Publications (213)
ARTICLE
Deep Learning Approach for Optimized DDoS Detection in SDN
Rolph Abraham Yao, Ferdinand Tonguim Guinko
The rise of Software-Defined Network (SDN) offers great flexibility in network infrastructure management. However, this flexibility also introduces critical security challenges, in particular vulnerability to Distributed Denial of Service attacks (DDoS). Traditional detection methods are often ineffective in the face of evolving attack strateg(...)
Software-Defined Network , Distributed Denial of Service , Deep Learning , models , specific dataset , performance
ARTICLE
Literature review on classification model for human skin disease
T. Ferdinand Guinko, B. Tanguy Kaboré
The rising global burden of skin diseases requires precise and efficient diagnostic tools to improve patient care and treatment outcomes. Recent advances in artificial intelligence, particularly deep learning, have significantly contributed to the automation of the classification of skin diseases. This review presents a detailed analysis of va(...)
Skin diseases; Classification model; Artificial intelligence; Deep learning; Convolutional neural network
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
Performance Analysis of Floodlight, ONOS, OpenDaylight and Ryu Controllers in Software-Defined Network
Rolph Abraham Yao, Ferdinand Tonguim Guinko
Software-defined networking (SDN) is a growing concept that allows the separation of the control layer from the data layer, making the network programmable, and having a centralized view and management of the network. The control layer is an important component of the network because it is composed of controllers that play a role in supervisin(...)
ONOS, DDOS, Performance analysis Ryu cotroller
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
Optimizing DDoS attack detection in SDN using machine learning
Rolph Abraham Yao, Ferdinand Tonguim Guinko
Distributed Denial of Service attacks are a major threat to network security, particularly for Software-Defined Networks. Despite their centralized and flexible management, they are particularly vulnerable to Distributed Denial of Service attacks. In this paper, an effective approach to identifying Distributed Denial of Service attacks based o(...)
Distributed Denial of Service , Software-Defined Network , model , Machine Learning , dataset , performance
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
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
A large-scale LPWAN Architecture for Multimedia Data Collection in High-security Challenge Areas
OUATTARA Yacouba, PODA Pasteur et TRAORE Mamouta
The Internet of Things (IoT) is rapidly expanding, including in conflict zones where security is
critical. Sound signals used for intelligence in the Middle East, combined with Sahel challenges from poor
infrastructure, emphasize the need for better data collection. This paper proposes a secure IoT architecture
using Low Power Wide Area Net(...)
LPWAN, LoRaWAN, Architecture, Design, Terrorism, Steganography, Military.