Publications (277)
ARTICLE
Resolving Conditional Implicit Calls to Improve Static and Dynamic Analysis in Android Apps
Jordan Samhi, René Just, Michael D. Ernst, Tegawendé F. Bissyandé, Jacques Klein
An implicit call is a mechanism that triggers the execution of a method m without a direct call to m in the code being analyzed. For instance, in Android apps the Thread.start() method implicitly executes the Thread.run() method. These implicit calls can be conditionally triggered by programmer-specified constraints that are evaluated at runti(...)
Resolving
PRéPUBLICATION
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
ARTICLE
Privacy-Preserving Android Malware Detection Using Deep Federated Learning
Rehanatou B. Coulibaly, Tegawende Bissyande, Aminata Sabané, Sabané Aminata, Abdoul Kader Kaboré
This work represents a major breakthrough in the fields of legal Technology, digital governance and mobile cybersecurity. Malware attacks on Android are increasing daily at a considerable volume, making Android users more vulnerable to cyberattacks. In response to this growing threat, researchers have developed numerous machine learning and de(...)
Android (operating system), Malware, Federated learning, Server, Mobile device
COMMUNICATION
AI4DVault: A Registry Architecture for Securing the AI4D Supply Chain
Aminata Sabane, Tegawendé F. Bissyande
As artificial intelligence for development initiatives expand, ensuring secure and transparent supply chains for AI artifacts has become a critical challenge in emerging countries. Recent incidents of malicious models on repositories like Hugging Face demonstrate that machine learning model platforms are increasingly vulnerable to the same sup(...)
AI4D , AI artifacts , supply chain
ARTICLE
CallNavi, A challenge and empirical study on LLM function calling and routing
Yewei Song, Xunzhu Tang, Cedric Lothritz, Saad Ezzini, Jacques Klein, Tegawendé Bissyande, Andrey Boytsov, Ulrick Ble, Anne Goujon
API-driven chatbot systems are increasingly integral to software engineering applications, yet their effectiveness hinges on accurately generating and executing API calls. This is particularly challenging in scenarios requiring multi-step interactions with complex parameterization and nested API dependencies. Addressing these challenges, this(...)
challenge
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
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
ARTICLE
Big data analytics in healthcare: machine learning-based cardiac disease prediction in West Africa
Amédée W. DERA, Ferdinand T. GUINKO
This paper investigates the application of machine learning for cardiac disease prediction in resource constrained healthcare settings. This study conducts an empirical study evaluating four classification algorithms (Support Vector Machine, Random Forest, Logistic Regression, Decision Tree) on a real-world dataset. The results demonstrate tha(...)
Big Data Analytics, Data-driven healthcare, Data analytics in healthcare, Machine Learning in Healthcare, Disease Prediction
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
African digital health strategic plans analysis: key weaknesses in contextualization, intervention focus, and technological foresight
Bry Sylla; Ansiouonèkou Pascal Somda; Jean Noel Nikiema; Leon Gueswende Blaise Savadogo; Gayo Diallo; Nicolas Meda
Digital health strategies are increasingly being adopted in Africa, but their consistency with best practice planning is poorly documented. 54 countries were screened; 48 had a plan in the Global Digital Health Monitor, and 11 recent plans met the inclusion criteria. Using the “Ready, Extract, Analyze, Distill” methodology and a customized gri(...)
Health policy, Public health, Digital health
COMMUNICATION
A Metamodel for Simplifying Infrastructure Deployment Using Vagrant
Flavien Hervé Somda; Arnold Stéphane Kabore; Boureima Zerbo
We propose a metamodel–driven framework that replaces hand-written Ruby Vagrantfiles with validated EMF models capturing core Vagrant concepts (virtual machines, providers, networks, shares, plugins) and provisioners including Shell, Puppet, and Ansible. The framework raises the level of abstraction by allowing users to specify infrastructures(...)
Metamodeling , Infrastructure as Code , Vagrant , Virtualization , Code Generation , DevOps
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
ARTICLE
Network Optimization for Data Flow Control in a Security-Challenged Country: The Case of Burkina Faso
Yamba Dabone, Pengwendé Zongo & Tounwendyam Frédéric Ouedraogo
The Internet plays a crucial role in everything these days—economic development, education, and civic engagement—but it is also exploited by cybercriminals and terrorists, particularly via propaganda on social networks. In Burkina, where the terrorist threat has been present since 2016, cyber-activists sometimes relay unverified information, w(...)
Internet, IXP, Cyber-terrorism, Social network, Architecture.
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