Abdessamad Imine

Aurel Randolph, Hanifa Boucheneb, Abdessamad Imine et al.

The Operational Transformation (OT) approach, used in many collaborative editors, allows a group of users to concurrently update replicas of a shared object and exchange their updates in any order. The basic idea of this approach is to transform any received update operation before its execution on a replica of the object. This transformation aims to ensure the convergence of the different replicas of the object, even though the operations are executed in different orders. However, designing transformation functions for achieving convergence is a critical and challenging issue. Indeed, the transformation functions proposed in the literature are all revealed incorrect. In this paper, we investigate the existence of transformation functions for a shared string altered by insert and delete operations. From the theoretical point of view, two properties - named TP1 and TP2 - are necessary and sufficient to ensure convergence. Using controller synthesis technique, we show that there are some transformation functions which satisfy only TP1 for the basic signatures of insert and delete operations. As a matter of fact, it is impossible to meet both properties TP1 and TP2 with these simple signatures.

Wail Zellagui, Abdessamad Imine, Yamina Tadjeddine

Recent advances in the field of large language models (LLMs), particularly the ChatGPT family, have given rise to a powerful and versatile machine interlocutor, packed with knowledge and challenging our understanding of learning. This interlocutor is a double-edged sword: it can be harnessed for a wide variety of beneficial tasks, but it can also be used to cause harm. This study explores the complicated interaction between ChatGPT and the growing problem of cryptocurrency fraud. Although ChatGPT is known for its adaptability and ethical considerations when used for harmful purposes, we highlight the deep connection that may exist between ChatGPT and fraudulent actions in the volatile cryptocurrency ecosystem. Based on our categorization of cryptocurrency frauds, we show how to influence outputs, bypass ethical terms, and achieve specific fraud goals by manipulating ChatGPT prompts. Furthermore, our findings emphasize the importance of realizing that ChatGPT could be a valuable instructor even for novice fraudsters, as well as understanding and safely deploying complex language models, particularly in the context of cryptocurrency frauds. Finally, our study underlines the importance of using LLMs responsibly and ethically in the digital currency sector, identifying potential risks and resolving ethical issues. It should be noted that our work is not intended to encourage and promote fraud, but rather to raise awareness of the risks of fraud associated with the use of ChatGPT.

Hiep H. Nguyen, Abdessamad Imine, Michael Rusinowitch

Currently, most of the online social networks (OSN) keep their data secret and in centralized manner. Researchers are allowed to crawl the underlying social graphs (and data) but with limited rates, leading to only partial views of the true social graphs. To overcome this constraint, we may start from user perspective, the contributors of the OSNs. More precisely, if users cautiously collaborate with one another, they can use the very infrastructure of the OSNs to exchange noisy friend lists with their neighbors in several rounds. In the end, they can build local subgraphs, also called local views of the true social graph. In this paper, we propose such protocols for the problem of \textit{private link exchange} over social graphs. The problem is unique in the sense that the disseminated data over the links are the links themselves. However, there exist fundamental questions about the feasibility of this model. The first question is how to define simple and effective privacy concepts for the link exchange processes. The second question comes from the high volume of link lists in exchange which may increase exponentially round after round. While storage and computation complexity may be affordable for desktop PCs, communication costs are non-trivial. We address both questions by a simple $(α,β)$-exchange using Bloom filters.

Houari Mahfoud, Abdessamad Imine

Over the past years several works have proposed access control models for XML data where only read-access rights over non-recursive DTDs are considered. A few amount of works have studied the access rights for updates. In this paper, we present a general model for specifying access control on XML data in the presence of update operations of W3C XQuery Update Facility. Our approach for enforcing such updates specifications is based on the notion of query rewriting where each update operation defined over arbitrary DTD (recursive or not) is rewritten to a safe one in order to be evaluated only over XML data which can be updated by the user. We investigate in the second part of this report the secure of XML updating in the presence of read-access rights specified by a security views. For an XML document, a security view represents for each class of users all and only the parts of the document these users are able to see. We show that an update operation defined over a security view can cause disclosure of sensitive data hidden by this view if it is not thoroughly rewritten with respect to both read and update access rights. Finally, we propose a security view based approach for securely updating XML in order to preserve the confidentiality and integrity of XML data.