Search Results for author: Luca Mariot

Found 23 papers, 4 papers with code

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

no code implementations15 Feb 2024 Claude Carlet, Marko Ðurasevic, Domagoj Jakobovic, Stjepan Picek, Luca Mariot

In the last 30 years, evolutionary algorithms have been shown to be a strong option for evolving Boolean functions in different sizes and with different properties.

Evolutionary Algorithms

A Discrete Particle Swarm Optimizer for the Design of Cryptographic Boolean Functions

no code implementations9 Jan 2024 Luca Mariot, Alberto Leporati, Luca Manzoni

A Particle Swarm Optimizer for the search of balanced Boolean functions with good cryptographic properties is proposed in this paper.

A New Angle: On Evolving Rotation Symmetric Boolean Functions

no code implementations20 Nov 2023 Claude Carlet, Marko Ðurasevic, Bruno Gašperov, Domagoj Jakobovic, Luca Mariot, Stjepan Picek

Rotation symmetric Boolean functions represent an interesting class of Boolean functions as they are relatively rare compared to general Boolean functions.

Evolutionary Algorithms

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

no code implementations20 Nov 2023 Claude Carlet, Marko Ðurasevic, Domagoj Jakobovic, Luca Mariot, Stjepan Picek

This paper provides a detailed experimentation with evolutionary algorithms with the goal of evolving (anti-)self-dual bent Boolean functions.

Evolutionary Algorithms

Local Search, Semantics, and Genetic Programming: a Global Analysis

no code implementations26 May 2023 Fabio Anselmi, Mauro Castelli, Alberto D'Onofrio, Luca Manzoni, Luca Mariot, Martina Saletta

In recent years, a new mutation operator, Geometric Semantic Mutation with Local Search (GSM-LS), has been proposed to include a local search step in the mutation process based on the idea that performing a linear regression during the mutation can allow for a faster convergence to good-quality solutions.


Digging Deeper: Operator Analysis for Optimizing Nonlinearity of Boolean Functions

no code implementations12 Feb 2023 Marko Djurasevic, Domagoj Jakobovic, Luca Mariot, Stjepan Picek

By observing the range of possible changes an operator can provide, as well as relative probabilities of specific transitions in the objective space, one can use this information to design a more effective combination of genetic operators.

Combinatorial Optimization

NASCTY: Neuroevolution to Attack Side-channel Leakages Yielding Convolutional Neural Networks

no code implementations25 Jan 2023 Fiske Schijlen, Lichao Wu, Luca Mariot

Side-channel analysis (SCA) can obtain information related to the secret key by exploiting leakages produced by the device.

Side Channel Analysis

On the Evolution of Boomerang Uniformity in Cryptographic S-boxes

no code implementations9 Dec 2022 Marko Djurasevic, Domagoj Jakobovic, Luca Mariot, Sihem Mesnager, Stjepan Picek

One example of such a property is called boomerang uniformity, which helps to be resilient against boomerang attacks.

Evolutionary Strategies for the Design of Binary Linear Codes

no code implementations21 Nov 2022 Claude Carlet, Luca Mariot, Luca Manzoni, Stjepan Picek

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 metaheuristic techniques and evolutionary algorithms.

Evolutionary Algorithms

The Influence of Local Search over Genetic Algorithms with Balanced Representations

no code implementations22 Jun 2022 Luca Manzoni, Luca Mariot, Eva Tuba

We continue the study of Genetic Algorithms (GA) on combinatorial optimization problems where the candidate solutions need to satisfy a balancedness constraint.

Combinatorial Optimization

The Effect of Multi-Generational Selection in Geometric Semantic Genetic Programming

no code implementations5 May 2022 Mauro Castelli, Luca Manzoni, Luca Mariot, Giuliamaria Menara, Gloria Pietropolli

Among the evolutionary methods, one that is quite prominent is Genetic Programming, and, in recent years, a variant called Geometric Semantic Genetic Programming (GSGP) has shown to be successfully applicable to many real-world problems.

Evolving Constructions for Balanced, Highly Nonlinear Boolean Functions

no code implementations17 Feb 2022 Claude Carlet, Marko Djurasevic, Domagoj Jakobovic, Luca Mariot, Stjepan Picek

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.

Evolutionary Algorithms

Modeling Strong Physically Unclonable Functions with Metaheuristics

no code implementations16 Feb 2022 Carlos Coello Coello, Marko Djurasevic, Domagoj Jakobovic, Luca Mariot, Stjepan Picek

While there is no reason to doubt the performance of CMA-ES, the lack of comparison with different metaheuristics and results for the challenge-response pair-based attack leaves open questions if there are better-suited metaheuristics for the problem.

Evolutionary Algorithms

Evolutionary Construction of Perfectly Balanced Boolean Functions

no code implementations16 Feb 2022 Luca Mariot, Stjepan Picek, Domagoj Jakobovic, Marko Djurasevic, Alberto Leporati

Finding Boolean functions suitable for cryptographic primitives is a complex combinatorial optimization problem, since they must satisfy several properties to resist cryptanalytic attacks, and the space is very large, which grows super exponentially with the number of input variables.

Combinatorial Optimization

Deriving Smaller Orthogonal Arrays from Bigger Ones with Genetic Algorithm

no code implementations25 Nov 2021 Luca Mariot

We consider the optimization problem of constructing a binary orthogonal array (OA) starting from a bigger one, by removing a specified amount of lines.

Salp Swarm Optimization: a Critical Review

1 code implementation3 Jun 2021 Mauro Castelli, Luca Manzoni, Luca Mariot, Marco S. Nobile, Andrea Tangherloni

In the crowded environment of bio-inspired population-based metaheuristics, the Salp Swarm Optimization (SSO) algorithm recently appeared and immediately gained a lot of momentum.

Evolutionary Algorithms for Designing Reversible Cellular Automata

1 code implementation25 May 2021 Luca Mariot, Stjepan Picek, Domagoj Jakobovic, Alberto Leporati

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

Evolutionary Algorithms

CoInGP: Convolutional Inpainting with Genetic Programming

1 code implementation23 Apr 2020 Domagoj Jakobovic, Luca Manzoni, Luca Mariot, Stjepan Picek, Mauro Castelli

In the second experiment, we train a GP convolutional predictor on two degraded images, removing around 20% of their pixels.

Tip the Balance: Improving Exploration of Balanced Crossover Operators by Adaptive Bias

no code implementations23 Apr 2020 Luca Manzoni, Luca Mariot, Eva Tuba

Experiments show that improving the exploration of the search space with this adaptive bias strategy is beneficial for the GA performances in terms of the number of optimal solutions found for the balanced nonlinear Boolean functions problem.

Towards an evolutionary-based approach for natural language processing

no code implementations23 Apr 2020 Luca Manzoni, Domagoj Jakobovic, Luca Mariot, Stjepan Picek, Mauro Castelli

Tasks related to Natural Language Processing (NLP) have recently been the focus of a large research endeavor by the machine learning community.


Balanced Crossover Operators in Genetic Algorithms

1 code implementation23 Apr 2019 Luca Manzoni, Luca Mariot, Eva Tuba

Furthermore, in two out of three crossovers, the "left-to-right" version performs better than the "shuffled" version.

Combinatorial Optimization

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