• Hybrid fraud detection model for financial institutions. 

  Mwarangu, Danson Gikonyo (Cuk, 2025)

  Digitization has significantly expanded access to financial services while simultaneously increasing the exposure of financial platforms to fraud. Institutions globally are adopting machine learning (ML) to detect emerging ...
• A hybrid machine learning based model to enhance detection of zero day attacks. 

  John, Dominic Kavoi (Cuk, 2025)

  In the current technological landscape, a lot of risks are present due to the availability of existing and novel kinds of attacks. For these attacks to be countered, systems that identify all the variants without any false ...
• Case based reasoning model to optimize sentencing guidelines in the judiciary of Kenya. 

  Charani, Donald Asiago (Cuk, 2025)

  Judicial sentencing often faces challenges of inconsistency and disparity, undermining both fairness and public trust. Existing guidelines provide direction, but variations persist due to the subjective interpretation of ...
• An adaptive machine learning model for real time detection and mitigation of oit intrusion threats 

  Kilonzi, Mwende Elizabeth (Cuk, 2025)

  The rapid expansion of Internet of Things (IoT) deployments has increased system exposure to advanced cyber threats such as Distributed Denial-of-Service (DDoS) attacks, botnet infections, and zero-day exploits. Traditional ...
• Leveraging machine learning for diabetes prediction:Ensemble model 

  Otieno Ogutu, McDonald (Cuk, 2025)

  Diabetes presents a great global health challenge, with delayed diagnosis significantly impeding effective management, particularly in resource-constrained regions. The critical shortage of medical professionals in regions ...

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