# Internet of Things Botnet Detection Approaches: Analysis and Recommendations for Future Research
## 7 Discussion
### IoT Botnets during the COVID-19 Pandemic  
The WHO Emergency Committee declared a global health emergency in January 2020 on the basis of rising case reporting rates for the novel coronavirus that spread to many countries [114]. Due to this worldwide pandemic of COVID-19 and its implications, the use of the Internet has been increased. Hence, every organization today, whether governmental or private, is digital and relies on the Internet and computer networks to exchange business data. There is an immediate need to make full use of available technologies, since there are changes in customer behavior, new ways of working and travel restrictions. Therefore,the Internet of Things (IoT) is considered to be one of the highly innovative technologies with great potential in the fight against coronavirus outbreaks. The IoT consists of a scarce network in which IoT devices sense the world, collect data and send useful data to the Internet. As IoT is rapidly being adopted in the context of COVID-19 [121], the value of IoT has significantly increased in the presence of this disease, and the number of Web-connected devices has increased, but most devices have little to no security features. The first quarter of 2020 showed a considerable increase in malware. There was a 58% increase in new IoT malware [122]. Consequently, the magnitude and complexity of the IoT botnet threats have gradually increased; IoT botnets exploit more vulnerabilities and cause evermore malicious activities. These activities include information theft and persistence threats, which impact critical systems through exfiltration channels and resource hijacking to convert the IoT devices into bots. This raises the need for similarly complex detection systems. It is projected that the need for IoT botnet detection is increasing at a significant rate due to the COVID-19 pandemic. Various methods, along with sensors and wireless communication techniques, could be used to build secure systems suitable for COVID-19 detection and monitoring. Many industries are using IoT to meet the requirements of government responses to COVID-19 [114] and are being targeted by attacks as a consequence, including healthcare, education, finance, retail and entertainment industries [122]. Given the importance of managing the COVID-19 pandemic globally and ensuring social distance, healthcare IoT devices have recently become more connected to the Internet as part of the linked health environment. With the aim of automating healthcare procedures, different applications are being employed to retrieve electronic health histories and medical files created by healthcare IoT devices in hospitals. As a result of the widespread outbreak triggered by the human-to-human spread of COVID-19, health officials exploited IoT devices to identify COVID-19 patients. With the intention of enabling faster diagnosis, different models have been utilized, such as X-ray images, ultrasound symptom detection, CT scan images, ICU data gathering, non-intrusive facial-recognition hospital profile examinations and others. Healthcare systems are highly important, as they provide life-critical services. Effective cyber-attacks on healthcare would directly endanger not only the protection of networks and information, but also the health and safety of patients--they may threaten lives. The impacts of cyber-attacks on healthcare facilities are large. They can range from malware that compromises the security of the infrastructure and privacy of patients to distributed denial of service (DDoS) attacks that threaten the ability of the facilities to provide patient care. In the last two quarters of 2020, a high rate of cyber-attacks by various actors against the healthcare sector has been observed. These actors aim to infect vital healthcare networks with various forms of cyber-attacks by using a variety of strategies, techniques and procedures (TTPs) to gain initial access and further exfiltrate sensitive health sector data.