ABSTRACT: Machine learning (ML)-orchestrated attacks have necessitated advanced security strategies to secure organizations sensitive transaction data with the emergence of sophisticated persistent ML cyberthreat in the digital era. This paper examined the evolving cyber-attacks, emphasizing the need for proactive and dynamic defense strategies. The paper highlights how attackers utilize advanced ML technique, to perpetrate attacks.
ABSTRACT: Africa faces a critical cybersecurity skills gap that formal education alone has been unable to close. This paper presents a research-informed framework for addressing this challenge by drawing on the Igbo Apprenticeship System (IAS), a community-based, semi-structured model of knowledge transfer indigenous to Southeastern Nigeria. Grounded in the principle of Onye Aghala Nwanneya (“no
ABSTRACT: Alzheimer’s disease (AD) is the most common type of dementia that affects more than 10% of the global population, and early detection is crucial in enabling effective treatment and care measures. One of the first structural alterations in Alzheimer’s patients is seen in the hippocampus, a sub cortical region of the brain important for
ABSTRACT: AI in banking is a rapidly growing area, and understanding user perception is crucial, especially in a developing market like Nigeria. The focus on it’s embrace over the commercial banking is particularly important, as trust is a significant barrier to the adoption of new technologies, especially in financial sectors. The surge in adoption of
ABSTRACT: The Belief Rule Base (BRB) expert systems have emerged as a prominent approach in expert knowledge representation and reasoning. BRB systems offer interpretability through easily understandable IF-THEN rules, facilitating validation by domain experts and enabling insight into the inference process. However, conventional BRB systems encounter challenges such as: combinatorial explosion, suboptimal parameter learning, and
ABSTRACT Smart homes enable remote control of appliances and increase user convenience, but a major challenge persists in detecting intruders with masked or covered faces. Existing systems, although effective under normal conditions, are not accurate when faces are obscured. The aim of this research is to develop an anti-theft model that accurately detects intruders even
ABSTRACT Leveraging machine learning algorithms to accurately predict patients who are unlikely to adhere to their prescribed medication and to target them with delivery of personalized and persuasive messages can be very effective and efficient in improving medication adherence. In this study, ANFIS prediction of patient’s non-adherence to medication and intervention system was developed to
ABSTRACT Artificial intelligence (AI) is a cutting-edge technology that allows machines to act intelligently and carry out certain tasks with or without human assistance. AI has revolutionised fields such as education, industry, agriculture, and governance. Recently, these fields have faced many challenges ranging from high-cost project implementation, technological bias, policy adoption, and highly personified algorithms
ABSTRACT This paper challenges the deterministic claim that artificial intelligence (AI) will inevitably lead to widespread job loss, arguing instead that such assertions often stem from flawed causal reasoning. Drawing on the fallacy illustrated by Texas State University’s elevator example and philosophical insights from Karl Popper and David Hume, the paper critiques the post hoc
ABSTRACT The banking sector, which is central to the economic structure, has become a primary target for cybercrime due to the adoption of digital banking and the increasing sophistication of cybercriminals. This not only poses a danger to banking sectors and their clientele, but also to people’s livelihoods and the stability of the global economy.