All features of DRAPA 2000 datasets.

<p>All features of DRAPA 2000 datasets.</p

A Survey: To Govern, Protect, and Detect Security Principles on Internet of Medical Things (IoMT)

The integration of medical equipment into the Internet of Things (IoT) led to the introduction of Internet of Medical Things (IoMT). Variation of IoT devices have been equipped in medical facilities. These devices provided convenience to healthcare provider since they can continuously monitor their patients in real-time, while allowing them to have greater physical flexibility and mobility. However, users of healthcare services (such as patients and medical staff) often are less concerned about security issues associated with IoT. These alleviate existing problems and jeopardize the lives of their patients by making them susceptible to attacks. Furthermore, IoMT applications have direct access to healthcare services because it handles sensitive patient information. Therefore, it is extremely important to preserve and establish the security and privacy of IoMT. This further justifies the need to investigate and address the related issues. Despite existing literature on security and privacy mechanisms, the domain still requires more attention. Therefore, this paper aims to discuss the security and privacy principles, as well as challenges associated with IoMT. Besides, a comprehensive analysis of privacy and security solutions for IoMT is also presented. In addition, we introduced a novel taxonomy of IoMT security and privacy based on cyber security principles such as &#x201C;govern,&#x201D; &#x201C;protect,&#x201D; and &#x201C;detect&#x201D;. In conclusion, this paper provides a discussion on existing challenges and future direction for researchers

Results of EM algorithm after feature e ranking.

<p>Results of EM algorithm after feature e ranking.</p

Results of K-means with varying number of clusters.

<p>Results of K-means with varying number of clusters.</p

List of attack steps (clusters) discovered on all dataset.

<p>List of attack steps (clusters) discovered on all dataset.</p

Results of Hierarchical based on seven selected features.

<p>Results of Hierarchical based on seven selected features.</p

Results of Hierarchical after feature ranking.

<p>Results of Hierarchical after feature ranking.</p

Feature ranking using IG on Inside 2 DARPA 2000 dataset.

<p>Feature ranking using IG on Inside 2 DARPA 2000 dataset.</p

Results of K-means after feature ranking.

<p>Results of K-means after feature ranking.</p

IDMEF alert format in an XML document.

<p>IDMEF alert format in an XML document.</p