Browsing by Author "Eslahi, Aida Vafae"

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    A Survey on securing smart finance using artificial intelligence and blockchai
    (Peninsula Publishing Press, 2026-01-10) Ali, Guma; Otim, Emmanuel; Mijwil, Maad M.; Buruga, Bosco Apparatus; Eslahi, Aida Vafae; Adamopoulos, Ioannis
    The rapid digitalization of financial services has given rise to smart finance ecosystems that integrate FinTech platforms, Internet of Things (IoT) devices, cloud infrastructures, and decentralized applications. While these systems enhance automation, operational efficiency, and financial inclusion, their highly distributed, data-intensive architectures introduce critical security, privacy, and trust challenges. In this context, artificial intelligence (AI) and blockchain have emerged as complementary technologies capable of addressing these challenges through intelligent decision-making, advanced threat detection, data integrity, and transparent operations. This survey provides a comprehensive review of recent research on securing smart finance systems using AI- and blockchain-based approaches. The survey comprehensively analyzed research published between 2023 and 2026 using the Scopus database, focusing on the keywords “AI,” “blockchain,” and “smart finance.” The analysis reveals extensive use of AI-driven security mechanisms, including credit scoring and risk assessment, transaction monitoring and fraud detection, anti-money laundering (AML) and know-your-customer compliance, identity verification, cyber threat detection, smart contract security analysis, behavioral biometrics, insurance fraud detection, and market risk prediction. In parallel, the survey examines blockchain-enabled security solutions, including secure payment and settlement systems, cross-border remittances, AML and counter-terrorism financing frameworks, digital identity management, smart contracts, asset tokenization, decentralized finance, auditability, and secure interbank communication. The integration of AI and blockchain offers significant advantages, including improved fraud detection accuracy, enhanced transparency and traceability, stronger data integrity, automated compliance, real-time threat response, and increased system resilience. Despite these benefits, key challenges persist, particularly in scalability, privacy preservation, interoperability, regulatory and ethical compliance, energy efficiency, explainability, and post-quantum security. The survey concludes by outlining future research directions and design guidelines for developing secure, scalable, and trustworthy smart finance systems that effectively leverage the integration between AI and blockchain.
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    Prevalence and clinical risk factors of stroke among hypertensive patients: A Cross-sectional study
    (Peninsula Press, 2026-03-09) Adamopoulos, Ioannis; Eslahi, Aida Vafae; Syrou, Niki; Mishra, Harshit; Tsirkas, Panagiotis; Ali, Guma
    Background: Stroke continues to be a primary cause of death and disability which mainly affects patients who have high blood pressure. The research set out to determine how often strokes occur together with their associated clinical risk factors in this specific patient group. Methods: Our research applied a quantitative method to perform a cross-sectional study which included 1,024 patients who had hypertension. Our research team conducted an analysis of 15 variables which included numerical data about patient age and their blood pressure readings and cholesterol measurements and categorical data about their gender and their heart disease status. Our research team conducted statistical analyses to identify which factors most strongly predicted the development of stroke in our patient population. Variables significant only in univariate analysis (p<0.05) but not retained after adjustment are displayed in the Univariate‑only section. ORs are plotted on a logarithmic scale, follows conventions consistent with Stata 17, data analysis through descriptive statistics and machine learning approaches while using Python and Excel as their main software applications. Results: Our research findings demonstrated that 25% of patients with hypertension developed strokes while age emerged as the most critical factor which increased stroke risk. The highest occurrence of 45% appeared in patients who were 70 years old or older. The research showed that glucose levels above 126 mg/dL together with obesity defined by a BMI of 30 kg/m² or higher served as important predictive factors which achieved statistical significance through p-values of 0.002 and 0.01. The presence of heart disease was also linked to increased stroke risk (p 0.001), emphasizing the need for comprehensive assessments in this demographic. Conclusion: The research findings reveal an urgent requirement for focused treatment programs which target adjustable risk elements including patient age and high blood sugar levels and excess body weight in people with hypertension. Our research shows that active control of these risk elements will lower the chance of stroke development which proves that patients need to follow specific lifestyle changes and maintain their health through scheduled checkups to achieve better results for their condition. Article