The Industrial Revolution 4.0 began with the breakthrough technological advances in 5G, and artificial intelligence has innovatively transformed the manufacturing industry from digitalization and automation to the new era of smart factories. A smart factory can do not only more than just produce products in a digital and automatic system, but also is able to optimize the production on its own by integrating production with process management, service distribution, and customized product requirement. A big challenge to the smart factory is to ensure that its network security can counteract with any cyber attacks such as botnet and Distributed Denial of Service, They are recognized to cause serious interruption in production, and consequently economic losses for company producers. Among many security solutions, botnet detection using honeypot has shown to be effective in some investigation studies. It is a method of detecting botnet attackers by intentionally creating a resource within the network with the purpose of closely monitoring and acquiring botnet attacking behaviors. For the first time, a proposed model of botnet detection was experimented by combing honeypot with machine learning to classify botnet attacks. A mimicking smart factory environment was created on IoT device hardware configuration. Experimental results showed that the model performance gave a high accuracy of above 96%, with very fast time taken of just 0.1 ms and false positive rate at 0.24127 using random forest algorithm with Weka machine learning program. Hence, the honeypot combined machine learning model in this study was proved to be highly feasible to apply in the security network of smart factory to detect botnet attacks.
Over the last year, the dangerous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread rapidly around the world. Malaysia has not been excluded from this COVID-19 pandemic. The resurgence of COVID-19 cases has overwhelmed the public healthcare system and overloaded the healthcare resources. Ministry of Health (MOH) Malaysia has adopted an Emergency Ordinance (EO) to instruct private hospitals to receive both COVID-19 and non-COVID-19 patients to reduce the strain on public facilities. The treatment of COVID-19 patients at private hospitals could help to boost the bed and critical care occupancy. However, with the absence of insurance coverage because COVID-19 is categorised as pandemic-related diseases, there are some challenges and opportunities posed by the treatment fees management. Another major issue in the collaboration between public and private hospitals is the willingness of private medical consultants to participate in the management of COVID-19 patients, because medical consultants in private hospitals in Malaysia are not hospital employees, but what are termed "private contractors" who provide patient care services to the hospitals. Other collaborative measures with private healthcare providers, e.g. tele-conferencing by private medical clinics to monitor COVID-19 patients and the rollout of national vaccination programme. The public and private healthcare partnership must be enhanced, and continue to find effective ways to collaborate further to combat the pandemic. The MOH, private healthcare sectors and insurance providers need to have a synergistic COVID-19 treatment plans to ensure public as well as insurance policy holders have equal opportunities for COVID-19 screening tests, vaccinations and treatment.