Healthcare organizations, realizing the potential of the Internet of Things (IoT)
technology, are rapidly adopting the technology to bring signi cant improvements in
the quality and e ectiveness of the service. However, these smart and interconnected
devices can act as a potential \back door" into a hospital's IT network, giving attack-
ers access to sensitive information. As a result, cyber-attacks on medical IoT devices
have been increasing since the last few years. It is a growing concern for all the
stakeholders involved, as the impact of such attacks is not just monetary or privacy
loss, but the lives of many patients are also at risk. Considering the various kinds of
IoT devices one may nd connected to a hospital's network, traditional host-centric
security solutions (e.g. antivirus, software patches) are at odds with realistic IoT
infrastructure (e.g. constrained hardware, lack of proper built-in security measures).
There is a need for security solutions which consider the challenges of IoT devices like
heterogeneity of technology and protocols used, limited resources in terms of battery
and computation power, etc. Accordingly, the goals of this thesis have been: (1) to
provide an in-depth understanding of vulnerabilities of medical IoT devices; (2) to in-
troduce a novel approach which uses a microservices-based framework as an adaptive and agile security solution to address the issue. The thesis focuses on OS Fingerprint-
ing attacks because of its signi cance for attackers to understand a target's network.
In this thesis, we developed three microservices, each one designed to serve a speci c
functionality. Each of these microservices has a small footprint with RAM usage of
approximately 50 MB. We also suggest how microservices can be used in a real-life
scenario as a software-based security solution to secure a hospital's network consisting
of di erent IoT devices. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2018. / FAU Electronic Theses and Dissertations Collection
| Identifer | oai:union.ndltd.org:fau.edu/oai:fau.digital.flvc.org:fau_40889 |
| Contributors | Trivedi, Ohm H. (author), Shankar, Ravi (Thesis advisor), Florida Atlantic University (Degree grantor), College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science |
| Publisher | Florida Atlantic University |
| Source Sets | Florida Atlantic University |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation, Text |
| Format | 136 p., application/pdf |
| Rights | Copyright © is held by the author with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder., http://rightsstatements.org/vocab/InC/1.0/ |
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