Sana Boujnah

11 papers C 6Misc 2Journal 2Unranked 1

Year	Rank	Type	Title / Venue / Authors
2024	Misc	`conf`	A Deep CNN-BiGRU model for Lymphoma and Residual Masses Recognition. ATSIP Radhia Ferjaoui, Sana Boujnah, Anouar Ben Khalifa
2024	Misc	`conf`	A Novel Deep Neural Network Model using Resnet50-BiLSTM for Biometric Ear Recognition in Degraded Conditions. ATSIP Sana Boujnah, Radhia Ferjaoui, Anouar Ben Khalifa
2024	C	`conf`	A Novel Handcrafted Features and Deep BiLSTM Neural Network for Lymphoma Recognition. CoDIT Radhia Ferjaoui, Sana Boujnah, Anouar Ben Khalifa
2023	C	`conf`	A Novel Public Database of Lymphoma for Whole Body Diffusion-Weighted MRI. CW Radhia Ferjaoui, Sana Boujnah, Nour El Houda Kraiem, Tarek Kraiem, Anouar Ben Khalifa
2023	C	`conf`	Hybrid approach for speaker recognition based on formant and pitch extraction. CW Sana Boujnah, Radhia Ferjaoui, Anouar Ben Khalifa
2023	C	`conf`	Person Identification with Voice and Ear-print in Degraded Conditions for Smart Home Access. CW Sana Boujnah, Radhia Ferjaoui, Anouar Ben Khalifa
2021	J	`jnl`	Machine learning for evolutive lymphoma and residual masses recognition in whole body diffusion weighted magnetic resonance images. Comput. Methods Programs Biomed. Radhia Ferjaoui, Mohamed Ali Cherni, Sana Boujnah, Nour El Houda Kraiem, Tarek Kraiem
2020	J	`jnl`	Ear recognition in degraded conditions based on spectral saliency: smart home access. J. Electronic Imaging Sana Boujnah, Sami Jaballah, Mohamed Ali Mahjoub, Mohamed Lassaad Ammari
2018	—	`conf`	3-Step Speaker Identification Approach in Degraded Conditions. SSD Sana Boujnah, Xianfang Sun, A. David Marshall, Paul L. Rosin, Mohamed Lassaad Ammari
2018	C	`conf`	Person's Identification with Partial Fingerprint Based on a Redefinition of Minutiae Features. AICCSA Sana Boujnah, Sami Jaballah, Anouar Ben Khalifa, Mohamed Lassaad Ammari
2018	C	`conf`	Smartphone-Captured Ear and Voice Database in Degraded Conditions. IPAS Sana Boujnah, Sami Jaballah, Mohamed Lassaad Ammari

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.

In 2025, he co-authored Assessing the Effectiveness of the Tigress Obfuscator Against MOPSA and BinaryNinja, published at CheckMATE. The paper evaluates the effectiveness of obfuscation techniques and their impact on source-level static analysis and binary-level decompilation.

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.