Samuel Ufom Okon

Enhancing Transparency and Accountability in Public Service through Open Data Initiatives: Insights from Estonia and Policy Recommendations for the United States

Samuel Ufom Okon · Asian Journal of Economics, Business and Accounting · 2024

This study addresses the challenge of enhancing transparency and accountability in public governance, focusing on the role of open data initiatives. The study evaluates key aspects of open data initiatives in both Estonia and the U.S., emphasizing the differences and similarities...

Open access Research Article 10.9734/ajeba/2024/v24i91496

Incorporating Privacy by Design Principles in the Modification of AI Systems in Preventing Breaches across Multiple Environments, Including Public Cloud, Private Cloud, and On-prem

Samuel Ufom Okon, Omobolaji Olufunmilayo Olateju, Olumide Samuel Ogungbemi, Sunday Abayomi Joseph, Anthony Obulor Olisa & Oluwaseun Oladeji Olaniyi · Journal of Engineering Research and Reports · 2024

The rapid integration of artificial intelligence (AI) across various sectors has significantly amplified privacy concerns, particularly with the growing reliance on cloud environments. Existing methods often fall short of effectively preventing privacy breaches due to inadequate...

Open access Research Article 10.9734/jerr/2024/v26i91269

Exploring the Concept of Explainable AI and Developing Information Governance Standards for Enhancing Trust and Transparency in Handling Customer Data

Omobolaji Olufunmilayo Olateju, Samuel Ufom Okon, Oluwaseun Oladeji Olaniyi, Amaka Debie Samuel-Okon & Christopher Uzoma Asonze · Journal of Engineering Research and Reports · 2024

The increasing integration of Artificial Intelligence (AI) systems in diverse sectors has raised concerns regarding transparency, trust, and ethical data handling. This study investigates the impact of Explainable AI (XAI) models and robust information governance standards on enh...

Open access Research Article 10.9734/jerr/2024/v26i71206

Combating the Challenges of False Positives in AI-Driven Anomaly Detection Systems and Enhancing Data Security in the Cloud

Omobolaji Olufunmilayo Olateju, Samuel Ufom Okon, Udochukwu ThankGod Ikechukwu Igwenagu, Abidemi Ayodotun Salami, Tunbosun Oyewale Oladoyinbo & Oluwaseun Oladeji Olaniyi · Asian Journal of Research in Computer Science · 2024

Anomaly detection is critical for network security, fraud detection, and system health monitoring applications. Traditional methods like statistical approaches and distance-based techniques often struggle with high-dimensional and complex data, leading to high false positive rate...

Open access Research Article 10.9734/ajrcos/2024/v17i6472

Formulating Global Policies and Strategies for Combating Criminal Use and Abuse of Artificial Intelligence

Amaka Debie Samuel-Okon, Omobolaji Olufunmilayo Olateju, Samuel Ufom Okon, Oluwaseun Oladeji Olaniyi & Udochukwu ThankGod Ikechukwu Igwenagu · Archives of Current Research International · 2024

This study investigates the criminal use and abuse of artificial intelligence (AI), exploring the effectiveness of various mitigation strategies. It employs a mixed-methods approach, combining quantitative data from a survey of 211 experts with qualitative insights from academic,...

Open access Research Article 10.9734/acri/2024/v24i5735