Publications (185)
ARTICLE
DDoS Attacks Simulation on a Storage Cloud: Impacts and Appropriate Security Mechanisms
Almissi Amed Kindo, Didier Bassole, Gouayon Koala, Oumarou Sié
Safety, availability, confidentiality and integrity are essentials characteristics for any user of cloud services. Distributed Denial of Service (DDoS) attacks are one of the most widespread threats on cloud computing. In this paper, we simulate DDoS attacks on a storage cloud and we try to assess the impact on the integrity, availability and(...)
DDoS, Cloud Computing, Storage cloud, LOIC, XerXes
ARTICLE
Advancements in Deep Learning for Malaria Detection: A Comprehensive Overview
Kiswendsida Kisito Kabore and Desire Guel and Flavien Herve Somda
Malaria remains a critical global health issue, with millions of cases reported annually, particularly in resource-limited regions. Timely and accurate diagnosis is vital to ensure effective treatment, reduce complications, and control transmission. Conventional diagnostic methods, including microscopy and Rapid Diagnostic Tests (RDTs), face c(...)
Malaria detection, Deep Learning, Convolutional Neural Networks (CNN), Medical Imaging, Automated diagnostics
ARTICLE
Assessing Robustness and Resistance to Attacks of an Authentication System Based on OpenID Connect Protocol and Ethereum Blockchain
Ilboudo Assane; Bassole Didier; Kouraogo Justin Pegdwindé; Koala Gouayon; Sie Oumarou
In this paper, we assess the robustness and resistance against various types of attacks of a multi-factor authentication mechanism that we have proposed. It is a mechanism based on the OpenID Connect protocol and utilizes the Ethereum blockchain. Robustness was evaluated by conducting appropriate security tests using AVISPA and Scyther protoco(...)
Single Sign-On, Robustness, Ethereum Blockchain, OpenID Connect
ARTICLE
Towards a Single-Sign-On Authentication Architecture Based on OpenID Connect Protocol and Blockchain Technology
Assane Ilboudo, Didier Bassole, Justin P. Kouraogo, Gouayon Koala, Oumarou Sie
OpenID Connect is a delegated authentication protocol used in web and mobile applications. It emphasizes the crucial role of third-party applications, also known as Relying Parties, which securely request information from an identity provider. In this article, we have proposed an approach based on the Ethereum blockchain to enhance the authent(...)
Authentication, Security, Blockchain, OpenID Connect
ARTICLE
5G NR Uplink Performance Optimization A Comprehensive Study on PRACH and PUSCH Interference Management
Désiré Guel, P. Justin Kouraogo, Flavien Hervé Somda, Boureima Zerbo, Oumarou Sié
The evolution of 5G New Radio (NR) technology offers unprecedented speeds, ultra-low latency, and the capability to connect billions of devices. However, these advancements come with significant challenges, particularly in managing interference during uplink communication. This study presents a comprehensive investigation into the optimization(...)
5G-NR , Physical Random Access Channel (PRACH), PUSCH, Intra/Inter-Cell Interference, Quality of Service (QoS), Block Error Rate (BLER)
ARTICLE
5G NR Uplink Performance Optimization: A Comprehensive Study on PRACH and PUSCH Interference Management
Désiré GUEL, Flavien Hervé SOMDA, Boureima Zerbo, Oumarou Sié
The evolution of 5G New Radio (NR) technology offers unprecedented speeds, ultra-low latency, and the
capability to connect billions of devices. However, these advancements come with significant challenges,
particularly in managing interference during uplink communication. This study presents a comprehensive
investigation into the optimizat(...)
5G-NR , Physical Random Access Channel (PRACH), PUSCH, Intra/Inter-Cell Interference, Quality of Service (QoS), Block Error Rate (BLER)
ARTICLE
Revisiting the Non-Determinism of Code Generation by the GPT-3.5 Large Language Model
Salimata Sawadogo, Aminata Sabané, Rodrique Kafando, Tegawendé F. Bissyandé
Despite recent advancements in Large Language Models (LLMs) for code generation, their inherent non-determinism remains a significant obstacle for reliable and reproducible software engineering research. Prior work has highlighted the high degree of variability in LLM-generated code, even when prompted with identical inputs. This non-determini(...)
LLM, TOT, GPT
ARTICLE
IoT Devices Security Improvement Based on Collaborative Intrusion Detection System and Blockchain Technology
Yempabou Yves Stéphans Loari; Didier Bassole; Leonard M. Sawadogo; Gouayon Koala; Oumarou Sié
IoT is one of today's major growth areas. With its low computing power and massively exchanged heterogeneous data, it is vulnerable to numerous at-tacks. In this paper, we proposed a collaborative system based on hybrid intrusion detection and blockchain technology to improve IoT devices security. Thus, we simulated a federated learning using(...)
IoT security, federated learning, CIDS, Blockchain
ARTICLE
Détection de communautés dans les graphes de connaissance d’activités 2025
Marthe Désirée Olivia HABACK, Serge SONFACK SOUNCHIO, Orlane SONKENG TSAFACK, Halguièta TRAWINA, Ho Tuong Vinh
La gestion des connaissances produites au cours des activités au sein des organisations joue un rôle important dans leur développement et leur succès. La formalisation de ces connaissances sous forme de graphe de connaissance d’activités (Activity Knowledge Graph : AKG) permet de représenter et de réutiliser ces connaissances pour résoudre des(...)
Graphe de connaissance, graphe de connaissance d’activité, détection de communauté, algorithme de Louvain
ARTICLE
Création d’une carte de connaissances à partir d’un graphe de connaissance d’activités 2025
Orlane SONKENG TSAFACK, Serge SONFACK SOUNCHIO, Marthe Désirée Olivia HABACK, Adama ARAMA, Halguièta TRAWINA, Ho Tuong Vinh
La gestion des connaissances produites au sein des organi- sations est capitale pour leur développement et les graphes de connaissance d’activités sont utilisés à cet effet. Ils per- mettent de réutiliser ces connaissances pour résoudre des problèmes ou prendre des décisions. Cependant, la réuti- lisation des graphes de connaissance d’activité(...)
Graphe de connaissances, Graphe de connaissance des ac- tivités, Carte de connaissances
ARTICLE
Beyond Syntax: Testing LLM Semantic Understanding of Code
Aminata Sabané, Tegawendé F. Bissyandé
While Large Language Models (LLMs) have shown promise in various software engineering tasks, their deep understanding of code semantics remains a challenging area. This paper introduces a novel methodology to probe the semantic understanding of LLMs by subjecting them to a rigorous test: identifying trivial equivalent mutations in C code gener(...)
LLM, code understanding, mutation equivalence
COMMUNICATION
Data Search in Smart GIS Database using Map Reduce Pattern and Bayesian Probability
Moubaric Kabore, Abdoulaye Sere, Vini Yves Bernadin Loyara
This paper deals with Bayesian approach in Data Research in GIS database through artificial Intelligence (AI) modules, reading the best bayesian probability before returning the data requested, denoted AI4DB. The proposed method combines meshing techniques and the map-reduce algorithm with Bayesian approach to obtain a smart GIS database to re(...)
MapReduce, GIS, Bayesian Probability
ARTICLE
Cross-Analysis of Social Media Opinions in a High-Security Challenge Context
Zombre Payiri Gregoire Wenceslas; Traore Yaya; P. Justin Kouraogo
This study aims to develop an approach for cross-analyzing public opinions on security issues in Burkina Faso, as expressed on social media platforms. We implemented a methodology combining web scraping, API calls, and large language models (LLMs) to collect and analyze data from Fasonet [1], Burkina24 [2] and YouTube [3]. The experiment invol(...)
Social media analysis , Opinion mining , Sentiment analysis , Large Language Models (LLMs) , Cross-platform analysis
ARTICLE
Text-to-OWL: Automated Ontology Construction for Tuberculosis Treatment Recommendation using Generative AI
OUÉDRAOGO Zonabo, TAPSOBA Lydie Simone, SABANE Aminata, BISSYANDE T François
his paper presents an automated approach for building ontologies to improve treat-
ment recommendations for tuberculosis (TB), in particular multidrug-resistant tuberculosis (MDR-
TB) cases in Burkina Faso, using generative language models such as GPT-3. The aim is to
facilitate the personalization of treatments according to the patient pro(...)
Tuberculosis · Generative AI · Ontologies · Medical Decision Support Systems · Text-to-Ontology
ARTICLE
Towards a Framework for the Preparation of High Quality Data for Use by Machine Learning Algorithms
Nabi, R., Traoré, Y., Thiombiano, J.
Nowadays, companies and organizations have access to various data collection tools that enable them to amass vast amounts of data, which can be stored in databases. This data can be leveraged by machine learning algorithms to extract valuable information for decision-makers. However, this raw data is often of poor quality, containing errors su(...)
data preparation,