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20182026
most citedCan You Hear It? Backdoor Attacks via Ultrasonic Triggers

37 citations · 224 across the 83 of their papers we have counts for

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cs.NE2026

Monotone but Exciting: On Evolving Monotone Boolean Functions with High Nonlinearity

Claude Carlet, Marko Čupić, Marko Ðurasevic +3

Monotone Boolean functions are a structurally important class of Boolean functions, but their restricted form imposes strong limitations on achievable nonlinearity. In this paper,…

cs.NE2026

NegaBent, No Regrets: Evolving Spectrally Flat Boolean Functions

Claude Carlet, Marko Ðurasevic, Ermes Franch +3

Negabent Boolean functions are defined by having a flat magnitude spectrum under the nega-Hadamard transform. They exist in both even and odd dimensions, and the subclass of functi…

cs.NE2025

On Counts and Densities of Homogeneous Bent Functions: An Evolutionary Approach

Claude Carlet, Marko Ðurasevic, Domagoj Jakobovic +3

Boolean functions with strong cryptographic properties, such as high nonlinearity and algebraic degree, are important for the security of stream and block ciphers. These functions…

cs.NE2025

A Systematic Study on the Design of Odd-Sized Highly Nonlinear Boolean Functions via Evolutionary Algorithms

Claude Carlet, Marko Đurasevic, Domagoj Jakobovic +2

This paper focuses on the problem of evolving Boolean functions of odd sizes with high nonlinearity, a property of cryptographic relevance. Despite its simple formulation, this pro…

cs.NE2025

Degree is Important: On Evolving Homogeneous Boolean Functions

Claude Carlet, Marko Ðurasevic, Domagoj Jakobovic +2

Boolean functions with good cryptographic properties like high nonlinearity and algebraic degree play an important in the security of stream and block ciphers. Such functions may b…

cs.NE2024

The More the Merrier: On Evolving Five-valued Spectra Boolean Functions

Claude Carlet, Marko Ðurasevic, Domagoj Jakobovic +2

Evolving Boolean functions with specific properties is an interesting optimization problem since, depending on the combination of properties and Boolean function size, the problem…

cs.NE2024

A Systematic Evaluation of Evolving Highly Nonlinear Boolean Functions in Odd Sizes

Claude Carlet, Marko Ðurasevic, Domagoj Jakobovic +2

Boolean functions are mathematical objects used in diverse applications. Different applications also have different requirements, making the research on Boolean functions very acti…

cs.NE2023

Look into the Mirror: Evolving Self-Dual Bent Boolean Functions

Claude Carlet, Marko Ðurasevic, Domagoj Jakobovic +2

Bent Boolean functions are important objects in cryptography and coding theory, and there are several general approaches for constructing such functions. Metaheuristics proved to b…

cs.NE2023

A New Angle: On Evolving Rotation Symmetric Boolean Functions

Claude Carlet, Marko Ðurasevic, Bruno Gašperov +3

Rotation symmetric Boolean functions represent an interesting class of Boolean functions as they are relatively rare compared to general Boolean functions. At the same time, the fu…

cs.NE2023

Digging Deeper: Operator Analysis for Optimizing Nonlinearity of Boolean Functions

Marko Djurasevic, Domagoj Jakobovic, Luca Mariot +1

Boolean functions are mathematical objects with numerous applications in domains like coding theory, cryptography, and telecommunications. Finding Boolean functions with specific p…

cs.NE2022

On the Evolution of Boomerang Uniformity in Cryptographic S-boxes

Marko Djurasevic, Domagoj Jakobovic, Luca Mariot +2

S-boxes are an important primitive that help cryptographic algorithms to be resilient against various attacks. The resilience against specific attacks can be connected with a certa…

cs.NE2022

Evolutionary Strategies for the Design of Binary Linear Codes

Claude Carlet, Luca Mariot, Luca Manzoni +1

The design of binary error-correcting codes is a challenging optimization problem with several applications in telecommunications and storage, which has also been addressed with me…

cs.NE2022★ 1 cited

Evolving Constructions for Balanced, Highly Nonlinear Boolean Functions

Claude Carlet, Marko Djurasevic, Domagoj Jakobovic +2

Finding balanced, highly nonlinear Boolean functions is a difficult problem where it is not known what nonlinearity values are possible to be reached in general. At the same time,…

cs.NE2022★ 2 cited

Evolutionary Construction of Perfectly Balanced Boolean Functions

Luca Mariot, Stjepan Picek, Domagoj Jakobovic +2

Finding Boolean functions suitable for cryptographic primitives is a complex combinatorial optimization problem, since they must satisfy several properties to resist cryptanalytic…

cs.NE2022

Modeling Strong Physically Unclonable Functions with Metaheuristics

Carlos Coello Coello, Marko Djurasevic, Domagoj Jakobovic +2

Evolutionary algorithms have been successfully applied to attacking Physically Unclonable Functions (PUFs). CMA-ES is recognized as the most powerful option for a type of attack ca…

cs.NE2021

On the Difficulty of Evolving Permutation Codes

Luca Mariot, Stjepan Picek, Domagoj Jakobovic +2

Combinatorial designs provide an interesting source of optimization problems. Among them, permutation codes are particularly interesting given their applications in powerline commu…

cs.NE2021

Evolutionary Algorithms for Designing Reversible Cellular Automata

Luca Mariot, Stjepan Picek, Domagoj Jakobovic +1

Reversible Cellular Automata (RCA) are a particular kind of shift-invariant transformations characterized by a dynamics composed only of disjoint cycles. They have many application…

cs.NE2021

On the Genotype Compression and Expansion for Evolutionary Algorithms in the Continuous Domain

Lucija Planinic, Marko Djurasevic, Luca Mariot +3

This paper investigates the influence of genotype size on evolutionary algorithms' performance. We consider genotype compression (where genotype is smaller than phenotype) and expa…

cs.NE2020

Fitness Landscape Analysis of Dimensionally-Aware Genetic Programming Featuring Feynman Equations

Marko Durasevic, Domagoj Jakobovic, Marcella Scoczynski Ribeiro Martins +2

Genetic programming is an often-used technique for symbolic regression: finding symbolic expressions that match data from an unknown function. To make the symbolic regression more…

cs.NE2020

CoInGP: Convolutional Inpainting with Genetic Programming

Domagoj Jakobovic, Luca Manzoni, Luca Mariot +2

We investigate the use of Genetic Programming (GP) as a convolutional predictor for missing pixels in images. The training phase is performed by sweeping a sliding window over an i…

cs.NE2019

A characterisation of S-box fitness landscapes in cryptography

Domagoj Jakobovic, Stjepan Picek, Marcella S. R. Martins +1

Substitution Boxes (S-boxes) are nonlinear objects often used in the design of cryptographic algorithms. The design of high quality S-boxes is an interesting problem that attracts…