Knock! Knock! Who Is There? Investigating Data Leakage from a Medical Internet of Things Hijacking Attack

Simple item page
dc.contributor.authorFlynn, Talon
dc.contributor.authorGrispos, George
dc.contributor.authorGlisson, William
dc.contributor.authorMahoney, William
dc.date.accessioned2020-01-04T08:31:35Z
dc.date.available2020-01-04T08:31:35Z
dc.date.issued2020-01-07
dc.description.abstractThe amalgamation of Medical Internet of Things (MIoT) devices into everyday life is influencing the landscape of modern medicine. The implementation of these devices potentially alleviates the pressures and physical demands of healthcare systems through the remote monitoring of patients. However, there are concerns that the emergence of MIoT ecosystems is introducing an assortment of security and privacy challenges. While previous research has shown that multiple vulnerabilities exist within MIoT devices, minimal research investigates potential data leakage from MIoT devices through hijacking attacks. The research contribution of this paper is twofold. First, it provides a proof of concept that certain MIoT devices and their accompanying smartphone applications are vulnerable to hijacking attacks. Second, it highlights the effectiveness of using digital forensics tools as a lens to identify patient and medical device information on a hijacker’s smartphone.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2020.791
dc.identifier.isbn978-0-9981331-3-3
dc.identifier.urihttp://hdl.handle.net/10125/64533
dc.language.isoeng
dc.relation.ispartofProceedings of the 53rd Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectMachine Learning and Cyber Threat Intelligence and Analytics
dc.subjectcybercrime
dc.subjectforensics
dc.subjecthijacking
dc.subjectinternet of things
dc.subjectmedical
dc.subjectsecurity
dc.titleKnock! Knock! Who Is There? Investigating Data Leakage from a Medical Internet of Things Hijacking Attack
dc.typeConference Paper
dc.type.dcmiText

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
0638.pdf
Size:
543.11 KB
Format:
Adobe Portable Document Format
Download

Collections

Machine Learning and Cyber Threat Intelligence and Analytics