Measures Of Pseudorandomness Research Articles

On the Stability of the Linear Complexity of Some Generalized Cyclotomic Sequences of Order Two

Linear complexity is an important pseudo-random measure of the key stream sequence in a stream cipher system. The 1-error linear complexity is used to measure the stability of the linear complexity, which means the minimal linear complexity of the new sequence by changing one bit of the original key stream sequence. This paper contributes to calculating the exact values of the linear complexity and 1-error linear complexity of the binary key stream sequence with two prime periods defined by Ding–Helleseth generalized cyclotomy. We provide a novel method to solve such problems by employing the discrete Fourier transform and the M–S polynomial of the sequence. Our results show that, by choosing appropriate parameters p and q, the linear complexity and 1-error linear complexity can be no less than half period, which shows that the linear complexity of this sequence not only meets the requirements of cryptography but also has good stability.

Pseudorandom Binary Sequences: Quality Measures and Number-Theoretic Constructions

In this survey we summarize properties of pseudorandomness and non-randomness of some number-theoretic sequences and present results on their behaviour under the following measures of pseudorandomness: balance, linear complexity, correlation measure of order k, expansion complexity and 2-adic complexity. The number-theoretic sequences are the Legendre sequence and the two-prime generator, the Thue-Morse sequence and its sub-sequence along squares, and the prime omega sequences for integers and polynomials.

Random Polynomials in Legendre Symbol Sequences

Abstract It is important in cryptographic applications that the “key” used should be generated from a random seed. Thus, if the Legendre symbol sequence generated by a polynomial (as proposed by Hoffstein and Lieman) is used, that is { ( f ( 1 ) p ) , ( f ( 2 ) p ) , ( f ( 3 ) p ) , ⋯ , ( f ( p ) p ) } , \left\{ {\left( {{{f\left( 1 \right)} \over p}} \right),\left( {{{f\left( 2 \right)} \over p}} \right),\left( {{{f\left( 3 \right)} \over p}} \right), \cdots ,\left( {{{f\left( p \right)} \over p}} \right)} \right\}, then it is important to choose the polynomial f “almost” at random. Goubin, Mauduit, and Sárközy presented some not very restrictive conditions on the polynomial f, but these conditions may not be satisfied if we choose a “truly” random polynomial. However, how can it be guaranteed that the pseudorandom measures of the sequence should be small for almost "random" polynomials? These semirandom polynomials will be constructed with as few modifications as necessary from a truly random polynomial.

Arithmetic Crosscorrelation of Pseudorandom Binary Sequences of Coprime Periods

The (classical) crosscorrelation is an important measure of pseudorandomness of two binary sequences for applications in communications. The arithmetic crosscorrelation is another figure of merit introduced by Goresky and Klapper generalizing Mandelbaum’s arithmetic autocorrelation. First we observe that the arithmetic crosscorrelation is constant for two binary sequences of coprime periods, which complements the analogous result for the classical crosscorrelation. Then we prove upper bounds for the constant arithmetic crosscorrelation of two Legendre sequences of different periods and of two binary <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula> -sequences of coprime periods, respectively.

Pseudorandom sequences derived from automatic sequences

Many automatic sequences, such as the Thue-Morse sequence or the Rudin-Shapiro sequence, have some desirable features of pseudorandomness such as a large linear complexity and a small well-distribution measure. However, they also have some undesirable properties in view of certain applications. For example, the majority of possible binary patterns never appears in automatic sequences and their correlation measure of order 2 is extremely large. Certain subsequences, such as automatic sequences along squares, may keep the good properties of the original sequence but avoid the bad ones. In this survey we investigate properties of pseudorandomness and non-randomness of automatic sequences and their subsequences and present results on their behaviour under several measures of pseudorandomness including linear complexity, correlation measure of order k, expansion complexity and normality. We also mention some analogs for finite fields.

Gowers norms and pseudorandom measures of subsets

Gowers norms and pseudorandom measures of subsets

Binary sequences and lattices constructed by discrete logarithms

&lt;abstract&gt;&lt;p&gt;In 1997, Mauduit and Sárközy first introduced the measures of pseudorandomness for binary sequences. Since then, many pseudorandom binary sequences have been constructed and studied. In particular, Gyarmati presented a large family of pseudorandom binary sequences using the discrete logarithms. Ten years later, to satisfy the requirement from many applications in cryptography (e.g., in encrypting "bit-maps'' and watermarking), the definition of binary sequences is extended from one dimension to several dimensions by Hubert, Mauduit and Sárközy. They introduced the measure of pseudorandomness for this kind of several-dimension binary sequence which is called binary lattices. In this paper, large families of pseudorandom binary sequences and binary lattices are constructed by both discrete logarithms and multiplicative inverse modulo $ p $. The upper estimates of their pseudorandom measures are based on estimates of either character sums or mixed exponential sums.&lt;/p&gt;&lt;/abstract&gt;

Correlation measure, linear complexity and maximum order complexity for families of binary sequences

The correlation measure of order k is an important measure of pseudorandomness for binary sequences. This measure tries to look for dependence between several shifted versions of a sequence. We study the relation between the correlation measure of order k and two other pseudorandom measures: the Nth linear complexity and the Nth maximum order complexity. We simplify and improve several state-of-the-art lower bounds for these two measures using the Hamming bound as well as weaker bounds derived from it.

Weighted Measures of Pseudorandom Binary Lattices

In cryptography one needs pseudorandom sequences whose short subsequences are also pseudorandom. To handle this problem, Dartyge, Gyarmati and Sárközy introduced weighted measures of pseudorandomness of binary sequences. In this paper we continue the research in this direction. We introduce weighted pseudorandom measure for multidimensional binary lattices and estimate weighted pseudorandom measure for truly random binary lattices. We also give lower bounds for weighted measures of even order and present an example by using the quadratic character of finite fields.

On pseudorandom subsets in finite fields I: measure of pseudorandomness and support of Boolean functions

On pseudorandom subsets in finite fields I: measure of pseudorandomness and support of Boolean functions

On an inequality between pseudorandom measures of lattices

Mauduit and Sárközy proved the following inequality between the well-distribution measure and the correlation measure of order 2: W(EN)≤3NC2(EN). This result has been generalized to inequalities between the combined pseudorandom measures and correlation measures of even order by the authors of the present paper. Here the multidimensional case is studied, and this inequality is extended further to the case of binary lattices.

Constructions of pseudorandom binary lattices using cyclotomic classes in finite fields

Abstract In 2006, Hubert, Mauduit and Sárközy extended the notion of binary sequences to n-dimensional binary lattices and introduced the measures of pseudorandomness of binary lattices. In 2011, Gyarmati, Mauduit and Sárközy extended the notions of family complexity, collision and avalanche effect from binary sequences to binary lattices. In this paper, we construct pseudorandom binary lattices by using cyclotomic classes in finite fields and study the pseudorandom measure of order k, family complexity, collision and avalanche effect. Results indicate that such binary lattices are “good,” and their families possess a nice structure in terms of family complexity, collision and avalanche effect.

On the pseudorandom properties of subsets constructed by using primitive roots

Dartyge and Sarkozy (partly with other coauthors) introduced pseudorandom measures of subsets, and studied the pseudorandomness of certain subsets related to primitive roots. In this paper we answer a conjecture of Dartyge, Sarkozy and Szalay, and study the pseudorandom properties of some subsets constructed by using primitive roots.

On the Maximum Order Complexity of the Thue-Morse and Rudin-Shapiro Sequence

Abstract Expansion complexity and maximum order complexity are both finer measures of pseudorandomness than the linear complexity which is the most prominent quality measure for cryptographic sequences. The expected value of the Nth maximum order complexity is of order of magnitude log N whereas it is easy to find families of sequences with Nth expansion complexity exponential in log N. This might lead to the conjecture that the maximum order complexity is a finer measure than the expansion complexity. However, in this paper we provide two examples, the Thue-Morse sequence and the Rudin-Shapiro sequence with very small expansion complexity but very large maximum order complexity. More precisely, we prove explicit formulas for their N th maximum order complexity which are both of the largest possible order of magnitude N. We present the result on the Rudin-Shapiro sequence in a more general form as a formula for the maximum order complexity of certain pattern sequences.

A Note on Hall’s Sextic Residue Sequence: Correlation Measure of Order $k$ and Related Measures of Pseudorandomness

It is known that Hall’s sextic residue sequence has some desirable features of pseudorandomness: an ideal two-level autocorrelation and linear complexity of the order of magnitude of its period $p$ . Here we study its correlation measure of order $k$ and show that it is, up to a constant depending on $k$ and some logarithmic factor, of order of magnitude $p^{1/2}$ , which is close to the expected value for a random sequence of length $p$ . Moreover, we derive from this bound a lower bound on the $N$ th maximum order complexity of order of magnitude $\log p$ , which is the expected order of magnitude for a random sequence of length $p$ .

Dynamic error testing method of electricity meters by a pseudo random distorted test signal

The complex random characteristics of dynamic loads in smart grid lead to the metering errors exceed the limits of electricity meters used in real field, these errors are called dynamic errors. By analyzing the typical intrinsic characteristics of large power dynamic loads and the nonadaptive linear modulation of compressive sensing (CS), this paper firstly constructs an orthogonal pseudo random measurement (OPRM) matrix to modulate distorted steady-state test signal (DSTS) and then proposes an orthogonal pseudo random measurement distorted dynamic test signal (OPRM-DDTS) with the intrinsic characteristics. In addition, an indirect likelihood function testing method is also proposed to solve the problems of both electricity meter dynamic error testing and dynamic reference electrical energy traceability. At last, a dynamic error testing system is built for verifying the indirect testing method under orthogonal pseudo random distorted dynamic test signal conditions, the dynamic errors of different electricity meters are given. Experimental results show that the orthogonal pseudo random distorted dynamic test signal and the indirect likelihood function testing method are effective for dynamic error testing of electricity meters, meanwhile, the measurement uncertainty of the dynamic error testing system is better than 0.042% (coverage factor k = 2).

Large families of pseudorandom binary lattices by using the multiplicative inverse modulo P

Hubert, Mauduit and Sárközy introduced pseudorandom measures for finite pseudorandom binary lattices. Gyarmati, Mauduit, Sárközy and Stewart presented some natural and flexible constructions, which are the two-dimensional extensions and modifications of a few one-dimensional constructions. The upper estimates for the pseudorandom measures of their binary lattices are based on the principle that character sums or exponential sums in two variables can be estimated by fixing one of the variables. In this paper, we constructed two large families of [Formula: see text] dimensional pseudorandom binary lattices by using the multiplicative inverse modulo [Formula: see text], and study the properties: pseudorandom measure, collision and avalanche effect.

Single-Pixel Color Imaging Method with a Compressive Sensing Measurement Matrix

Compressive sensing theory has addressed the limitations of traditional methods in the field of information technology, and led to a revolution. On the basis of compressive sensing theory research, this study utilized the exterior determinacy and inherent randomness of chaotic sequences, designed a pseudo-random circulant measurement matrix based on chaotic sequence. Compared with other deterministic measurement matrices, the restoration effect of the designed measurement matrix remarkably improved and showed advantages in hardware and storage. Then, this study developed a single-pixel imaging scheme that could accurately obtain color information. The proposed improved measurement matrix combined with the hardware system could accurately reconstruct color images and had good robustness according to various experimental data.

Hamming correlation of higher order

We introduce a new measure of pseudorandomness, the (periodic) Hamming correlation of order $\ell$ which generalizes the Hamming autocorrelation ($\ell = 2$). We analyze the relation between the Hamming correlation of order $\ell$ and the periodic analog of the correlation measure of order $\ell$ introduced by Mauduit and Sárközy. Roughly speaking, the correlation measure of order $\ell$ is a finer measure than the Hamming correlation of order $\ell$. However, the latter can be much faster calculated and still detects some undesirable linear structures. We analyze examples of sequences with optimal Hamming correlation and show that they have large Hamming correlation of order $\ell$ for some very small $\ell&gt;2$. Thus they have some undesirable linear structures, in particular in view of cryptographic applications such as secure communications.

On multi-dimensional pseudorandom subsets

TextIn a series of papers C. Dartyge and A. Sárközy (partly with other coauthors) studied pseudorandom measures of subsets. In this paper we extend the theory of C. Dartyge and A. Sárközy to several dimensions. We introduce measure for multi-dimensional pseudorandom subsets, and study the connection between measures of different orders. Large families of multi-dimensional pseudorandom subsets are given by using the squares in Fq. VideoFor a video summary of this paper, please visit https://youtu.be/7iH9x7nyyfQ.