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Digital Signatures in the Modern Era: A Review of Cryptographic Progress and Post-Quantum Challenges
No full textThis paper aimed to provide a thorough examination of recent advancements in digital signatures, emphasizing data security, authentication, and information non-repudiation in the digital age. The study is based on a review of scientific literature from the period 2020 to 2025, in which fundamental principles such as cryptography, public key infrastructure (PKI), hash functions, and RSA algorithms were analysed. It was confirmed that the practical principles of digital signatures were analysed in sensitive areas such as blockchain and healthcare, along with emerging technologies like post-quantum systems and artificial intelligence. The research findings showed that traditional algorithms like RSA are gradually being replaced by newer models such as Syrga-1 and HBSS, which provide better protection against quantum attacks. The importance of PKI in identity verification and certificate management within decentralized systems was confirmed. We consider digital signatures to be essential for ensuring integrity and non-repudiation in many applications. This study enhances academic literature by elucidating contemporary difficulties and prospects for continued progress in digital security. Nonetheless, constraints remain concerning the experimental status of post-quantum technologies and the absence of widespread standardization. Recommendations include expediting the standardization of post-quantum algorithms, incorporating them with blockchain technology, formulating lightweight schemes for the Internet of Things, and enhancing awareness about the usage of digital signatures in both public and private sectors
AI-Enabled Distributed Cloud Frameworks for Big Data Analytics with Privacy Preservation
No full textThe fast rise of the Big Data and the faster adoption of Artificial Intelligence (AI) have changed the modern computational ecosystems allowing to conduct real-time analytics and automation in some of the most vital areas: healthcare, finance, and industrial IoT. Nevertheless, there are notable problems with traditional centralized cloud designs such as poor scalability, high latency, network overload, and augmented privacy and security threats in distributing sensitive information that is sensitive. To fill these gaps, this paper suggests a new AI-enabled distributed cloud framework (AIDCF) that combines federated learning, differential privacy, and homomorphic encryption to facilitate secure, privacy-preserving and scalable analytics on the Big Data without centralized sharing of data. The mixed-method research design was chosen, which involved the development of theoretical frameworks, the modeling of algorithms, and simulation of experiment, based on synthetic multi-domain data (healthcare, finance, IoT) running on distributed cloud nodes (10-100). The outcomes indicate the novelty and high-performance AIDCF, which has a high accuracy (93.7%), low latency (139 ms), high throughput (1585 MB/s) and high computational performance (89.5 percent), as well as the significant reduction in privacy loss (ε = 1.3) compared to other models such as DP-FedAvg, SecureML, and Baseline Cloud Analytics (BCA). These results confirm that the presented framework provides a feasible trade-off between analytical and confidentiality protection, which makes it be deployed in privacy-sensitive, real-time, and large-scale distributed systems. Altogether, AIDCF offers a scalable, secure, and high-performance distributed AI system, which will push the state of the art of privacy-aware Big Data processing
Mapping ISP Malware Trends in Albania: Clustering for Smarter Cyber Defences
Full text linkCybersecurity plays a vital role in protecting digital infrastructure, with Internet Service Providers (ISPs) standing at the core of this ecosystem. This research takes an exploratory perspective, given the limitations of both the dataset and the number of available features. The analysis draws on malware detection data from Albania, reported through the Shadow Server platform, covering a 15-month period across seven ISPs. By applying time-series clustering alongside statistical methods, the study groups ISPs according to their security patterns. The time-series analysis points to three distinct periods of heightened malware activity, while the characteristics-based approach identifies three groups of ISPs that differ in their vulnerability profiles. Taken together, these results underline the need for customized cybersecurity strategies and stronger cooperation among ISPs. Despite the constraints of a relatively small dataset, clustering techniques prove useful for optimizing resources, supporting regulatory compliance, and informing strategic decisions aimed at more effective threat prevention and mitigation
COVID-19: A Comprehensive Assessment of the Pandemic\u27s Impact in Albania
No full textThe COVID-19 pandemic, which began in late 2019, has had a profound impact on the political, medical, and social landscapes of countries worldwide. This study provides a comprehensive analysis of the pandemic\u27s effects in Albania, examining the multifaceted challenges faced by the country. It begins with an in-depth assessment of the healthcare sector, addressing the early strain on medical resources, difficulties in executing rapid immunization campaigns, and the need to adapt healthcare infrastructure to unprecedented demands. The economic analysis explores shifts in employment patterns, the collapse of key sectors such as tourism and small businesses, and government interventions, including fiscal stimulus measures aimed at alleviating financial hardship. The paper also considers the social repercussions of the pandemic, including the rise of community-driven resilience initiatives, the mental health toll of extended lockdowns, and the acceleration of digital transformation in education and public services. Using Albania as a case study, this research emphasizes the importance of regional cooperation in enhancing resilience to external crises, provides practical recommendations for future crisis preparedness, and offers broader insights relevant to the Western Balkans
Limitations of Electronic Assessment: A Systematic Review
No full textElectronic assessment—also referred to as online, digital, or automated assessment—has become an integral component of modern education, particularly in the context of e-learning and blended learning environments. It facilitates the evaluation of students’ knowledge, skills, and attitudes while offering notable advantages such as flexibility, cost-effectiveness, and enhanced access to educational data. Despite its growing prominence, electronic assessment is not without its limitations, which can hinder its effectiveness and broader adoption in educational settings. This study aims to systematically identify and analyze the key limitations associated with electronic assessment, with the goal of informing improved practices and aligning assessment strategies with future educational demands. Employing the PRISMA framework, a systematic review was conducted using articles published between 2000 and 2024. Relevant studies were sourced from databases such as Scopus, Google Scholar, and ScienceDirect, using a comprehensive set of search terms related to electronic assessment and its constraints across various educational contexts. The review identified ten major categories of limitations: technical issues, academic integrity concerns, accessibility and equity challenges, difficulties in measuring learning outcomes, data privacy risks, student inexperience, inadequate technical infrastructure, inaccuracies in scoring and grading, challenges in assessing group work, and limited teacher familiarity with assessment technologies. These challenges underscore the need for strategic improvements to maximize the reliability, equity, and pedagogical value of electronic assessments. Furthermore, the findings reveal a predominant focus in the literature on assessing individual content knowledge, with relatively limited exploration of broader educational outcomes or diverse theoretical frameworks. Addressing these gaps—both methodological and practical—will be critical to enhancing the future role of electronic assessment in education
A Systematic Literature Review on Integrating VANETs, VDTNs, 5G, and IoT for Smart Cities: Current Approaches, Challenges, and Future Directions
Full text linkNowadays smart cities have become a necessity for rapidly changing and transforming urban environments and the core technologies enabling this development are Vehicular Ad Hoc Networks (VANETs), Vehicular Delay Tolerant Networks (VDTNs), 5G networks, and Internet of Things (IoT). These technologies alone offer an important contribution, but when integrated effectively, they offer the opportunity of uninterrupted connectivity, real-time data sharing and management of urban resources. This paper conducts a comprehensive literature review to study existing techniques/approaches and challenges for integrating VANET, VDTN, 5G, and IoT within smart cities based on three research questions. Recent articles from databases such as Google Scholar, ResearchGate and MDPI, were reviewed to examine this integration, to identify recent advancements in this topic with focus on innovative methodologies proposed in an international context and to highlight the research gaps, challenges and solutions. The VOSviewer software was used to build the keyword co-occurrence network and to cluster the relevant literature. Our findings reveal that although promising solutions exist, issues such as high mobility, heterogeneous network architecture, and resource constraints remain critical barriers to large-scale deployment of smart city applications. Furthermore, this review proposes a conceptual framework for intelligent and adaptive network integration of VANET, VDTN, IoT, and 5G for future smart city applications
Cluster Analysis of Merger and Acquisition Patterns in the Electronic Design Automation Industry Using Machine Learning Techniques
No full textMergers and Acquisitions (M&A) are key drivers of the evolution of the Electronic Design Automation (EDA) industry through technology integration and market expansion. Here, we apply an AI-based clustering approach to unveil and explain the different waves of M&As. Two clustering algorithms are used: K-Means algorithm with the help of ML.NET to cluster the data based on some quantitative characteristics; and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) that uses a density-based approach to detect clusters and outliers. Temporal transformation is used for the historical data and feature vectors are encoded using temporal metrics and a combined business model encoding. The approach that is proposed offers actionable insights by building feature sets from the number of days since the earliest event, the operational lifetime of the acquired companies, and a technological impact score or encoded business model data. These patterns are useful for industry stakeholders to understand the market consolidation trends without the need to understand the details of the underlying infrastructure
The Role of Educators in Promoting Social-Emotional Learning Across Albania’s K-12 Education System
No full textSocial-emotional learning (SEL) is a critical educational framework that stresses the development of skills necessary for emotional intelligence, interpersonal relationships, and decision-making. It fosters a holistic approach to education, addressing both cognitive and emotional aspects of learning. This study aims to explore how educators facilitate SEL in the K-12 framework, emphasizing their understanding and application of SEL competencies in the Albanian educational context. A random sample of 367 educators from various K-12 institutions across Albania were surveyed using structured questionnaires to assess their perceptions and practices regarding SEL. The evaluation of the data was done using inferential as well as descriptive statistics. Educators’ roles in promoting SEL involve creating supportive classroom environments, integrating SEL into the curriculum, and employing active teaching strategies. This includes training sessions, and collaborative learning experiences that empower educators to nurture students’ emotional and social competencies effectively. The analysis incorporates independent sample t-tests and ANOVA to compare results across different educational contexts and levels. Findings are expected to reveal significant correlations between educators’ SEL competencies and students’ emotional well-being, highlighting the significance of continuous professional growth in SEL. Strengthening the role of educators in SEL implementation is vital for fostering resilient in Albania’s K-12 education system
The Role of the Court in the Bankruptcy Process: A Statistical and Comparative Case Study
No full textThis paper explores whether the court-centric model established by Albania\u27s Bankruptcy Law No. 110/2016 attains the expected efficiency, transparency, and creditor protection gains. This research develops the constitutionally imposed role of the courts in initiating, conducting, and completing bankruptcy processes, which is based on policy papers, parliamentary reports, and doctrinal analysis of the bankruptcy law. Utilizing a synthetic, yet real-world consistent dataset of completed cases in Albania and an EU benchmark group, it investigates the impact of court involvement on bankruptcy duration and outcome. Accordingly, this study uses descriptive statistics, two-way ANOVA, chi-square tests, and binary logistic regression to evaluate the interaction effects of country and judicial engagement in terms of case duration and reorganization outcome. It appears from the results that Albanian proceedings are far lengthier than EU cases at each point of the involvement scale, whereas in both systems, high court engagement is consistently associated with reduced duration. Outcome analysis reveals that Albania remains primarily liquidator, while the EU benchmark reaches a considerably higher proportion of reorganizations. The statistical models result in high explanatory power (above 0.82 for R² and Nagelkerke R²) to support the view that the institutional environment and the level of judicial oversight are crucial determinants of efficiency and rescue outcome. The results depict a gap between the formal goals of the 2016 reform and its actual performance, where improvement in judicial capacity, case management, and implementation practices is required for Albania\u27s court-cantered insolvency structure to reach its full potential
Strategic Human Resource Management and Its Impact on Organizational Performance: Empirical Insights
Full text linkIn light of today’s dynamic economy, Human Resource Management (HRM) has become a strategic lever for enhancing organizational performance, resilience, and long-term competitiveness. This study presents an original pioneering investigation into the strategic role of HRM within the Albanian private sector, making the first study of its kind in the country. It introduces an innovative conceptual model that integrates both HR roles and practices as dual expressions of HR strategy, offering a novel and internationally relevant framework. Grounded in more than two decades of international literature, the study applies a robust econometric approach to examine the multidimensional relationships between HRM and the performance of the organization. Data were collected through a structured questionnaire among private companies of varying sizes in Albania with over fifty employees. The evaluation was conducted using the Structural Equation Model (SEM) via the "LaVan" package in R. Findings reveal that key strategic components business strategy, the role of Human Resources, HR practices, and HR outcomes collectively contribute to strategic and internal fit, significantly enhancing organizational performance. By addressing a critical research gap in developing economies, this study establishes a strong theoretical and methodological foundation for future research both in Albania and in other transitional markets. The implications are particularly relevant for scholars, policymakers, and business leaders seeking to advance sustainable performance through strategic human resource development