- Distributed systems and fault tolerance
- Service-Oriented Architecture and Web Services
- Privacy, Security, and Data Protection
- Privacy-Preserving Technologies in Data
- Peer-to-Peer Network Technologies
- Access Control and Trust
- Cryptography and Data Security
- Internet Traffic Analysis and Secure E-voting
- Distributed and Parallel Computing Systems
- Usability and User Interface Design
- Semantic Web and Ontologies
- Advanced Database Systems and Queries
- Caching and Content Delivery
- Spam and Phishing Detection
- Hate Speech and Cyberbullying Detection
- IoT and Edge/Fog Computing
- Logic, programming, and type systems
- Context-Aware Activity Recognition Systems
- Authorship Attribution and Profiling
- Imbalanced Data Classification Techniques
- Formal Methods in Verification
- Web Data Mining and Analysis
- Complex Network Analysis Techniques
- Model-Driven Software Engineering Techniques
- Advanced Malware Detection Techniques
Université de Lorraine
2016-2025
Laboratoire Lorrain de Recherche en Informatique et ses Applications
2015-2025
Centre National de la Recherche Scientifique
2007-2025
Institut national de recherche en informatique et en automatique
2014-2024
Centre Inria de l'Université de Lorraine
2013-2023
Politecnico di Milano
2022
Nottingham Trent University
2022
Peer-to-peer (P2P) networks are very efficient for distributing content. We want to use this potential allow not only distribution but collaborative editing of Existing systems centralised or depend on the number sites. Such cannot scale when deployed P2P networks. In paper, we propose a new model building system. This is fully decentralised and does
Credit card fraud is a significant problem, with millions of dollars lost each year. Detecting fraudulent transactions challenging task due to the large volume data and constantly evolving tactics fraudsters. Likewise any detection it important select relevant features that help distinguishing between non-fraudulent transactions. It also crucial design model effectively captures relationships involved entities such as merchants customers. In this work, prior stage feature engineering carried...
Differential privacy (DP) is considered as the gold standard for data privacy. While problem of answering simple queries and functions under DP guarantees has been thoroughly addressed in recent years, releasing multidimensional remains challenging. In this paper, we focus on problem, particular how to construct privacy-preserving views using a domain decomposition approach. The main idea recursively split into sub-domains until convergence condition met. resulting are perturbed then...
The internet has been inundated with an ocean of information, and hence, information retrieval systems are failing to provide optimal results the user. In order meet challenge, query expansion techniques have emerged as a game-changer improving significantly. Of late, semantic attracted increased interest among researchers since these offer more pertinent practical users. These allow user retrieve meaningful useful from web. Currently, few research works comprehensive review on expansion;...
In collaborative editing, consistency maintenance of the copies shared data is a critical issue. last decade, operational transformation (OT) approach revealed as suitable mechanism for maintaining consistency. Unfortunately, none published propositions relying on this are able to satisfy mandatory correctness properties TP <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> and xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> defined in...
Reconciliating divergent data is an important issue in concurrent engineering, mobile computing and software configuration management. Currently, a lot of synchronizers or merge tools perform reconciliations. However, they do not define what the correctness their synchronisation. In this paper, we propose to use transformational approach as basic model for reasonning about We algorithm specific transformation functions that realize file system Unlike classic synchronizers, our synchronizer...
Complex networks usually expose community structure with groups of nodes sharing many links the other in same group and relatively few rest. This feature captures valuable information about organization even evolution network. Over last decade, a great number algorithms for detection have been proposed to deal increasingly complex networks. However, problem doing this private manner is rarely considered. In paper, we solve under differential privacy, prominent privacy concept releasing data....
Rather than anonymizing social graphs by generalizing them to super nodes/edges or adding/removing nodes and edges satisfy given privacy parameters, recent methods exploit the semantics of uncertain achieve protection participating entities their relationships. These techniques anonymize a deterministic graph converting it into an form. In this paper, we propose general obfuscation model based on adjacency matrices that keep expected node degrees equal those in unanonymized graph. We analyze...
The problem of private publication graph data has attracted a lot attention recently. prevalence differential privacy makes the more promising. However, large body existing works on differentially release graphs have not answered question about upper bounds budgets. In this paper, for first time, such bound is provided. We prove that with budget O(log n), there exists an algorithm capable releasing noisy output edge edit distance O(1) against true graph. At same complexity our Top-m Filter...
The operational transformation (OT) approach, used in many collaborative editors, allows a group of users to concurrently update replicas shared object and exchange their updates any order. basic idea is transform received operation before its execution on replica the object. Concretely, OT consists centralized/decentralized integration procedure function. In context decentralized integration, designing functions for achieving convergence critical challenging issue. Indeed, proposed...
Online Social Network (OSN) profiles help users to create first impressions on other and therefore lead various social benefits. However, can become the victims of privacy harms such as identity theft, stalking or discrimination due personal data revealed in these profiles. So they have carefully select settings for their profile attributes, keeping mind this trade-off between benefit. Since a consists several attributes usually do not fully understand how revelation different attribute...