29 citations · 139 across the 31 of their papers we have counts for
34 papers
A Dual Perspective on Synthetic Trajectory Generators: Utility Framework and Privacy Vulnerabilities
Aya Cherigui, Florent Guépin, Arnaud Legendre +1
Human mobility data are used in numerous applications, ranging from public health to urban planning. Human mobility is inherently sensitive, as it can contain information such as r…
Experiments \& Analysis of Privacy-Preserving SQL Query Sanitization Systems
Loïs Ecoffet, Veronika Rehn-Sonigo, Jean-François Couchot +1
Analytical SQL queries are essential for extracting insights from relational databases but concurrently introduce significant privacy risks by potentially exposing sensitive inform…
Automatic ICD-10 Code Association: A Challenging Task on French Clinical Texts
Yakini Tchouka, Jean-François Couchot, David Laiymani +2
Automatically associating ICD codes with electronic health data is a well-known NLP task in medical research. NLP has evolved significantly in recent years with the emergence of pr…
An Easy-to-use and Robust Approach for the Differentially Private De-Identification of Clinical Textual Documents
Yakini Tchouka, Jean-François Couchot, David Laiymani
Unstructured textual data is at the heart of healthcare systems. For obvious privacy reasons, these documents are not accessible to researchers as long as they contain personally i…
In-stream Probabilistic Cardinality Estimation for Bloom Filters
Remy Scholler, Jean-Francois Couchot, Oumaima Alaoui-Ismaili +2
The amount of data coming from different sources such as IoT-sensors, social networks, cellular networks, has increased exponentially during the last few years. Probabilistic Data…
Differentially Private Multivariate Time Series Forecasting of Aggregated Human Mobility With Deep Learning: Input or Gradient Perturbation?
Héber H. Arcolezi, Jean-François Couchot, Denis Renaud +2
This paper investigates the problem of forecasting multivariate aggregated human mobility while preserving the privacy of the individuals concerned. Differential privacy, a state-o…
Multi-Freq-LDPy: Multiple Frequency Estimation Under Local Differential Privacy in Python
Héber H. Arcolezi, Jean-François Couchot, Sébastien Gambs +2
This paper introduces the multi-freq-ldpy Python package for multiple frequency estimation under Local Differential Privacy (LDP) guarantees. LDP is a gold standard for achieving l…
Improving the utility of locally differentially private protocols for longitudinal and multidimensional frequency estimates
Héber H. Arcolezi, Jean-François Couchot, Bechara Al Bouna +1
This paper investigates the problem of collecting multidimensional data throughout time (i.e., longitudinal studies) for the fundamental task of frequency estimation under Local Di…
Random Sampling Plus Fake Data: Multidimensional Frequency Estimates With Local Differential Privacy
Héber H. Arcolezi, Jean-François Couchot, Bechara Al Bouna +1
With local differential privacy (LDP), users can privatize their data and thus guarantee privacy properties before transmitting it to the server (a.k.a. the aggregator). One primar…
Safe Disassociation of Set-Valued Datasets
Nancy Awad, Bechara Al Bouna, Jean-Francois Couchot +1
Disassociation introduced by Terrovitis et al. is a bucketization based anonimyzation technique that divides a set-valued dataset into several clusters to hide the link between ind…
A Robust Data Hiding Process Contributing to the Development of a Semantic Web
Jacques M. Bahi, Jean-François Couchot, Nicolas Friot +1
In this paper, a novel steganographic scheme based on chaotic iterations is proposed. This research work takes place into the information hiding framework, and focus more specifica…
Traversing a n-cube without Balanced Hamiltonian Cycle to Generate Pseudorandom Numbers
Jean-François Couchot, Pierre-Cyrille Heam, Christophe Guyeux +2
This article presents a new class of Pseudorandom Number Generators. The generators are based on traversing a n-cube where a Balanced Hamiltonian Cycle has been removed. The constr…
Well-supported phylogenies using largest subsets of core-genes by discrete particle swarm optimization
Reem Alsrraj, Bassam AlKindy, Christophe Guyeux +2
The number of complete chloroplastic genomes increases day after day, making it possible to rethink plants phylogeny at the biomolecular era. Given a set of close plants sharing in…
One random jump and one permutation: sufficient conditions to chaotic, statistically faultless, and large throughput PRNG for FPGA
Mohammed Bakiri, Jean-François Couchot, Christophe Guyeux
Sub-categories of mathematical topology, like the mathematical theory of chaos, offer interesting applications devoted to information security. In this research work, we have intro…
On the ability to reconstruct ancestral genomes from Mycobacterium genus
Christophe Guyeux, Bashar Al-Nuaimi, Bassam AlKindy +2
Technical signs of progress during the last decades has led to a situation in which the accumulation of genome sequence data is increasingly fast and cheap. The huge amount of mole…
Random Walk in a N-cube Without Hamiltonian Cycle to Chaotic Pseudorandom Number Generation: Theoretical and Practical Considerations
Sylvain Contassot-Vivier, Jean-François Couchot, Christophe Guyeux +1
Designing a pseudorandom number generator (PRNG) is a difficult and complex task. Many recent works have considered chaotic functions as the basis of built PRNGs: the quality of th…
Improving Blind Steganalysis in Spatial Domain using a Criterion to Choose the Appropriate Steganalyzer between CNN and SRM+EC
Jean-Francois Couchot, Raphaël Couturier, Michel Salomon
Conventional state-of-the-art image steganalysis approaches usually consist of a classifier trained with features provided by rich image models. As both features extraction and cla…
FPGA Implementation of -Linear Pseudorandom Number Generators Based on Zynq MPSoC: a Chaotic Iterations Post Processing Case Study
Mohammed Bakiri, Jean-François Couchot, Christophe Guyeux
Pseudorandom number generation (PRNG) is a key element in hardware security platforms like field-programmable gate array FPGA circuits. In this article, 18 PRNGs belonging in 4 fam…
A Second Order Derivatives based Approach for Steganography
Jean-François Couchot, Raphaël Couturier, Yousra Ahmed Fadil +1
Steganography schemes are designed with the objective of minimizing a defined distortion function. In most existing state of the art approaches, this distortion function is based o…
Binary Particle Swarm Optimization versus Hybrid Genetic Algorithm for Inferring Well Supported Phylogenetic Trees
Bassam AlKindy, Bashar Al-Nuaimi, Christophe Guyeux +4
The amount of completely sequenced chloroplast genomes increases rapidly every day, leading to the possibility to build large-scale phylogenetic trees of plant species. Considering…
Quality Analysis of a Chaotic Proven Keyed Hash Function
Jacques M. Bahi, Jean-François Couchot, Christophe Guyeux
Hash functions are cryptographic tools, which are notably involved in integrity checking and password storage. They are of primary importance to improve the security of exchanges t…
Neural Networks and Chaos: Construction, Evaluation of Chaotic Networks, and Prediction of Chaos with Multilayer Feedforward Networks
Jacques M. Bahi, Jean-François Couchot, Christophe Guyeux +1
Many research works deal with chaotic neural networks for various fields of application. Unfortunately, up to now these networks are usually claimed to be chaotic without any mathe…
Steganalyzer performances in operational contexts
Yousra A. Fadil, Jean-François Couchot, Raphaël Couturier +1
Steganography and steganalysis are two important branches of the information hiding field of research. Steganography methods consist in hiding information in such a way that the se…
Improved Core Genes Prediction for Constructing well-supported Phylogenetic Trees in large sets of Plant Species
Bassam AlKindy, Huda Al-Nayyef, Christophe Guyeux +3
The way to infer well-supported phylogenetic trees that precisely reflect the evolutionary process is a challenging task that completely depends on the way the related core genes h…