Cyber supply chain threat analysis and prediction using machine learning and ontology

Cyber Supply Chain (CSC) security requires a secure integrated network among the sub-systems of the inbound and outbound chains. Adversaries are deploying various penetration and manipulation attacks on an CSC integrated network’s node. The different levels of integrations and inherent system complexities pose potential vulnerabilities and attacks that may cascade to other parts of the supply chain system. Thus, it has become imperative to implement systematic threats analyses and predication within the CSC domain to improve the overall security posture. This paper presents a unique approach that advances the current state of the art on CSC threat analysis and prediction by combining work from three areas: Cyber Threat Intelligence (CTI), Ontologies, and Machine Learning (ML). The outcome of our work shows that the conceptualization of cybersecurity using ontological theory provides clear mechanisms for understanding the correlation between the CSC security domain and enables the mapping of the ML prediction with 80% accuracy of potential cyberattacks and possible countermeasures

Effect of voice reminder on compliance with recommended hand hygiene practise among health-care workers in Kano metropolis.

BACKGROUND: Poor compliance with recommended hand hygiene practise by health-care workers is an emerging public health threat associated with significant morbidity, mortality and spread of multidrug-resistant microorganisms. OBJECTIVE: This study assessed the effect of voice reminder on compliance with recommended hand hygiene practise among the baseline, and post-intervention compliance with recommended hand hygiene among health-care workers using the WHO checklist for observation of 5-moments of hand hygiene of health-care workers in Kano. METHODS: Quasi-experimental study design was used. A total of 408 (204 in each arm) baseline and post-intervention observations were conducted in two hospitals in Kano, selected using a multistage sampling technique. Voice reminders were installed in the intervention hospital, and post-intervention observation was conducted 3 months after introducing a voice reminder. SPSS version 22.0 was used for data analysis. Relationship between variables was tested using χ2 and McNemar's test within the groups at 0.05 α-level of significance. RESULTS: Baseline compliance with hand hygiene in the intervention and control hospitals were 31.4% and 48.0%, respectively. Post-intervention compliance in the intervention and control hospitals were found to be 78.0% and 65.2%, respectively. Voice reminder improved compliance with hand hygiene practise when compared with baseline by +148% (P# = 0.3) in the intervention hospital compared with +36% (P# =0.1) in the control hospital. The differences were not statistically significant post-intervention when compared with the baseline. CONCLUSIONS: Voice reminder intervention improved hand hygiene compliance among health-care workers in the intervention hospital compared with the control hospital. Voice reminders should be provided in the hospitals by stakeholders. This can help in improving compliance with hand hygiene among health-care workers and reducing the burden of hospital-acquired infections due to the hands of health-care workers