# Quantum Machine Learning for Security Assessment in the Internet of Medical Things (IoMT)
## 2 Background
### Security Flaws in IoMT Devices  
Many events, both in the real world and in academic research, have shown how serious IoT security flaws are and their potential consequences. The Open Web Application Security Project (OWASP), a group that works to improve software, publishes an annual list of the most dangerous security holes of IoT. Below are some examples of each of these mistakes. This flaw is often encountered in new malware. For example, we found a version of Mirai called Mukashi that used brute-force attacks with default credentials to get into Zyxel NAS systems by exploiting CVE-2020-9054. Mukashi was able to do so because it used a loophole. As part of our research into complex IoMT ecosystems, we found the medical platforms were exposed to security risks while connecting and operating various devices. The server for the home automation system was not locked down, so sensitive information, such as the geolocation of the homes and hard-coded passwords, was exposed. The effects of a compromised automation platform are further discussed in this research.  
The service providers with insecure networks aim to identify security flaws in products. The study showed that sensitive user information was leaked because the device had open ports that allowed it to connect to the Internet. It is not difficult to find examples of how people and networks have been compromised by device flaws, and more such cases are likely to occur in the future. The users need to know about these common flaws to protect themselves.  
Threat actors can use vulnerable devices to move laterally, which allows them to move closer to important targets. Attackers can use vulnerabilities to take over specific devices, convert them into weapons for use in larger campaigns, or even use them to spread malware across an entire network. IoT botnets are an example of how dangerous device vulnerabilities can be and how sophisticated cybercriminals' methods are in taking advantage of them. One of the most well-known types of IoT botnet malware is headlines, which use a network of thousands of infected home IoT devices to launch a distributed denial of service (DDoS) attack against a number of well-known websites [15]. There is no clear line between the security needs of businesses and homes. IoT devices, primarily when used for remote work, make that line even less clear. This is particularly true when people work in the same office. Bringing IoT devices into the home can increase the number of possible entry points for hackers. This could put the company's network and employees in danger. This is a major concern for bring-your-own-device rules and arrangements allowing people to work from home. In addition, attackers can use weak Internet of Things (IoT) devices to enter internal networks. The growing list of threats includes new attacks that use side channels, such as infrared laser beam attacks on smart devices in homes and businesses and domain name service (DNS) rebinding attacks that can collect and send information from within networks.  
The heterogeneity, velocity, and massivity in IoMT data communications pose serious challenges to traditional security solutions, as presented in Section 2.3.