Mobile Agent based Intrusion Detection for Smart and Connected Medical Devices
| dc.contributor.advisor | Thamilarasu, Geethapriya | |
| dc.contributor.author | Odesile, Adedayo | |
| dc.date.accessioned | 2017-08-11T22:46:08Z | |
| dc.date.issued | 2017-08-11 | |
| dc.date.submitted | 2017-06 | |
| dc.description | Thesis (Master's)--University of Washington, 2017-06 | |
| dc.description.abstract | The advent of wearable and implantable devices have fostered recent advances in healthcare. Medical devices equipped with wireless connectivity to remote monitoring features are increasingly becoming connected to each other and the internet. Such smart and connected medical devices referred to as the Internet of Medical Things have enabled continuous real-time patient monitoring, increase in diagnostic accuracy, and effective treatment. Inspite of their numerous benefits, these devices open up newer attack surfaces thereby introducing multitude of security and privacy concerns. In this research, we design and develop a mobile agent based intrusion deteciton system to secure the network of connected medical devices. In particular, the proposed system is hierarchical, autonomous, and employs machine and regression algorithms to detect network level intrusions as well as anomalies in sensor data. Our simulation results reflect a relatively high detection accuracy with minimal resource overhead. | |
| dc.embargo.lift | 2020-08-01T22:46:08Z | |
| dc.embargo.terms | Restrict to UW for 3 years -- then make Open Access | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.other | Odesile_washington_0250O_17569.pdf | |
| dc.identifier.uri | http://hdl.handle.net/1773/39858 | |
| dc.language.iso | en_US | |
| dc.rights | CC BY | |
| dc.subject | intrusion detection | |
| dc.subject | IoT | |
| dc.subject | medical devices | |
| dc.subject | mobile agent | |
| dc.subject | security | |
| dc.subject | wban | |
| dc.subject | Computer science | |
| dc.subject.other | To Be Assigned | |
| dc.title | Mobile Agent based Intrusion Detection for Smart and Connected Medical Devices | |
| dc.type | Thesis |
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