Acta Informatica Pragensia, 2025 (vol. 14), issue 1
Article
Cloud Survivability Scenarios Under Attacks With and Without Countermeasures
Rachid Beghdad, Faiza Benmenzer, Alaa Eddine Khalfoune
Acta Informatica Pragensia 2025, 14(1), 1-25 | DOI: 10.18267/j.aip.2483123 
Background: Despite its increasing importance, cloud computing is vulnerable to Distributed Denial of Service (DDoS) attacks, affecting data centre availability and functionality. Unfortunately, the impact of these attacks on cloud survivability remains underexplored. Most works overlook long-term resilience and lack comprehensive metrics, in-depth simulation, large-scale experiments, and combined attack and defence scope. Objective: This study investigates the survivability of cloud environments under DDoS attacks in extreme cases, involving intensive attacks leading to cloud failure. By simulating worst-case scenarios, including thousands of attacks...
Development and Validation of a Blockchain Literacy Scale
Kemal Elciyar, Neşe Satılmış
Acta Informatica Pragensia 2025, 14(1), 26-41 | DOI: 10.18267/j.aip.2515789
Background: The use of blockchain is increasing daily and has become a transformative technology across various sectors. The competent use of blockchain is becoming a fundamental skill. Although numerous studies have attempted to measure digital competencies, the absence of research specifically focused on blockchain literacy has left a significant gap. Objective: The aim of this study is to provide a systematic review of digital literacy and blockchain measurement frameworks, comparing them with existing theoretical digital competence models. Methods: Furthermore, we introduce a newly developed Blockchain Literacy Scale (BLS). The factorial structure...
BACP-LRS: Blockchain and IPFS-based Land Record System
Insaf Boumezbeur, Abdelhalim Benoughidene, Imane Harkat, Farah Boutouatou, Dounia Keddari, Karim Zarour
Acta Informatica Pragensia 2025, 14(1), 42-62 | DOI: 10.18267/j.aip.2524300
Background: Land records have traditionally derived their credibility from a central database of local government records, with copies issued to land owners. Physical records are the only credible source of any information related to land ownership that has been in existence for a long time. However, physical records are prone to manipulation and fraud. Recently, some academic research has begun to address the potential use of blockchain technology to improve the security and reliability of land registration processes. Objective: The purpose of the present work is to propose an architecture for blockchain-based access control for distribution, ensuring...
Forecasting Financial Distress for Shaping Public Policy: An Empirical Investigation
Soumya Ranjan Sethi, Dushyant Ashok Mahadik
Acta Informatica Pragensia 2025, 14(1), 63-87 | DOI: 10.18267/j.aip.2533379
Background: Prediction of financial distress has been made more accurate and reliable through machine learning methods. Financial stress affects the business corporate entity, society and the general economy. Analysing such nonlinear events is essential for preventing the dangers and supporting a favourable economic climate. Objective: This paper seeks to develop a robust predictive model for identifying firms in the Indian context other than the financial service sector that may face financial distress and also to check the impact of one essential predictor, i.e., future cash flow, on financial distress prediction. Besides, the study also aims at...
Induced Partitioning for Incremental Feature Selection via Rough Set Theory and Long-tail Position Grey Wolf Optimizer
Said Al Afghani Edsa, Khamron Sunat
Acta Informatica Pragensia 2025, 14(1), 88-111 | DOI: 10.18267/j.aip.2544582
Background: Feature selection methods play a crucial role in handling challenges such as imbalanced classes, noisy data and high dimensionality. However, existing techniques, including swarm intelligence and set theory approaches, often struggle with high-dimensional datasets due to repeated reassessment of feature selection, leading to increased processing time and computational inefficiency. Objective: This study aims to develop an enhanced incremental feature selection method that minimizes dependency on the initial dataset while improving computational efficiency. Specifically, the approach focuses on dynamic sampling and adaptive optimization...
Predicting Employee Turnover Using Machine Learning Techniques
Adil Benabou, Fatima Touhami, My Abdelouahed Sabri
Acta Informatica Pragensia 2025, 14(1), 112-127 | DOI: 10.18267/j.aip.2554256
Background: Employee turnover is a persistent issue in human resource management, leading to significant costs for organizations. This study aims to identify the most effective machine learning model for predicting employee attrition, thereby providing organizations with a reliable tool to anticipate turnover and implement proactive retention strategies. Objective: This study aims to address the challenge of employee attrition by applying machine learning techniques to provide predictive insights that can improve retention strategies. Methods: Nine machine learning algorithms are applied to a dataset of 1,470 employee records. After data preprocessing...
Blockchain Approach for Healthcare Using Fog Topology and Lightweight Consensus
Aya Laouamri, Sarra Cherbal, Yacine Mosbah, Chahrazed Benrebbouh, Kamir Kharoubi
Acta Informatica Pragensia 2025, 14(1), 128-154 | DOI: 10.18267/j.aip.2562854
Background: The internet of things (IoT) has transformed healthcare by integrating various devices and systems, fostering innovation in data management and operational efficiency. However, ensuring data integrity, security and trust within IoT networks remains a pressing challenge, particularly in critical sectors such as healthcare. Objective: This study aims to explore the integration of blockchain technology with IoT systems, focusing on addressing scalability and real-time applicability issues in healthcare data management. By proposing novel solutions, the research seeks to enhance the security and reliability of IoT systems in healthcare environments....
Explanatory Model of Awareness Factors of Smart Technologies for Independent Living at Home in Later Life
Natalija Rebrica, Andraž Petrovčič, Urška Tuškej Lovšin
Acta Informatica Pragensia 2025, 14(1), 155-173 | DOI: 10.18267/j.aip.2583064
Background: Despite the rapid development of Smart Technologies for Independent Living at Home (STILH) among older adults, their market is still underdeveloped. Low awareness is one of the key reasons for the slow uptake of STILH in later life. A significant gap exists in the literature regarding the factors that shape older adults′ awareness of STILH. Objective: The aim is to provide a conceptual overview and empirical test of awareness factors of STILH in later life. An explanatory model is proposed by integrating insights from consumer behaviour, information processing and technology adoption models. Methods: The model is tested with structural...
Review
Optimization in Routing and Vehicle Selection for E-commerce Last Mile Logistics: Bibliometric Analysis
Sari Andarwati Kunharyanto, Ratna Mayasari, Dili Oktaviana
Acta Informatica Pragensia 2025, 14(1), 174-190 | DOI: 10.18267/j.aip.2575558
Background: The study investigates the emerging concept of Last Mile Logistics (LML), focusing on optimization routing for e-commerce deliveries. This research addresses the growing demand for efficient delivery systems driven by the rise of online shopping and technological advancements. Objective: This article aims to analyse existing literature, identify trends and highlight gaps in LML research. Methods: A systematic approach was used for the selection of studies and then bibliometric analysis was used to map and evaluate relevant studies. The Scopus citation database was used to gather peer-reviewed articles from 1999 to 2023. R-Studio and VOS...