Publications (274)
ARTICLE
Text Mining for Thematic Keyword Extraction: Enriching a French Lexicon on Food Security
Rabiatou Zampaligre, Aminata Sabané, Rodrique Kafando, Abdoul Kader Kaboré, Tegawendé F. Bissyandé
Food security is a major concern in many countries in West Africa, particularly Burkina Faso. Early warning systems for food security and famines rely primarily on numerical data for analysis, while textual data, which is more complex to process, is seldom used. In this paper, we propose a textual analysis approach using text mining techniques(...)
Lexicon, Terminology, Food security, Thematic map, Process (computing), Domain (mathematical analysis), Named-entity recognition
ARTICLE
Text-to-OWL: Automated Ontology Construction for Tuberculosis Treatment Recommendation Using Generative AI
Zonabo Ouédraogo, Lydie Simone Tapsoba, Aminata Sabané, Rodrique Kafando, Abdoul Kader Kaboré, Tegawendé F. Bissyandé
This paper presents an automated approach for building ontologies to improve treatment 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 profile(...)
Ontology, Generative grammar, Tuberculosis, Generative model, Semantics (computer science)
ARTICLE
Detection of Malicious Android Applications Based on Verification of Indicators of Compromise and Machine Learning Techniques
Theodore Dama, Aminata Sabané, Abdoul Kader Kaboré, Tegawendé F. Bissyandé
Android is the operating system with the largest share of the global smartphone market. The system’s popularity makes it an attractive target for malware because of its users’ data. Despite the security measures used by Google and certain researchers to combat malicious applications, some still slip through the net. In this article, we propose(...)
Android (operating system), Compromise, Support vector machine, Training set, Robustness (evolution)
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
DamFlow: Preventing a Flood of Irrelevant Data Flows in Android Apps
Marco Alecci, Jordan Samhi, Marc Miltenberger, Steven Arzt, Tegawendé F. Bissyandé, Jacques Klein
State-of-the-art tools like FlowDroid have been proposed to detect data leaks in Android apps, but two main challenges persist: ① false alarms and ② undetected data leaks. One contributing factor to these challenges is that a tool such as FlowDroid relies on predefined lists of privacy-sensitive source and sink API methods. Generating such lis(...)
Preventing
COMMUNICATION
Intelligence Artificielle et Apprentissage universitaire
OUATTARA Yacouba
L'émergence de l'intelligence artificielle dans l'enseignement supérieur soulève des défis pédagogiques et éthiques, particulièrement concernant son utilisation dans les travaux
académiques. Cette étude, menée auprès de 300 étudiants et 20 enseignants d'universités burkinabé, combine une enquête quantitative et des entretiens semi-directifs.(...)
IA ; apprentissage ; éducation ; enseignement
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
Towards a Semantic Architecture for Data Lakes
Sione, A., Traore, Y., Thiombiano, J.
Data lakes are a storage system for large volumes of raw heterogeneous data, adopting an area-based architecture. The main challenge of this architecture is the extraction and storage of raw data without any content monitoring, making data processing and access difficult. In this paper, we propose the integration of an ontology into this archi(...)
Data lake , Architecture, Ontology Area Semantic
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
You Got Phished! Analyzing How to Provide Useful Feedback in Anti-Phishing Training with LLM Teacher Models
Tailia Malloy, Laura Bernardy, Omar El Bachyr, Fred Philippy, Jordan Samhi, Jacques Klein, Tegawendé F. Bissyandé
Training users to correctly identify potential security threats like social engineering attacks such as phishing emails is a crucial aspect of cybersecurity. One challenge in this training is providing useful educational feedback to maximize student learning outcomes. Large Language Models (LLMs) have recently been applied to wider and wider a(...)
cybersecurity, phishing, large language models, education, embeddings
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
Exploring the Role of Artificial Intelligence in Enhancing Security Operations: A Systematic Review
Despoina Giarimpampa, Roland Meier, Tegawendé F. Bissyande, Vincent Lenders, Jacques Klein
Artificial intelligence (AI) is reshaping Security Operations Centers (SOCs). This systematic literature review analyses AI’s transformative impact across the NIST Cybersecurity Framework. The analysis of 189 papers related to AI use-cases for SOCs shows widespread application of AI for detection, with 65% of studies focusing on it. Yet, it al(...)
A Systematic Review