def classify(res,m,n,omega,lastBit):
# Initialise the subsets to empty lists and the counters to 0
# (for each subset)
r0 = [0,0]
c0 = [0,0]
r1 = [0,0]
c1 = [0,0]
# Classify each message depending if there was a reduction or not
for i in range(0,sampleSize):
# assuming that the bit is 1
#print lastBit
#print i
#print len(res[0][i])
temp1 = montMul(res[lastBit][i][-1],m[i],n,omega) #multiplication
temp1,red = montMulRed(temp1,temp1,n,omega) #squaring
r1[red]+=t[i]
c1[red]+=1
#assuming that the bit is 0
temp0,red = montMulRed(res[lastBit][i][-1],res[lastBit][i][-1],n,omega) #squaring
r0[red]+=t[i]
c0[red]+=1
res[1][i].append(temp1)
res[0][i].append(temp0)
# Calculate the difference between the average times when we assume that
# last bit is 0 and when the last bit is 1
u0 = abs(float(r0[1])/c0[1] - float(r0[0])/c0[0])
u1 = abs(float(r1[1])/c1[1] - float(r1[0])/c1[0])
return u0,u1,res
def test_errorFix(res,k,m,t):
r0 = [0,0]
c0 = [0,0]
r1 = [0,0]
c1 = [0,0]
lastBit = k&1
confidence = deque([],average_n)
temp0 = [0]*sampleSize
temp1 = [0]*sampleSize
x=[]
for i in range(0,sampleSize):
x.append(res[lastBit][i][-1])
for j in range(0,test_length):
r0 = [0,0]
c0 = [0,0]
r1 = [0,0]
c1 = [0,0]
for i in range(0,sampleSize):
temp = montMul(x[i],m[i],n,omega)
temp1[i],red = montMulRed(temp,temp,n,omega)
r1[red]+=t[i]
c1[red]+=1
temp0[i],red = montMulRed(x[i],x[i],n,omega)
r0[red]+=t[i]
c0[red]+=1
u0 = abs(float(r0[1])/c0[1] - float(r0[0])/c0[0])
u1 = abs(float(r1[1])/c1[1] - float(r1[0])/c1[0])
confidence.append(abs(u0-u1))
k<<=1
if u1>u0:
k+=1
x,temp1 = temp1,x
else:
x,temp0 = temp0,x
# If the average confidence level for the past "average_n" iterations
# is under threshold_difference return false
if len(confidence)==average_n:
if sum(confidence)/len(confidence)<threshold_difference:
return False
return True
def main(n,e):
m,t,x = getRandomMessages() # get the random ciphers (in Mont form),
# corresponding times and partial results of the
# partial exponentiation
# Temporary memory to save partial results of the exponentiation when
# assuming the last bit of the key is 0 or 1
res1 = [0]*sampleSize
res0 = [0]*sampleSize
key_guess = 1;
B = 1 #number of bits in the guessed key
H = 1 #hamming weight of the guessed key
while B+H < maxLength:
print B
# Initialise the subsets to empty lists and the counters to 0
# (for each subset)
r0 = [0,0]
c0 = [0,0]
r1 = [0,0]
c1 = [0,0]
# Classify each message depending if there was a reduction or not
for i in range(0,sampleSize):
# assuming that the bit is 1
res1[i] = montMul(x[i],m[i],n,omega) #multiplication
res1[i],red = montMulRed(res1[i],res1[i],n,omega) #squaring
r1[red]+=t[i]
c1[red]+=1
#assuming that the bit is 0
res0[i],red = montMulRed(x[i],x[i],n,omega) #squaring
r0[red]+=t[i]
c0[red]+=1
# Calculate the difference between the average times when we assume that
# last bit is 0 and when the last bit is 1
u1 = abs(float(r1[1])/c1[1] - float(r1[0])/c1[0])
u0 = abs(float(r0[1])/c0[1] - float(r0[0])/c0[0])
# some threshold conditions
if abs(u0-u1)<threshold_difference:
print "The difference between deviation of means is not big enough"
return -1
if u1>u0 and u1<threshold_individual:
print "The timing difference between M1 and M2 is not big enough"
return -1
if u0>u1 and u0<threshold_individual:
print "The timing difference between M3 and M4 is not big enough"
return -1
# Append the guessed bit to the key and save the partial results of the
# exponentiation in x and save the partial results in x
key_guess = key_guess<<1
if u1>u0:
key_guess +=1
H+=1
x,res1 = res1,x
else:
x,res0 = res0,x
B+=1
# Test the key by appending a '1' to it
# The last bit of d is '1' because gcd(d,phi(N)) = 1
key_temp = (key_guess<<1) | 1
if testKey(key_temp):
return key_temp
print "1011111110001100011110011001001001001010111110011101001010000101"
print "{0:b}".format(key_guess)
print "B="+str(B)+" H="+str(H)
return -1
