Gabriel Zaid - RankMe

19 papers Journal 16Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	From linear regression to generative model for explainable non profiled side-channel attacks. IACR Cryptol. ePrint Arch. Sana Boussam, Mathieu Carbone, Benoît Gérard, Guénaël Renault, Gabriel Zaid
2025	J	`jnl`	Optimal Dimensionality Reduction using Conditional Variational AutoEncoder. IACR Cryptol. ePrint Arch. Sana Boussam, Mathieu Carbone, Benoît Gérard, Guénaël Renault, Gabriel Zaid
2025	J	`jnl`	Optimal Dimensionality Reduction using Conditional Variational AutoEncoder. IACR Trans. Cryptogr. Hardw. Embed. Syst. Sana Boussam, Mathieu Carbone, Benoît Gérard, Guénaël Renault, Gabriel Zaid
2024	J	`jnl`	A Hard-Label Cryptanalytic Extraction of Non-Fully Connected Deep Neural Networks using Side-Channel Attacks. CoRR Benoît Coqueret, Mathieu Carbone, Olivier Sentieys, Gabriel Zaid
2024	J	`jnl`	A Hard-Label Cryptanalytic Extraction of Non-Fully Connected Deep Neural Networks using Side-Channel Attacks. IACR Cryptol. ePrint Arch. Benoît Coqueret, Mathieu Carbone, Olivier Sentieys, Gabriel Zaid
2023	J	`jnl`	Conditional Variational AutoEncoder based on Stochastic Attacks. IACR Trans. Cryptogr. Hardw. Embed. Syst. Gabriel Zaid, Lilian Bossuet, Mathieu Carbone, Amaury Habrard, Alexandre Venelli
2023	—	`conf`	When Side-Channel Attacks Break the Black-Box Property of Embedded Artificial Intelligence. AISec@CCS Benoît Coqueret, Mathieu Carbone, Olivier Sentieys, Gabriel Zaid
2023	J	`jnl`	When Side-Channel Attacks Break the Black-Box Property of Embedded Artificial Intelligence. CoRR Benoît Coqueret, Mathieu Carbone, Olivier Sentieys, Gabriel Zaid
2022	J	`jnl`	Conditional Variational AutoEncoder based on Stochastic Attack. IACR Cryptol. ePrint Arch. Gabriel Zaid, Lilian Bossuet, Mathieu Carbone, Amaury Habrard, Alexandre Venelli
2021	—	`—`	Bridging Deep Learning and Classical Profiled Side-Channel Attacks. (Rapprochement de l'apprentissage profond et des attaques par canaux auxiliaires). Gabriel Zaid
2021	J	`jnl`	Efficiency through Diversity in Ensemble Models applied to Side-Channel Attacks - A Case Study on Public-Key Algorithms -. IACR Cryptol. ePrint Arch. Gabriel Zaid, Lilian Bossuet, Amaury Habrard, Alexandre Venelli
2021	J	`jnl`	Efficiency through Diversity in Ensemble Models applied to Side-Channel Attacks - A Case Study on Public-Key Algorithms -. IACR Trans. Cryptogr. Hardw. Embed. Syst. Gabriel Zaid, Lilian Bossuet, Amaury Habrard, Alexandre Venelli
2021	J	`jnl`	Ranking Loss: Maximizing the Success Rate in Deep Learning Side-Channel Analysis. IACR Trans. Cryptogr. Hardw. Embed. Syst. Gabriel Zaid, Lilian Bossuet, François Dassance, Amaury Habrard, Alexandre Venelli
2020	J	`jnl`	Methodology for Efficient CNN Architectures in Profiling Attacks. IACR Trans. Cryptogr. Hardw. Embed. Syst. Gabriel Zaid, Lilian Bossuet, Amaury Habrard, Alexandre Venelli
2020	—	`conf`	Online Performance Evaluation of Deep Learning Networks for Profiled Side-Channel Analysis. COSADE Damien Robissout, Gabriel Zaid, Brice Colombier, Lilian Bossuet, Amaury Habrard
2020	J	`jnl`	Online Performance Evaluation of Deep Learning Networks for Side-Channel Analysis. IACR Cryptol. ePrint Arch. Damien Robissout, Gabriel Zaid, Brice Colombier, Lilian Bossuet, Amaury Habrard
2020	J	`jnl`	Ranking Loss: Maximizing the Success Rate in Deep Learning Side-Channel Analysis. IACR Cryptol. ePrint Arch. Gabriel Zaid, Lilian Bossuet, François Dassance, Amaury Habrard, Alexandre Venelli
2020	J	`jnl`	Understanding Methodology for Efficient CNN Architectures in Profiling Attacks. IACR Cryptol. ePrint Arch. Gabriel Zaid, Lilian Bossuet, Amaury Habrard, Alexandre Venelli
2019	J	`jnl`	Methodology for Efficient CNN Architectures in Profiling Attacks. IACR Cryptol. ePrint Arch. Gabriel Zaid, Lilian Bossuet, Amaury Habrard, Alexandre Venelli

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.