With growing healthcare demands, the Internet of Medical Things (IoMT) has grown significantly in recent years and is dominating the healthcare industry. However, these smarter and advanced medical devices are “more” complicated in terms of software and hardware, with several defects and vulnerabilities that have been found and can lead to possible malicious attacks. Healthcare organizations are the new focus of attackers for carrying out IoMT-focused cyberattacks, which are becoming more common. In recent years, ransomware and distributed denial of service (DDoS) attacks are malware-based popular attacks on IoMT devices. Cyberattacks and disruptions in clinical care can have a catastrophic effect on patient safety, which trickles down to the medical staff’s responsiveness. Moreover, because different medical devices have varying vital capabilities, it is critical to enable differentiated network services for these devices with varying critical levels of operation under network dynamics. Hence, it becomes crucial to efficiently detect and identify any malicious network activities to eliminate or minimize the impact of these attacks, as well as to detect and identify network traffics belonging to different medical equipment.

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The threats to the cybersecurity of today’s organizations’ networks are numerous, vastly varied and constantly evolving. According to a very recent report, about 81 percent of US organizations have faced a cyberattack. Operational downtime was the biggest impact for those organizations (55 percent), followed by compromised customer data (37 percent), and compromised end-user safety (36 percent). Most recently, the COVID-19 pandemic has reared its ugly head – cyberattacks have become more common and have large increased very recently. However, the scale of contemporary network traffic volumes makes monitoring and visualizing real-time information considerably more challenging for human ability to process. Although many IDSs utilizes several visualization techniques and notification mechanisms to provide administrators with an overall view and specific information about particular traffic or attacks on the network, they often still fail to represent the events in an understandable way, and it is quite difficult to understand the relevance of aggregate traffic when receiving only the alarms for individual intrusion records. Moreover, these tools are not well suited for continuous monitoring scenarios since network administrators will suffer from loss of concentration, visual fatigue, temporal demand, and frustration increase.

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 Online presence and the spread of misinformation have long been significant social and public health concerns. For example, during the COVID-19 pandemic, the amount and frequency of social media consumption increased, and information about COVID-19 spread rapidly on social media platforms, including both inaccurate and misleading information. This content appears to have contributed to beliefs in conspiracy theories and misinformation, as use of social media is associated with increased conspiracy theory and misinformation beliefs. This specific COVID-19 vaccine misinformation is in addition to the already high levels of misinformation about vaccines in general, and significant levels of misinformation related to other issues, such as climate change, which often claim that evidence-based scientific approaches are harmful or do not work. The viral spread of digital misinformation has become so serious that the World Economic Forum considers it among the main threats to human society. Therefore, training and educating people on how to recognize misinformation, verify sources, and then make responsible decisions on the sharing of information is therefore of paramount importance.

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