def dft(sequence, reference=None):
if None == reference:
N = len(sequence)
seq_a = list(sequence)
else:
N = len(reference)
seq_a = list(reference)
seq_a_target = list(sequence)
fun_p = bma(seq_a * 2) # turn sequence as periodic
L = fun_p.degree()
# assert 2 * L <= len(seq_a)
# selection of parameters
# fine smallest n, s.t. N | (2^n - 1)
n = 1
while 0 != (2**n - 1) % N: # this means N cannot be even number
n += 1
# print n
# define the extension field
TheExtensionField = GF(2**n, 'beta')
beta = TheExtensionField.gen()
fun_f = TheExtensionField.polynomial()
TheExtensionPolynomialRing = TheExtensionField['Y']
# print fun_f
# construct a new m-seq {b_t}
seq_b_iv = []
for i in range(n):
seq_b_iv.append((beta**i).trace())
seq_b_generator = lfsr(seq_b_iv, fun_f)
seq_b = []
for i in range(2**len(seq_b_iv) - 1):
seq_b.append(seq_b_generator.next())
# print seq_b_iv
# print seq_b
# let alpha be an element in GF(2^n) with order N
alpha = beta**((2**n - 1) / N)
# print alpha, alpha ** N
# procedure
# step 1. compute coset
I = coset(N)
# print I
# step 2.
fun_p_extended = TheExtensionPolynomialRing(fun_p)
# print fun_p_extended
spectra_A = [None] * N
spectra_A_target = [None] * N
for k in I:
if fun_p_extended(alpha**k) != 0:
spectra_A[k] = 0
if reference:
spectra_A_target[k] = 0
continue
# print 'k', k, fun_p_extended(alpha ** k)
# sub-routine for computing A_k
# 1. get coset size
m = I[k]
# print k, m, n
# 2. k-decimation sequence
seq_c = []
if m == n:
for t in range(2 * m):
seq_c.append(seq_b[(t * k) % (2**n - 1)])
elif m < n:
for t in range(2 * m):
seq_c.append(trace(alpha**(k * t), m))
else:
import sys
sys.stderr.write("should never happen?\n")
sys.exit(-1)
# print seq_b
# print seq_c
fun_p_k = bma(seq_c)
# print fun_p
# print fun_p_k
# print fun_p / fun_p_k
matrix_M_ele = []
for i in range(m):
for ele in range(i, m + i):
matrix_M_ele.append(seq_c[ele])
matrix_M = matrix(GF(2), m, m, matrix_M_ele)
# print 'matrix_M'
# print matrix_M
# 3. contruct a filter
fun_q = fun_p.parent()(fun_p / fun_p_k)
# print fun_q
# print type(fun_q)
# 4. compute the time convolution
seq_v_generator = convolution(seq_a, fun_q)
seq_v = []
for i in range(m):
seq_v.append(seq_v_generator.next())
if reference:
seq_v_target_generator = convolution(seq_a_target, fun_q)
seq_v_target = []
for i in range(m):
seq_v_target.append(seq_v_target_generator.next())
# 4.5 solve linear equations to get x_i
matrix_x = matrix_M.inverse() * matrix(GF(2), m, 1, seq_v)
# print 'matrix_x'
# print matrix_x
if reference:
matrix_x_target = matrix_M.inverse() * matrix(
GF(2), m, 1, seq_v_target)
# print 'matrix_x_target'
# print matrix_x_target
# 5. compute A_k = V * T
V = 0
for i in range(m):
if 1 == matrix_x[i][0]:
V += alpha**(i * k)
if reference:
V_target = 0
for i in range(m):
if 1 == matrix_x_target[i][0]:
V_target += alpha**(i * k)
fun_q_extended = TheExtensionPolynomialRing(fun_q)
# print fun_q_extended
T = fun_q_extended(alpha**k)**(-1)
# print T
# print type(T)
A_k = V * T
# print A_k
spectra_A[k] = A_k
if reference:
A_k_target = V_target * T
spectra_A_target[k] = A_k_target
# print spectra_A
# print spectra_A_target
# to compute the A_k where k is not coset leader
for i in I:
for j in range(1, I[i]):
spectra_A[(i * (2**j)) % N] = spectra_A[i]**(2**j)
if reference:
spectra_A_target[(i * (2**j)) %
N] = spectra_A_target[i]**(2**j)
# print alpha ** 6
if None == reference:
return spectra_A
else:
return spectra_A, spectra_A_target
def dft_attack(seq_s, fun_f, fun_g):
n = fun_f.degree()
field = GF(2 ** n, name = 'gamma', modulus = fun_f)
gamma = field.gen()
seq_b_iv = []
for i in range(n):
seq_b_iv.append(trace(gamma ** i))
seq_b_generator = lfsr(seq_b_iv, fun_f)
seq_b = []
for i in range(2 ** n - 1):
seq_b.append(seq_b_generator.next())
# print 'seq_b', seq_b
seq_a = []
seq_b_doubled = seq_b * 2 # for ease of programming
for i in range(2 ** n - 1):
seq_a.append(GF(2)(fun_g(seq_b_doubled[i : (i + n)])))
fun_p = bma(seq_a)
if len(seq_s) < fun_p.degree():
os.stderr.write("algorithm failed\n")
os.exit(-1)
# 2
coset_leaders = coset(2 ** n - 1)
for k in coset_leaders: # coset() is changed?
if 1 == gcd(k, 2 ** n - 1) and k is not 1:
break
# k_inverse = field(k).pth_power(-1) # not right?
for i in range(2 ** n - 1):
if (i * k) % (2 ** n - 1) == 1:
k_inverse = i
break
#print 'k_inverse', k_inverse
# 3
# print 'seq_a', seq_a
# print type(seq_a[0])
(A_k, S_k) = dft(seq_s, seq_a)
# print 'A_k', A_k
# online phase
# 1
# print 'seq_s', seq_s
# two dft computations are combined now
# print 'S_k', S_k
# 2
# print 'k', k
# print 'k_inverse', k_inverse
# k_inverse = 13
gamma_tau = (S_k[k] * (A_k[k] ** (-1))) ** (k_inverse)
# print gamma_tau
# 3
result_u = []
for i in range(n):
result_u.append(trace(gamma_tau * (gamma_tau.parent().gen() ** i)))
return result_u
def dft(sequence, reference=None):
if None == reference:
N = len(sequence)
seq_a = list(sequence)
else:
N = len(reference)
seq_a = list(reference)
seq_a_target = list(sequence)
fun_p = bma(seq_a * 2) # turn sequence as periodic
L = fun_p.degree()
# assert 2 * L <= len(seq_a)
# selection of parameters
# fine smallest n, s.t. N | (2^n - 1)
n = 1
while 0 != (2 ** n - 1) % N: # this means N cannot be even number
n += 1
# print n
# define the extension field
TheExtensionField = GF(2 ** n, "beta")
beta = TheExtensionField.gen()
fun_f = TheExtensionField.polynomial()
TheExtensionPolynomialRing = TheExtensionField["Y"]
# print fun_f
# construct a new m-seq {b_t}
seq_b_iv = []
for i in range(n):
seq_b_iv.append((beta ** i).trace())
seq_b_generator = lfsr(seq_b_iv, fun_f)
seq_b = []
for i in range(2 ** len(seq_b_iv) - 1):
seq_b.append(seq_b_generator.next())
# print seq_b_iv
# print seq_b
# let alpha be an element in GF(2^n) with order N
alpha = beta ** ((2 ** n - 1) / N)
# print alpha, alpha ** N
# procedure
# step 1. compute coset
I = coset(N)
# print I
# step 2.
fun_p_extended = TheExtensionPolynomialRing(fun_p)
# print fun_p_extended
spectra_A = [None] * N
spectra_A_target = [None] * N
for k in I:
if fun_p_extended(alpha ** k) != 0:
spectra_A[k] = 0
if reference:
spectra_A_target[k] = 0
continue
# print 'k', k, fun_p_extended(alpha ** k)
# sub-routine for computing A_k
# 1. get coset size
m = I[k]
# print k, m, n
# 2. k-decimation sequence
seq_c = []
if m == n:
for t in range(2 * m):
seq_c.append(seq_b[(t * k) % (2 ** n - 1)])
elif m < n:
for t in range(2 * m):
seq_c.append(trace(alpha ** (k * t), m))
else:
import sys
sys.stderr.write("should never happen?\n")
sys.exit(-1)
# print seq_b
# print seq_c
fun_p_k = bma(seq_c)
# print fun_p
# print fun_p_k
# print fun_p / fun_p_k
matrix_M_ele = []
for i in range(m):
for ele in range(i, m + i):
matrix_M_ele.append(seq_c[ele])
matrix_M = matrix(GF(2), m, m, matrix_M_ele)
# print 'matrix_M'
# print matrix_M
# 3. contruct a filter
fun_q = fun_p.parent()(fun_p / fun_p_k)
# print fun_q
# print type(fun_q)
# 4. compute the time convolution
seq_v_generator = convolution(seq_a, fun_q)
seq_v = []
for i in range(m):
seq_v.append(seq_v_generator.next())
if reference:
seq_v_target_generator = convolution(seq_a_target, fun_q)
seq_v_target = []
for i in range(m):
seq_v_target.append(seq_v_target_generator.next())
# 4.5 solve linear equations to get x_i
matrix_x = matrix_M.inverse() * matrix(GF(2), m, 1, seq_v)
# print 'matrix_x'
# print matrix_x
if reference:
matrix_x_target = matrix_M.inverse() * matrix(GF(2), m, 1, seq_v_target)
# print 'matrix_x_target'
# print matrix_x_target
# 5. compute A_k = V * T
V = 0
for i in range(m):
if 1 == matrix_x[i][0]:
V += alpha ** (i * k)
if reference:
V_target = 0
for i in range(m):
if 1 == matrix_x_target[i][0]:
V_target += alpha ** (i * k)
fun_q_extended = TheExtensionPolynomialRing(fun_q)
# print fun_q_extended
T = fun_q_extended(alpha ** k) ** (-1)
# print T
# print type(T)
A_k = V * T
# print A_k
spectra_A[k] = A_k
if reference:
A_k_target = V_target * T
spectra_A_target[k] = A_k_target
# print spectra_A
# print spectra_A_target
# to compute the A_k where k is not coset leader
for i in I:
for j in range(1, I[i]):
spectra_A[(i * (2 ** j)) % N] = spectra_A[i] ** (2 ** j)
if reference:
spectra_A_target[(i * (2 ** j)) % N] = spectra_A_target[i] ** (2 ** j)
# print alpha ** 6
if None == reference:
return spectra_A
else:
return spectra_A, spectra_A_target
