Publications (197)
ARTICLE
Optimizing the 4G--5G Migration: A Simulation-Driven Roadmap for Emerging Markets
Desire Guel and Justin Pegd-Windé Kouraogo and Kouka Kouakou Nakoulma
Deploying fifth-generation (5G) networks in emerging markets demands a balance between performance targets and constraints in budget, spectrum, and infrastructure. We use MATLAB simulations to quantify how radio and architectural levers - MIMO (beamforming, diversity, spatial multiplexing), carrier aggregation (CA), targeted spectrum refarming(...)
5G migration, emerging markets, MIMO, carrier aggregation, spectrum refarming, mmWave, NSA/SA, D2D, M2M
COMMUNICATION
BF-WeakWeb-2025: A Novel Dataset and LLM Benchmark for Web Vulnerability Detection in Burkina Faso
Nana Sidwendluian Romaric and Bassolé Didier and Guel Désiré and Sié Oumarou
In a context of increasing digitalisation of administrative processes, cybersecurity has become a strategic issue for states, particularly Burkina Faso. Unfortunately, there is a lack of research into cybersecurity in Burkina Faso. In this article, we present an approach for identifying vulnerabilities in applications and websites from Burkina(...)
Knowledge engineering, Analytical models, Large language models, Cyberspace, Benchmark testing, Aging, Software, Data models, Communications technology, Computer security, OWASP Top 10, Web vulnerablity scanners, Fine-tuning, Large Language Model, Web application attacks
COMMUNICATION
Private Key Fragments Secure Recovery Approach in Passkeys System Based on Blockchain Technology and Error-Correcting Codes
Assane Ilboudo Didier Bassole and Desire Guel
In this paper, we propose an innovative approach to enhance the security and resilience of passkeys. this approach combines Shamir’s Secret Sharing Scheme, Reed–Solomon error-correcting codes, AES-GCM encryption, and decentralized storage systems such as blockchain and IPFS. In this approach, the adopted methodology is structured around three(...)
Solid modeling, Scalability, Computational modeling, Resists, Robustness, Error correction codes, Blockchains, Encryption, Secure storage, Resilience, Passkey System, Blockchain, Error-Correcting Codes, Security
ARTICLE
Optimization and comparison of Deep Learning architectures for multi class classification of DDoS attacks in enterprise networks
Yacouba OUATTARA, Yaya TRAORE and Yves SAVADOGO
This article presents an in-depth study aimed at optimizing and comparing several deep learning architectures for multi-class classification of DDoS attacks in enterprise
networks, using the CIC-DDoS2019 dataset. The methodological approach includes rigorous data preprocessing (normalization, encoding, balancing, stratified split) as well as(...)
DDoS, intrusion detection, multi- class classification, Deep Learning, CNN-1D, CNN-LSTM, CNN-BiLSTM, CIC-DDoS2019.
ARTICLE
Deep learning models for binary ddos attack detection in enterprise environments
Yacouba OUATTARA Yaya TRAORE Yves SAVADOGO
This paper proposes an experimental methodology
based on the comparison of several deep learning models for the
detection of distributed denial of service (DDoS) attacks in
enterprise network environments. The CIC-DDoS2019 dataset,
recognized for the richness and realism of its attack scenarios,
served as a basis for the preparation, trai(...)
Cybersecurity, Deep Learning, Binary Classification, Intrusion Detection System (IDS), DDoS, CIC- DDoS2019 dataset
ARTICLE
A Hybrid Optimization Framework for Emergency Resource Allocation in Low-Resource Settings: Application to Burkina Faso
Tougma Manegaouindé Roland, Zerbo Boureima, Guel Désiré, Traore Salah Idriss Seif, Napon Salifou
The overuse of hospitals in Burkina Faso, especially during emergencies, is largely due to chronic underfunding and weak coordination among health centers. These challenges create critical bottlenecks in emergency care, where resources are limited and demand is often unpredictable. Motivated by the need for improved management of emergency pat(...)
Adaptation Models, Uncertainty, Hospitals, Decision Making, Urban Areas, Artificial Neural Networks, Linear Programming, Mathematical Models, Resource Management, Particle Swarm Optimization, Linear Programming, Particle Swarm Optimization, Artificial Neural Networks, Emergency Resource Allocation, Healthcare Optimization, Burkina Faso
COMMUNICATION
5G-NR PUSCH Receiver Optimization in Context of Intra/Inter Cell Interference
Désiré Guel, Flavien Hervé Somda, P. Justin Kouraogo, Boureima Zerbo
As 5G New Radio (5G-NR) networks evolve, managing intracell and inter-cell interference, especially during uplink transmissions on the Physical Uplink Shared Channel (PUSCH) becomes increasingly challenging. This paper presents a novel approach to optimizing User Equipment (UE) and cell configuration parameters to mitigate interference and imp(...)
5G-NR PUSCH, Intra/Inter-Cell Interference, Quality of Service (QoS), Block Error Rate (BLER)
COMMUNICATION
A Structured Metamodel for Architecture Debt Management
Flavien Hervé SOMDA, Desire GUEL
Architecture debt in information systems poses significant challenges, leading to increased maintenance costs, reduced performance, and compromised quality. Effective management of architecture debt is crucial for the sustainability and efficiency of software systems. This paper proposes a comprehensive metamodel to support managing architectu(...)
Architecture Debt, Metamodel, Impact Analysis, Traceability, Model-Driven Engineering.
ARTICLE
Enhancing the security of the MQTT protocol in the Internet of Things using the Syracuse conjecture
OUATTARA Yacouba, COMPAORE Ousmane, OUEDRAOGO Victor, TRAORE Yaya
This article proposes a scientific contribution to strengthen the security of the MQTT protocol in
an IoT environment. MQTT is natively a communication protocol that does not embed any security. Messages are
transmitted in clear text over the network. Being an IoT protocol, MQTT evolves in an environment with limited
resources, where energy(...)
Collatz conjecture, Collatz sequence, dynamic authentication, Internet of Things (IoT), lightweight encryption, MQTT, Security
ARTICLE
Data Search in Smart GIS Database Using Map Reduce Pattern and Bayesian Probability
Moubaric Kabore, Abdoulaye Sere and 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
Large Language Models Adaptation for Web Applications Attacks Detection
Nana Sidwendluian Romaric, Bassolé Didier, Guel Désiré, Sié Oumarou
Large Language Models (LLMs) represent a major advance in the field of deep learning. Their ability to understand long-term dependencies between words in a sentence has completely revolutionized natural language processing. Based on the architecture of transformers, LLMs are trained to solve common linguistic problems, such as text classificat(...)
Adaptation models, Accuracy, Large language models, Text categorization, Bidirectional control, Transformers, Encoding, Service-oriented architecture, Computer security, Payloads, Fine-tuning;Large Language Model, Web application attacks, Detection
ARTICLE
Health centers network analysis with Gephi and ForceAtlas2 approach: Case of Burkina Faso
Saan-nonnan Olivier Dabire, Désiré Guel, Boureima Zerbo
Burkina Faso, like many developing countries, faces significant challenges in public health, particularly regarding healthcare access and infrastructure distribution. Healthcare centers are unevenly distributed across regions, resulting in disparities in access to care. This study aims to analyze the structure and efficiency of the healthcare(...)
Force Atlas2, Graph theory, Modularity, Density, Health network, Burkina Faso
ARTICLE
Artificial intelligence for IoT threat detection: Case of DDoS attacks
Dr. Yacouba OUATTARA Dr. Yaya TRAORE D. Moumine Arthur OUEDRAOGO
With the rapid expansion of connected objects in our daily lives, the risks of cyberattacks, particularly by distributed denial of service (DDoS), have increased considerably. IoT devices, often designed with few resources and little protection, are easy targets for cybercriminals. In this context, our study explores the role of artificial int(...)
IoT, DDoS, Machine Learning, Deep Learning, K-Means, Isolation Forest, Random Forest
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