def produceMasterProfileFAR(text, user):
all_keyHoldTime = []
all_interkeyTime = []
filename = 'processedData/text{0}/user{1}.json'.format(text, user)
with open(filename, 'r') as f:
data = [json.loads(line) for line in f]
outliers = getPositionOfOutliers(text, user)
data = [timings for i, timings in enumerate(data) if not i in outliers]
for i, timings in enumerate(data):
ikt = calculateInterkeyTime(timings['keyPressData'],
timings['keyReleaseData'])
kht = calculateKeyHoldTime(timings['keyPressData'],
timings['keyReleaseData'])
if len(ikt) > len(kht):
del ikt[-1]
elif len(kht) > len(ikt):
del kht[-1]
all_interkeyTime.append(ikt)
all_keyHoldTime.append(kht)
master_interkeyTime = [
statistics.mean(time) for time in zip(*all_interkeyTime)
]
master_keyHoldTime = [
statistics.mean(time) for time in zip(*all_keyHoldTime)
]
return (master_interkeyTime, master_keyHoldTime, all_interkeyTime,
all_keyHoldTime)
def profilePlot():
all_keyHoldTime = []
all_interkeyTime = []
for user in range(1, 2):
for text in range(1, 2):
filename = 'processedData/text{0}/user{1}.json'.format(text, user)
with open(filename, 'r') as f:
data = [json.loads(line) for line in f]
outliers = getPositionOfOutliers(text, user)
data = [
timings for i, timings in enumerate(data) if not i in outliers
]
for i, timings in enumerate(data):
ikt = calculateInterkeyTime(timings['keyPressData'],
timings['keyReleaseData'])
kht = calculateKeyHoldTime(timings['keyPressData'],
timings['keyReleaseData'])
if len(ikt) > len(kht):
del ikt[-1]
elif len(kht) > len(ikt):
del kht[-1]
all_interkeyTime.append(ikt)
all_keyHoldTime.append(kht)
fig = int('{}{}'.format(user, text))
plt.figure(fig)
plt.plot([i / 10000 for i in kht], [i / 10000 for i in ikt])
plt.xlabel('Key Hold Time (*10^4)(microseconds)')
plt.ylabel('Interkey Time (*10^4)(microseconds)')
plt.savefig('user{}-text{}.png'.format(user, text))
def authenticateFRR(user, text, comparator):
master_ikt, master_kht, c, d = produceMasterProfileFRR(text, user)
count = 0
allUserCount = 0
filename = 'processedData/text{0}/user{1}.json'.format(text, user)
with open(filename, 'r') as f:
data = [json.loads(line) for line in f]
outliers = getPositionOfOutliers(text, user)
data = [timings for i, timings in enumerate(data) if not i in outliers]
for timings in data[5:]:
ikt = calculateInterkeyTime(timings['keyPressData'],
timings['keyReleaseData'])
kht = calculateKeyHoldTime(timings['keyPressData'],
timings['keyReleaseData'])
if len(ikt) > len(kht):
del ikt[-1]
elif len(kht) > len(ikt):
del kht[-1]
euclideanDistance = [
((x1 - x2)**2 + (y1 - y2)**2)**(1 / 2)
for x1, y1, x2, y2 in zip(master_ikt, master_kht, ikt, kht)
]
dissimilarity = sum(euclideanDistance)
authenticationValue = 1 if dissimilarity <= comparator else 0
user = '******' if authenticationValue == 1 else 'Imposter'
if user == 'Imposter':
count += 1
allUserCount += 1
return ((count / allUserCount) * 100)
def authenticate():
dp, dr = extractTimings(dataProcess(pressdata), dataProcess(releasedata))
lt = calculateLatencyTime(dp, dr)
ikt = calculateInterkeyTime(dp, dr)
# master_lt = []
# master_ikt = []
master_lt, master_ikt = produceMasterProfile()
euclideanDistance = [
((x1 - x2)**2 + (y1 - y2)**2)**(1 / 2)
for x1, y1, x2, y2 in zip(master_lt, master_ikt, lt, ikt)
]
dissimilarity = sum(euclideanDistance)
comparator = generateComparator()
authenticationValue = 1 if dissimilarity <= comparator else 0
# print(authenticationValue)
user = '******' if authenticationValue == 1 else 'Imposter'
print(user)
def plotOfBoxplots():
filename = 'processedData/text{0}/user{1}.json'.format(3, 1)
with open(filename, 'r') as f:
data = [json.loads(line) for line in f]
all_ikt = [[
i / 10000 for i in calculateInterkeyTime(timings['keyPressData'],
timings['keyReleaseData'])
] for timings in data]
ikt = [list(lst) for lst in zip(*all_ikt)]
plt.figure()
plt.boxplot(ikt, vert=0)
my_yticks = [
's-t', 't-u', 'u-d', 'd-e', 'e-n', 'n-t', 't-space', 'space-h', 'h-e',
'e-l', 'l-l', 'l-o', 'o-space', 'space-w', 'w-o', 'o-r', 'r-l', 'l-d'
]
plt.yticks(list(range(1, 19)), my_yticks)
plt.xlabel('Range of interkey values (*10^4)(microseconds)')
plt.ylabel('Box plots')
plt.show()
def produceMasterProfile():
with open('data.json', 'r') as f:
data = json.load(f)
for timings in data:
lt = calculateLatencyTime(timings['keyPressData'],
timings['keyReleaseData'])
ikt = calculateInterkeyTime(timings['keyPressData'],
timings['keyReleaseData'])
all_latencyTime.append(lt)
all_interkeyTime.append(ikt)
master_latencyTime = [
statistics.mean(time) for time in zip(*all_latencyTime)
]
master_interkeyTime = [
statistics.mean(time) for time in zip(*all_interkeyTime)
]
# print(master_latencyTime)
# print(master_interkeyTime)
plt.figure(1)
plt.plot(master_latencyTime, master_interkeyTime)
# plt.show()
return (master_latencyTime, master_interkeyTime)
def produceMasterProfileFRR(text, user):
all_keyHoldTime = []
all_interkeyTime = []
filename = 'processedData/text{0}/user{1}.json'.format(text, user)
with open(filename, 'r') as f:
data = [json.loads(line) for line in f]
outliers = getPositionOfOutliers(text, user)
data = [timings for i, timings in enumerate(data) if not i in outliers]
# here only 5 records have been used because after removing outliers around 20 records are only left
# per user; so only 5 for master profile generation and remaining for authentication
for timings in data[:5]:
ikt = calculateInterkeyTime(timings['keyPressData'],
timings['keyReleaseData'])
kht = calculateKeyHoldTime(timings['keyPressData'],
timings['keyReleaseData'])
if len(ikt) > len(kht):
del ikt[-1]
elif len(kht) > len(ikt):
del kht[-1]
all_interkeyTime.append(ikt)
all_keyHoldTime.append(kht)
master_interkeyTime = [
statistics.mean(time) for time in zip(*all_interkeyTime)
]
master_keyHoldTime = [
statistics.mean(time) for time in zip(*all_keyHoldTime)
]
return (master_interkeyTime, master_keyHoldTime, all_interkeyTime,
all_keyHoldTime)