On Binary de Bruijn Sequences from LFSRs with Arbitrary Characteristic Polynomials

We propose a construction of de Bruijn sequences by the cycle joining method from linear feedback shift registers (LFSRs) with arbitrary characteristic polynomial $f(x)$. We study in detail the cycle structure of the set $\Omega(f(x))$ that contains all sequences produced by a specific LFSR on distinct inputs and provide a fast way to find a state of each cycle. This leads to an efficient algorithm to find all conjugate pairs between any two cycles, yielding the adjacency graph. The approach is practical to generate a large class of de Bruijn sequences up to order $n \approx 20$. Many previously proposed constructions of de Bruijn sequences are shown to be special cases of our construction

The Cycle Structure of LFSR with Arbitrary Characteristic Polynomial over Finite Fields

We determine the cycle structure of linear feedback shift register with arbitrary monic characteristic polynomial over any finite field. For each cycle, a method to find a state and a new way to represent the state are proposed.Comment: An extended abstract containing preliminary results was presented at SETA 201

De Bruijn Sequences, Adjacency Graphs and Cyclotomy

We study the problem of constructing De Bruijn sequences by joining cycles of linear feedback shift registers (LFSRs) with reducible characteristic polynomials. The main difficulty for joining cycles is to find the location of conjugate pairs between cycles, and the distribution of conjugate pairs in cycles is defined to be adjacency graphs. Let l(x) be a characteristic polynomial, and l(x)=l_1(x)l_2(x)\cdots l_r(x) be a decomposition of l(x) into pairwise co-prime factors. Firstly, we show a connection between the adjacency graph of FSR(l(x)) and the association graphs of FSR(l_i(x)), 1\leq i\leq r. By this connection, the problem of determining the adjacency graph of FSR(l(x)) is decomposed to the problem of determining the association graphs of FSR(l_i(x)), 1\leq i\leq r, which is much easier to handle. Then, we study the association graphs of LFSRs with irreducible characteristic polynomials and give a relationship between these association graphs and the cyclotomic numbers over finite fields. At last, as an application of these results, we explicitly determine the adjacency graphs of some LFSRs, and show that our results cover the previous ones

On the Maximum Nonlinearity of De Bruijn Sequence Feedback Function

The nonlinearity of Boolean function is an important cryptographic criteria in the Best Affine Attack approach. In this paper, based on the definition of nonlinearity, we propose a new design index of nonlinear feedback shift registers. Using the index and the correlative necessary conditions of de Bruijn sequence feedback function, we prove that when $n \ge 9$, the maximum nonlinearity $Nl{(f)_{\max }}$ of arbitrary $n -$order de Bruijn sequence feedback function $f$ satisfies $3 \cdot {2^{n - 3}} - ({Z_n} + 1) < Nl{(f)_{\max }} \le {2^{n - 1}} - {2^{\frac{{n - 1}}{2}}}$ and the nonlinearity of de Bruijn sequence feedback function, based on the spanning tree of adjacency graph of affine shift registers, has a fixed value. At the same time, this paper gives the correlation analysis and practical application of the index

The Adjacency Graphs of Linear Feedback Shift Registers with Primitive-like Characteristic Polynomials

We consider the adjacency graphs of the linear feedback shift registers (LFSRs) with characteristic polynomials of the form l(x)p(x), where l(x) is a polynomial of small degree and p(x) is a primitive polynomial. It is shown that, their adjacency graphs are closely related to the association graph of l(x) and the cyclotomic numbers over finite fields. By using this connection, we give a unified method to determine their adjacency graphs. As an application of this method, we explicitly calculate the adjacency graphs of LFSRs with characteristic polynomials of the form (1+x+x^3+x^4)p(x), and construct a large class of De Bruijn sequences from them

Complexity measures for classes of sequences and cryptographic apllications

Pseudo-random sequences are a crucial component of cryptography, particularly in stream cipher design. In this thesis we will investigate several measures of randomness for certain classes of finitely generated sequences. We will present a heuristic algorithm for calculating the k-error linear complexity of a general sequence, of either finite or infinite length, and results on the closeness of the approximation generated. We will present an linear time algorithm for determining the linear complexity of a sequence whose characteristic polynomial is a power of an irreducible element, again presenting variations for both finite and infinite sequences. This algorithm allows the linear complexity of such sequences to be determined faster than was previously possible. Finally we investigate the stability of m-sequences, in terms of both k-error linear complexity and k-error period. We show that such sequences are inherently stable, but show that some are more stable than others