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Daniela Mueller

Publications and source records attributed to Daniela Mueller.

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Stronger bounds on the cost of computing Groebner bases for HFE systems

We give upper bounds for the solving degree and the last fall degree of the polynomial system associated to the HFE (Hidden Field Equations) cryptosystem. Our bounds improve the known bounds for this type of systems. We also present new results on the connection between the solving degree and the last fall degree and prove that, in some cases, the solving degree is independent of coordinate changes.

cs.CR

Some Results on Linearized Trinomials that Split Completely

Linearized polynomials over finite fields have been much studied over the last several decades. Recently there has been a renewed interest in linearized polynomials because of new connections to coding theory and finite geometry. We consider the problem of calculating the rank or nullity of a linearized polynomial $L(x)=\sum_{i=0}^{d}a_i x^{q^i}$ (where $a_i\in \mathbb{F}_{q^n}$) from the coefficients $a_i$. The rank and nullity of $L(x)$ are the rank and nullity of the associated $\mathbb{F}_q$-linear map $\mathbb{F}_{q^n} \longrightarrow \mathbb{F}_{q^n}$. McGuire and Sheekey defined a $d\times d$ matrix $A_L$ with the property that $$\mbox{nullity} (L)=\mbox{nullity} (A_L -I).$$ We present some consequences of this result for some trinomials that split completely, i.e., trinomials $L(x)=x^{q^d}-bx^q-ax$ that have nullity $d$. We give a full characterization of these trinomials for $n\le d^2-d+1$.

math.NT

On the Termination of the General XL Algorithm and Ordinary Multinomials

The XL algorithm is an algorithm for solving overdetermined systems of multivariate polynomial equations, which was initially introduced for quadratic equations. However, the algorithm works for polynomials of any degree, and in this paper we will focus on the performance of XL for polynomials of degree $\geq3$, where the optimal termination value of the parameter $D$ is still unknown. We prove that the XL algorithm terminates at a certain value of $D$ in the case that the number of equations exceeds the number of variables by 1 or 2. We also give strong evidence that this value is best possible, and we show that this value is smaller than the degree of regularity. Part of our analysis requires proving that ordinary multinomials are strongly unimodal, and this result may be of independent interest.

math.AC