSingle.begin_loc)
length_of_bit = int(ruleSingle.length)
random_end_bit = int(ruleSingle.end_loc)
val_range = ruleSingle.range
# 接下来对传感器的change是严格的，在某种程度上是严格的
target_binary_bit = tmp_origin_data.iloc[i]['data_in_binary']
descriptionTmp = "This is sensor value changing "
# 这里居然使用的是硬编码，将来是很有可能出现问题的
if basicType == 0:
descriptionTmp = descriptionTmp + " max-value change "
elif basicType == 1:
descriptionTmp = descriptionTmp + " min-value change "
elif basicType == 2:
descriptionTmp = descriptionTmp + " random-value change "
elif basicType == 3:
descriptionTmp = descriptionTmp + " apt advanced change "
descriptionTmp = "before binary is " + target_binary_bit[
random_begin_bit:random_end_bit + 1]
target_binary_bit = list(target_binary_bit)
# 以下是攻击的核心内容，根据不同的type，制造不同类型的攻击
# 想要实现多态攻击，这里的粒度还暂时不够
if basicType == 2: # 不一定在传感器取值范围
for love in range(random_begin_bit, random_end_bit + 1):
if (random.random() > 0.5):
target_binary_bit[love] = '0'
else:
target_binary_bit[love] = '1'
elif basicType == 0:
for love in range(random_begin_bit, random_end_bit + 1):
target_binary_bit[love] = '1'
elif basicType == 1:
for love in range(random_begin_bit, random_end_bit + 1):
target_binary_bit[love] = '0'
target_binary_bit = "".join(target_binary_bit)
descriptionTmp = descriptionTmp + " end binary is " + target_binary_bit[
random_begin_bit:random_end_bit + 1]
tmp_origin_data.loc[i, 'data_in_binary'] = target_binary_bit
tmp_origin_data.loc[i, 'data_in_hex'] = binary_str_to_hex_str(
target_binary_bit)
tmp_origin_data.loc[i, 'anormal'] = 7
hex_data = binary_str_to_hex_str(target_binary_bit)
for peace in range(0, 8):
tmp_origin_data.loc[i, 'data' +
str(peace)] = hex_data[2 * peace:2 *
peace + 2]
df3 = tmp_origin_data.iloc[i]
self.descriptionStruct.updateBasicInformation(
7, df3['can_id'], df3['time'], descriptionTmp,
df3['data_in_binary'])
self.store_place = "../src/attack_test"
document_name = document_name + str(begin_time) + "_" + str(
self.input_num) + ".csv"
if not os.path.exists(self.store_place):
os.mkdir(self.store_place)
tmp_origin_data.to_csv(self.store_place + "/" + document_name)
self.descriptionStruct.writeIntoCsv()
return
def changedatafield_attack_const_or_multivalue(self, id, exist_time):
# 这二者的名字是一样的？但是攻击类型是否需要相同呢？暂时是未知的
self.get_rule(" ")
document_name = "changedatafield_attack_test.csv"
# 从源数据中提取重放数据
begin_time = random.random()
begin_time = self.sourceDataSnippet.shape[0] * (2 / 3) * begin_time
begin_time = self.sourceDataSnippet.iloc[round(begin_time)]['time']
tmp_origin_data = self.sourceDataSnippet
end_time = exist_time + begin_time
# 首先得到目标列表，存放的是Rule Class的类
tmp_rule_list = self.myRuleMap.getTargetCanIdRule(id)
final_rule_list = []
for item in tmp_rule_list:
if item.type_of_class == 2 or item.type_of_class == 4:
final_rule_list.append(item)
# 存储好我们接下来要操作的类即可，这种操作是某种程度 to some extent 合理的
# 这里就随便选几个规则，都改一改
for i in range(0, self.sourceDataSnippet.shape[0]):
if tmp_origin_data.iloc[i]['time'] >= begin_time and tmp_origin_data.iloc[i]['time'] <= end_time \
and tmp_origin_data.iloc[i]['can_id'] == id:
# 正式进入random环节
# 从前半部分直接random到后半部分
print("successfully")
random_num = round(random.random() *
(len(final_rule_list) - 1)) # 取到这个值即可
ruleSingle = final_rule_list[random_num]
random_begin_bit = ruleSingle.begin_loc
length_of_bit = ruleSingle.length
random_end_bit = ruleSingle.end_loc
val_range = ruleSingle.range
target_binary_bit = tmp_origin_data.iloc[i]['data_in_binary']
descriptionTmp = ""
if ruleSingle.type_of_class == 2:
descriptionTmp = descriptionTmp + "This is a const value: "
else: # multi表示有很多个数值，处理过程是合理的
descriptionTmp = descriptionTmp + "This is a multi value: "
descriptionTmp = "before binary is " + target_binary_bit[
random_begin_bit:random_end_bit + 1]
target_binary_bit = list(target_binary_bit)
for love in range(random_begin_bit, random_end_bit + 1):
if (random.random() > 0.5):
target_binary_bit[love] = '0'
else:
target_binary_bit[love] = '1'
target_binary_bit = "".join(target_binary_bit)
descriptionTmp = descriptionTmp + " end binary is " + target_binary_bit[
random_begin_bit:random_end_bit + 1]
tmp_origin_data.loc[i, 'data_in_binary'] = target_binary_bit
tmp_origin_data.loc[i, 'data_in_hex'] = binary_str_to_hex_str(
target_binary_bit)
tmp_origin_data.loc[i, 'anormal'] = 6
hex_data = binary_str_to_hex_str(target_binary_bit)
for peace in range(0, 8):
tmp_origin_data.loc[i, 'data' +
str(peace)] = hex_data[2 * peace:2 *
peace + 2]
df3 = tmp_origin_data.iloc[i]
self.descriptionStruct.updateBasicInformation(
6, df3['can_id'], df3['time'], descriptionTmp,
df3['data_in_binary'])
self.store_place = "../src/attack_test"
document_name = document_name + str(begin_time) + "_" + str(
self.input_num) + ".csv"
if not os.path.exists(self.store_place):
os.mkdir(self.store_place)
tmp_origin_data.to_csv(self.store_place + "/" + document_name)
self.descriptionStruct.writeIntoCsv()
def changedatafield_attack(self, id, attackType, exist_time):
# 这种数据域攻击主要有两种：
# 一种是使用将某个字段设置为最大or最小常量
# 另一种是历史序列重放，可以认为是变种重返攻击
# doc path是完全不需要的
# 只对某种报文进行数据域修改，description也是暂时不需要的，应该是的吧
self.get_rule(" ")
'''
新的tag标志
checksum_tag = 0
sensor_tag = 1
const_tag = 2
counter_tag = 3
multi_value_tag = 4
no_meaning_tag = 5
攻击的mod：
以下的mod如何决定呢？暂时是不清楚的哦
const_attack: yes or no
multi_value_atack: 统一修改为第i个数值，这里i的生成方式可以固定，也可以随机
counter_attack: +1 +2 +3 修改数值即可
sensor_attack: max-value, min-value, any-value
'''
# 这里是统一的文件输入位置，可以考虑加一个函数load
document_name = "changedatafield_attack_test.csv"
# 在这里需要设定一系列参数的
# exist_time = 0.5 # 修改在0.5s内的所有数据
# 从源数据中提取重放数据
begin_time = random.random()
# 这里标记的是begin的行
begin_time = self.historyNormalDataSnippet.shape[0] * (2 /
3) * begin_time
begin_time = self.historyNormalDataSnippet.iloc[round(
begin_time)]['time']
tmp_origin_data = self.historyNormalDataSnippet
end_time = exist_time + begin_time
for i in range(0, self.origin_data.shape[0]):
# 进行按行访问
if tmp_origin_data.iloc[i][
'time'] >= begin_time and tmp_origin_data.iloc[i][
'time'] <= end_time:
if tmp_origin_data.iloc[i]['can_id'] == id:
tmp_str = tmp_origin_data.iloc[i]['data_in_binary']
# 这里显然是不太舒服的，我真的是直接裂开了
res_str = self.change_data_field(
tmp_str,
attackType) # 进行了某种级别的攻击，这里需要先定义接口，再进行不同种类的攻击书写
tmp_origin_data.iloc[i, 2] = res_str
tmp_origin_data.iloc[i, 2] = binary_str_to_hex_str(res_str)
# 下面的存储操作是完全类似的，是可以封装为函数的部分
self.store_place = "../src/attack_test"
document_name = document_name + str(begin_time) + "_" + str(
self.input_num) + ".csv"
if not os.path.exists(self.store_place):
os.mkdir(self.store_place)
tmp_origin_data.to_csv(self.store_place + "/" + document_name)
return None
