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Addressing Insider Threats: The Human Factor in Cybersecurity for Financial Institutions Hewa Majeed Zangana; Harman Salih Mohammed; Mamo Muhamad Husain
Journal of Innovation Information Technology and Application (JINITA) Vol 7 No 1 (2025): JINITA, June 2025
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v7i1.2686

Financial institutions face persistent cybersecurity threats, with insider threats emerging as a particularly complex challenge due to their human-centric nature. This study aims to examine the human factor in cybersecurity within financial institutions, with a focus on insider threats and strategies to mitigate them. A hybrid research approach was used, combining a systematic literature review (SLR) and qualitative case study analysis to investigate cybersecurity risks, AI-driven solutions, and regulatory compliance. The findings reveal that AI-powered toolsâ€”such as behavioral biometrics, machine learning, and blockchain technologiesâ€”substantially enhance fraud detection and risk management. Real-world implementations in financial institutions demonstrated improved threat response, reduced regulatory penalties, and increased operational efficiency. The study concludes that integrating technological tools with a strong cybersecurity culture can significantly mitigate insider threats.

Banking Cybersecurity: Safeguarding Financial Information in the Digital Era Hewa Majeed Zangana; Harman Salih Mohammed; Mamo Muhamad Husain
Journal of Computers and Digital Business Vol. 4 No. 2 (2025)
Publisher : PT. Delitekno Media Madiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56427/jcbd.v4i2.751

This study explores the escalating cybersecurity challenges in the banking sector and the potential of large language models (LLMs) to enhance digital defense mechanisms. Employing a qualitative methodology that includes a systematic literature review, expert interviews, and case study evaluations, the research investigates the integration of LLMs in cybersecurity operations such as threat detection, automated incident response, and user authentication. The findings reveal that LLMs offer significant advantages in real-time anomaly detection, predictive analytics, and natural language-based security training. However, their adoption is hindered by concerns over algorithmic transparency, data privacy, and the need for specialized technical expertise within financial institutions. A key contribution of this work is the development of an integrated cybersecurity framework that combines AI-driven technologies, blockchain-based transaction security, digital forensic tools, and human-centered security practices. The proposed framework aims to guide financial institutions in implementing adaptive, intelligent cybersecurity strategies aligned with evolving global regulatory standards. This research offers both theoretical insights and practical recommendations for enhancing cyber resilience in digital banking environments. It emphasizes the importance of a multidimensional approach that addresses technical innovation, organizational preparedness, and regulatory compliance. Future studies are encouraged to validate the proposed framework through empirical testing across diverse banking infrastructures.

The Role of Change Control Boards in Ensuring Cybersecurity Compliance for IT Infrastructure Hewa Majeed Zangana; Firas Mahmood Mustafa; Ayaz Khalid Mohammed; Marwan Omar
JITCE (Journal of Information Technology and Computer Engineering) Vol. 9 No. 1 (2025)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar

In the dynamic landscape of information technology, maintaining cybersecurity compliance is a paramount concern for organizations. Change Control Boards (CCBs) play a crucial role in this context, serving as a governance mechanism to oversee and manage changes within IT infrastructure. This paper explores the significance of CCBs in ensuring cybersecurity compliance, focusing on their functions, processes, and impact on organizational security posture. Through a comprehensive review of existing literature and case studies, the research highlights how CCBs facilitate risk assessment, enforce policy adherence, and mitigate potential threats arising from changes in the IT environment. The findings underscore the importance of structured change management and suggest best practices for integrating cybersecurity considerations into the CCB workflow. By understanding the role of CCBs, organizations can enhance their ability to safeguard sensitive data and maintain regulatory compliance in an ever-evolving threat landscape.

The Role of Change Control Boards in Ensuring Cybersecurity Compliance for IT Infrastructure Hewa Majeed Zangana; Firas Mahmood Mustafa; Ayaz Khalid Mohammed; Marwan Omar
JITCE (Journal of Information Technology and Computer Engineering) Vol. 9 No. 1 (2025)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar

In the dynamic landscape of information technology, maintaining cybersecurity compliance is a paramount concern for organizations. Change Control Boards (CCBs) play a crucial role in this context, serving as a governance mechanism to oversee and manage changes within IT infrastructure. This paper explores the significance of CCBs in ensuring cybersecurity compliance, focusing on their functions, processes, and impact on organizational security posture. Through a comprehensive review of existing literature and case studies, the research highlights how CCBs facilitate risk assessment, enforce policy adherence, and mitigate potential threats arising from changes in the IT environment. The findings underscore the importance of structured change management and suggest best practices for integrating cybersecurity considerations into the CCB workflow. By understanding the role of CCBs, organizations can enhance their ability to safeguard sensitive data and maintain regulatory compliance in an ever-evolving threat landscape.

AI-Driven Fraud Detection in Digital Banking: A Hybrid Approach using Deep Learning and Anomaly Detection Harman Salih Mohammed; Zina Bibo Sallow; Hewa Majeed Zangana
SISTEMASI Vol 15, No 1 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Universitas Islam Indragiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i1.5757

The rapid digital transformation in the banking sector has introduced new opportunities for efficiency and customer convenience but has also amplified the risks of financial fraud. Traditional fraud detection mechanisms, often reliant on static rule-based systems, struggle to keep pace with the dynamic, evolving nature of fraudulent activities. This paper proposes a novel hybrid framework that integrates deep learning models with anomaly detection techniques to enhance the accuracy, robustness, and adaptability of fraud detection in digital banking. The proposed approach leverages a deep neural network (DNN) architecture trained under supervised learning to capture complex transactional patterns and combines it with autoencoder-based unsupervised anomaly detection to uncover previously unseen fraud strategies. Extensive experiments on benchmark financial datasets demonstrate that the hybrid system significantly outperforms state-of-the-art methods in terms of precision, recall, and false-positive reduction. Furthermore, the study highlights the scalability of the approach for real-time banking applications and its potential for multi-institutional deployment, enabling secure inter-bank fraud intelligence sharing without compromising data privacy. Extensive experiments on benchmark financial datasets demonstrate that the hybrid system significantly outperforms state-of-the-art methods in terms of precision, recall, and false-positive reduction. Furthermore, the study highlights the scalability of the approach for real-time banking applications. This work contributes to the growing field of AI-driven financial security by addressing both detection performance and adaptability to emerging fraud behaviors.

Cybernetic Deception: Unraveling the Layers of Email Phishing Threats Hewa Majeed Zangana; Ayaz Khalid Mohammed; Amira Bibo Sallow; Zina Bibo Sallow
International Journal of Research and Applied Technology Vol. 4 No. 1 (2024): International Journal of Research and Applied Technology (INJURATECH)
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/injuratech.v4i1.13620

E-mail phishing, a tireless and versatile cybersecurity risk, requires a intensive examination to fortify organizational resistances. This broad survey dives into the multifaceted measurements of e-mail phishing, including mental control strategies, mechanical complexities, and real-world experiences determined from assorted case considers. The investigation of location and anticipation procedures covers a extend of commitments, tending to half breed machine learning approaches, the significance of client instruction, and the part of administrative compliance. These procedures give a significant system for organizations pointing to improve their flexibility against the energetic scene of phishing strategies. The theoretical underscores the administrative landscape's significant part in forming cybersecurity hones, advertising a organized establishment for organizations to adjust with legitimate prerequisites. Expecting future patterns and challenges, such as the integration of characteristic dialect preparing procedures and the complexities of cloud-based phishing assaults, gets to be basic for maintained cyber versatility. In conclusion, this paper serves as a comprehensive direct, enabling people and organizations with the information and methodologies required to explore the complex scene of e-mail phishing dangers. It recognizes the energetic nature of the danger scene, highlighting the progressing travel in combating computerized duplicity and invigorating preparation against the ever-evolving strategies of phishing foes.

Navigating the Digital Marketplace: A Comprehensive Review of E-Commerce Trends, Challenges, and Innovations Hewa Majeed Zangana; Natheer Yaseen Ali; Ayaz khalid Mohammed
TIJAB (The International Journal of Applied Business) Vol. 8 No. 1 (2024): APRIL 2024
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/tijab.v8.I1.2024.54618

Background: Comprehensive exploration of e-commerce landscape; Insights drawn from diverse scholarly sources across disciplines. Objective: Examine key themes, including COVID-19 impact, consumer behavior, business models, regulatory challenges, security, privacy, opportunities, and future trends in digital commerce. Method: The methodology involved a comprehensive literature review spanning various disciplines to explore e-commerce. Scholarly sources were gathered from academic databases and journals, focusing on key themes like the COVID-19 impact, consumer behavior, business models, regulatory challenges, security, privacy, opportunities, and future trends. Data analysis identified patterns and trends, with findings organized into distinct sections. Synthesizing and interpreting the results within the e-commerce context, along with peer feedback, ensured the study's rigor and credibility. Results: Uncover sustained shift in consumer preferences influenced by the pandemic; Provide insights into strategic approaches adopted by businesses in the digital marketplace. Conclusion: Anticipate future e-commerce trajectory, discussing emerging trends like metaverse integration, AI, augmented reality shopping, voice commerce, and online-offline convergence; Serve as a guide for businesses navigating challenges, seizing opportunities, and aligning with emerging trends; Offer a comprehensive understanding of the dynamic nature of e-commerce in the digital age. Keywords: Artificial Intelligence; Business; E-Commerce; Marketing.

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