Enes Pasalic

Almost Fully Optimized Infinite Classes of Boolean Functions Resistant to (Fast) Algebraic Cryptanalysis

In this paper the possibilities of an iterative concatenation method towards construction of Boolean functions resistant to algebraic cryptanalysis are investigated. The notion of

Constructions of Resilient S-Boxes With Strictly Almost Optimal Nonlinearity Through Disjoint Linear Codes

\mathcal{AAR}

Generalized Maiorana-McFarland Construction of Resilient Boolean Functions With High Nonlinearity and Good Algebraic Properties

(Algebraic Attack Resistant) function is introduced as a unified measure of protection against classical algebraic attacks as well as fast algebraic attacks. Then, it is shown that functions that posses the highest resistance to fast algebraic attacks are necessarily of maximum

Meet-in-the-Middle Attack on Reduced Versions of the Camellia Block Cipher

\mathcal{AI}

A Note on Generalized Bent Criteria for Boolean Functions

(Algebraic Immunity ), the notion introduced in [20] defined as a minimum degree of functions that annihilate either f or 1 + f . More precisely, if for any non-annihilating function g of degree e an optimum degree relation e + d *** n is satisfied in the product fg = h (denoting deg (h ) = d ), then the function f in n variables must have maximum

Constructions of Bent—Negabent Functions and Their Relation to the Completed Maiorana—McFarland Class

\mathcal{AI}

Generalized Bent Functions - Some General Construction Methods and Related Necessary and Sufficient Conditions

, i.e. for nonzero function g the relation fg = 0 or (1 + f )g = 0 implies

The Higher-Order Meet-in-the-Middle Attack and Its Application to the Camellia Block Cipher

deg(g)\geq \frac{n}{2}

Probabilistic Versus Deterministic Algebraic Cryptanalysis—A Performance Comparison

. The presented theoretical framework allows us to iteratively construct functions with maximum

On the Construction of Cryptographically Significant Boolean Functions Using Objects in Projective Geometry Spaces

\mathcal{AI}