Mobile Ad hoc networks attract more attention over the years, but the security matter of this type of network makes it hard  to achieve all of their advantages. Cryptographic key management is the cornerstone for building any robust network  security solution. Identity-based cryptography is a promising solution that resists well the key escrow problem, which is  suitable for Mobile Ad hoc networks. In this paper, we give an overview of the most important identity-based encryption  schemes proposed in the last decade; combined with other techniques to enhance it and provide better results for Mobile  Ad hoc networks. Hence, we give a comparative analysis to highlight their advantages and weaknesses. This work gives  insights into a recent research to point out its interesting features, take advantages of its strength, ovoid its weaknesses and  to lay out the future directions in this area.

Auteurs : Kenza Gasmi, Abdelhabib Bourouis, Rohallah Benaboud

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Special issue of  The 2nd International Conference on Computer Science’s Complex Systems and their  Applications (ICCSA’2021) .

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In this « special issue » on the topic « From Data and Information Processing to Knowledge Organization: Architectures,Models and Systems », seven (07) selected communications have been reviewed by peers in the OCTA Multi-Conference (unifying 4 scientific projects: SIIE, ISKO-Maghreb, CITED and TBMS) in program committees. We consider that this set of proposals, enriched in circumstance of this special issue by its authors at our request, are an excellent engine of current scientific ideas and challenges in the domain concerned in ISKO-Maghreb Society.

Auteur : Sahbi Sidhom

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We intend in this paper to outline one part of the number theory genesis relatively to the equation: a square plus/minus a number equals a square focusing on the Arabic mathematicians’ works, like, for example, those of al-Khazin, Ibn al-Laith, al-Karaji, al-Baghdadi and al-Khallat. We will then briefly describe the occidental tradition relative to his subject threw the works of Fibonacci, Fermat, Frenecle, Euler, and others.

Auteurs : Khaled Kchir, Saif-Eddin Toumi, Foued Nafti

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Today, the world is affected by a new concept of war called terrorism. As plans to face conventional enemies have become unusual against terrorism, there are a necessity for innovative concepts and technologies. In order to support units,  we aim to upgrade the capability of leaders structuring their choices. In this paper, we offer a multi-agent architecture for the planning of actions against terrorist attacks. It is distinguished by decisive policy responses and methodical procedures for managing the situation, as well as by the flexibility to adapt a contingency scenario. We describe the relationship between actors during a terrorist attack in order to establish the best possible distribution of units to  neutralize the enemy.

Auteurs : Oussama Kebir, Issam Nouaouri, Mouna Belhaj, Lamjed Ben Said, Kamel Akrout

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Through this study, we propose an overview of two decades of research on Strategic Environmental Scanning (ESS) and competitive intelligence (CI) in Tunisia. A particular attention is given to Scientific and Technical Scanning (STS) as part of SES practices and as a strong support to R&D activity and  trigger of innovation. The objective of this work is to fill a gap faced by academic researchers interested in issues related to this field of research. The scarcity of meta-analyses within the literature review and retrospective studies could be an obstacle to the cumulative nature of the research and the
capitalization of actionable knowledge from the various investigations.

Auteurs : Souad Kamoun Chouk, Maroua Hammami

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Different diffusion tools within collaborative networks provide to researchers more and recent information.

In this paper, we focus on the scientific quality of diffused information and discuss the implications of this tendency for scientific performance. We propose a qualitative scientific watch system enriched by an alerts’ personalization and cartographic visualization tools.

The proposed watch system is based on scientific quality evaluation in its different parts. Scientific quality evaluation is made by the mean of scientometric indicators to select qualitative new publications to diffuse to the
researchers. The integration of personalization tool helps researchers on identifying qualitative information which corresponds to their needs. Moreover, the cartographic visualization provides to the researchers the possibility of analyzing and choosing more quickly interesting and useful alerts.

Auteurs : Nedra Ibrahim, Anja Habacha Chaibi, Henda Ben Ghézala

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Differential Evolution (DE) and the Particle Swarm Optimization (PSO) are two evolutionary algorithms that confirmed their efficiency in resolving complex problems. In this paper, we intend to adopt these algorithms to resolve a complex inventory management problem, known in the literature by the transshipment problem.

This problem concerns network of collaborative retailers selling items and they collaborate by exchanging items between them.

The transshipment problem consists in deriving the optimal replenishment
quantity, for each retailer, while a transshipment policy is adopted.

A huge body of literature works has addressed this problem where several configurations are investigated. A few of them has addressed the multi-
item and the multi-location configuration because of its complexity. We focus in this paper on this complex configuration and we resolve it by the PSO and DE algorithms. Secondly, we compare between the performances of these algorithms according to a set of criteria. Thirdly, we analysis the impact of the studied transshipment parameters on the inventory system performance measures.

Auteurs : Noomen Selmi , Mohamed Hmiden , Lamjed Ben Said

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This article presents the results obtained in applying an innovative and optimized approach to textual semantic analysis inthe service of decision-making.

Significant improvements have been made in the existing procedures of sentiment andrecommendation analysis, and in opinions mining, to enable better-motivated decisions and benefit from big data.

These improvements concerned, especially, the support of the notions of aspects, attention and subjectivity to lighten the treatments, well adapted in the context of big data. The results obtained show the interesting contribution of the approachto the specific field of business intelligence (BI) relative to user behaviors analysis.

Auteur : Hammou FADILI
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In the Internet age where the information flow has grown rapidly, there is an increase in digital communication. The spread of hatred that was previously limited to verbal communications has quickly moved over the Internet. Social media and community forums that allow people to discuss and express their opinions are becoming platforms for the dissemination of hate messages. Many countries have developed laws to prevent online hate speech.

They hold thecompanies that run the social media responsible for their failure to remove hate speech. However, manual analysis of hate speech on online platforms is infeasible due to the huge amount of data as it is expensive and time consuming. Thus, it is important to automatically process the online user contents to detect and remove hate speech from online media.

Through this work, we propose some solutions for the problem of automatic detection of hate messages. We perform hate speech classification using embedding representations of words and Deep Neural Networks (DNN).

We compare fastText and BERT (Bidirectional Encoder Representations from Transformers) embedding representations of words. Furthermore, we perform classification using two approaches: (a) using word embeddings as input to Support Vector Machines (SVM) and DNN-based classifiers; (b) fine-tuning of a BERT model for classification using a task-specific corpus.

Among the DNN-based classifiers, we compare Convolutional Neural Networks (CNN), Bi-Directional Long Short Term Memory (Bi-LSTM) and Convolutional Recurrent Neural Network (CRNN). The classification was performed on a Twitter dataset using three classes: hate, offensive and neither classes. Compared to the feature-based approaches, the BERT fine-tuning approach obtained a relative improvement of 16% in terms of macro-average F1-measure and 5.3% in terms of weighted F1-measure.

Auteurs : Ashwin Geet D’Sa, Irina Illina, Dominique Fohr

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