- class galois.FLFSR
A Fibonacci linear-feedback shift register (LFSR).
Notes¶
A Fibonacci LFSR is defined by its feedback (connection) polynomial
\[ f(x) = 1 + a_1 x + a_2 x^2 + \dots + a_{n} x^{n}, \]where \(f(0) = 1\) and the degree \(n\) equals the length of the shift register. The associated output sequence \(y[t]\) satisfies the linear recurrence
\[ y[t] + a_1 y[t-1] + a_2 y[t-2] + \dots + a_{n} y[t-n] = 0. \]The characteristic polynomial of the sequence is the reciprocal of the feedback polynomial
\[\begin{split} c(x) &= x^{n} + a_1 x^{n-1} + a_2 x^{n-2} + \dots + a_{n} \\ &= x^{n} f(x^{-1}). \end{split}\]In the Fibonacci configuration, the shift register is arranged so that its taps implement the recurrence directly. The taps are simply the feedback coefficients \([-a_1, -a_2, \dots, -a_n]\) in a fixed left-to-right order that matches the chosen shift direction.
Fibonacci LFSR Configuration¶y[t] +--------------+<-------------+<-------------+<-------------+ | ^ ^ ^ | | | -a_1 | -a_2 | -a_{n-1} | -a_n | | T[0] | T[1] | T[n-2] | T[n-1] | +--------+ | +--------+ | | +--------+ | +->| S[0] |--+->| S[1] |--+--- ... ---+->| S[n-1] |--+--> y[t-n] +--------+ +--------+ +--------+ y[t-1] y[t-2] y[t-n]The state vector is stored left-to-right as \(S = [S_0, S_1, \dots, S_{n-1}]\).
References¶
Gardner, D. 2019. “Applications of the Galois Model LFSR in Cryptography”. figshare. https://hdl.handle.net/2134/21932.
See also
Examples¶
Create a Fibonacci LFSR from a degree-4 primitive characteristic polynomial over \(\mathrm{GF}(2)\).
In [1]: feedback_poly = galois.primitive_poly(2, 4).reverse(); feedback_poly Out[1]: Poly(x^4 + x^3 + 1, GF(2)) In [2]: lfsr = galois.FLFSR(feedback_poly) In [3]: print(lfsr) Fibonacci LFSR: field: GF(2) feedback_poly: 1 + x^3 + x^4 characteristic_poly: x^4 + x + 1 taps: [0 0 1 1] order: 4 state: [1 1 1 1] initial_state: [1 1 1 1]Step the Fibonacci LFSR and produce 10 output symbols.
In [4]: lfsr.state Out[4]: GF([1, 1, 1, 1], order=2) In [5]: lfsr.step(10) Out[5]: GF([1, 1, 1, 1, 0, 0, 0, 1, 0, 0], order=2) In [6]: lfsr.state Out[6]: GF([1, 0, 1, 1], order=2)Create a Fibonacci LFSR from a degree-4 primitive characteristic polynomial over \(\mathrm{GF}(7)\).
In [7]: feedback_poly = galois.primitive_poly(7, 4).reverse(); feedback_poly Out[7]: Poly(5x^4 + 3x^3 + x^2 + 1, GF(7)) In [8]: lfsr = galois.FLFSR(feedback_poly) In [9]: print(lfsr) Fibonacci LFSR: field: GF(7) feedback_poly: 1 + x^2 + 3x^3 + 5x^4 characteristic_poly: x^4 + x^2 + 3x + 5 taps: [0 6 4 2] order: 4 state: [1 1 1 1] initial_state: [1 1 1 1]Step the Fibonacci LFSR and produce 10 output symbols.
In [10]: lfsr.state Out[10]: GF([1, 1, 1, 1], order=7) In [11]: lfsr.step(10) Out[11]: GF([1, 1, 1, 1, 5, 5, 1, 3, 1, 4], order=7) In [12]: lfsr.state Out[12]: GF([5, 5, 6, 6], order=7)Create a Fibonacci LFSR from a degree-4 primitive characteristic polynomial over \(\mathrm{GF}(2^3)\).
In [13]: feedback_poly = galois.primitive_poly(2**3, 4).reverse(); feedback_poly Out[13]: Poly(3x^4 + x^3 + 1, GF(2^3)) In [14]: lfsr = galois.FLFSR(feedback_poly) In [15]: print(lfsr) Fibonacci LFSR: field: GF(2^3) feedback_poly: 1 + x^3 + 3x^4 characteristic_poly: x^4 + x + 3 taps: [0 0 1 3] order: 4 state: [1 1 1 1] initial_state: [1 1 1 1]Step the Fibonacci LFSR and produce 10 output symbols.
In [16]: lfsr.state Out[16]: GF([1, 1, 1, 1], order=2^3) In [17]: lfsr.step(10) Out[17]: GF([1, 1, 1, 1, 2, 2, 2, 1, 4, 4], order=2^3) In [18]: lfsr.state Out[18]: GF([0, 3, 7, 7], order=2^3)Create a Fibonacci LFSR from a degree-4 primitive characteristic polynomial over \(\mathrm{GF}(3^3)\).
In [19]: feedback_poly = galois.primitive_poly(3**3, 4).reverse(); feedback_poly Out[19]: Poly(10x^4 + x^3 + 1, GF(3^3)) In [20]: lfsr = galois.FLFSR(feedback_poly) In [21]: print(lfsr) Fibonacci LFSR: field: GF(3^3) feedback_poly: 1 + x^3 + 10x^4 characteristic_poly: x^4 + x + 10 taps: [ 0 0 2 20] order: 4 state: [1 1 1 1] initial_state: [1 1 1 1]Step the Fibonacci LFSR and produce 10 output symbols.
In [22]: lfsr.state Out[22]: GF([1, 1, 1, 1], order=3^3) In [23]: lfsr.step(10) Out[23]: GF([ 1, 1, 1, 1, 19, 19, 19, 1, 25, 25], order=3^3) In [24]: lfsr.state Out[24]: GF([ 6, 24, 4, 16], order=3^3)Constructors¶
-
FLFSR(feedback_poly: Poly, state: ArrayLike | None =
None) Constructs a Fibonacci LFSR from its feedback polynomial \(f(x)\).
- classmethod Taps(taps: FieldArray, ...) Self
Constructs a Fibonacci LFSR from its taps \(T = [-a_1, -a_2, \dots, -a_n]\).
String representation¶
Methods¶
-
step(steps: int =
1) FieldArray Produces the next
stepsoutput symbols.
- to_galois_lfsr() GLFSR
Converts the Fibonacci LFSR to a Galois LFSR that produces the same output sequence.
Properties¶
- property field : type[FieldArray]
The
FieldArraysubclass for the finite field that defines the linear arithmetic.
- property order : int
The order of the linear recurrence and linear recurrent sequence. The order of a sequence is defined by the degree of the connection, feedback, and characteristic polynomials that generate it.
- property taps : FieldArray
The shift register taps \(T = [-a_1, -a_2, \dots, -a_{n-1}, -a_n]\). The taps of the shift register define the linear recurrence relation.
Polynomials¶
- property characteristic_poly : Poly
The characteristic polynomial \(c(x) = x^{n} + a_1 x^{n-1} + a_2 x^{n-2} + \dots + a_{n}\).
- property feedback_poly : Poly
The feedback polynomial \(f(x) = 1 + a_1 x + a_2 x^2 + \dots + a_{n} x^{n}\).
State¶
- property initial_state : FieldArray
The initial state vector \(S = [S_0, S_1, \dots, S_{n-2}, S_{n-1}]\).
- property state : FieldArray
The current state vector \(S = [S_0, S_1, \dots, S_{n-2}, S_{n-1}]\).