Accountability in smart grid and medical sensor network
| dc.contributor | Vrbsky, Susan V. | |
| dc.contributor | Zhang, Jingyuan | |
| dc.contributor | Hong, Xiaoyan | |
| dc.contributor | Li, Shuhui | |
| dc.contributor.advisor | Xiao, Yang | |
| dc.contributor.author | Liu, Jing | |
| dc.contributor.other | University of Alabama Tuscaloosa | |
| dc.date.accessioned | 2017-03-01T16:46:41Z | |
| dc.date.available | 2017-03-01T16:46:41Z | |
| dc.date.issued | 2013 | |
| dc.description | Electronic Thesis or Dissertation | en_US |
| dc.description.abstract | Although advanced cyber security technology has protected every level of current network infrastructure, vulnerabilities continue to emerge after new functions are added. As a complement, accountability is required to further secure the network in terms of privacy, integrity, and confidentiality. Even if a security issue presents itself, the built-in accountability mechanism will find out who is responsible for it. This dissertation mainly studies existing technologies of accountability and tries to address several important cyber security issues using these techniques. One specific problem has been raised in smart grids. As we know, power utility company charges customers solely based on readings from their power meters. Considering operating cost, the utility just measures aggregated power supply to a service area. Once a meter is compromised by cyber attacks, the utility can hardly find it out and thus may have economic loss. To make the smart grid more reliable, we proposed accountable metering systems in both home area and neighborhood area networks. Analysis and simulation results show that abnormal meters could be effectively identified under certain reasonable assumptions. Another case is the medical sensor network (MSN). In this context, patients are deployed with medical sensors and wearable devices and are remotely monitored by professionals. Since it is an economical way to reduce healthcare costs and save medical resources, we expect a robust, reliable, and scalable MSN in the near future. However, the time signal and temporal history in current MSN are vulnerable due to unsecured infrastructure and transmission strategies. Meanwhile, the MSN may leak patients' identifications or other sensitive information that violates personal privacy. To make sure the correctness of critical time signal, we presented two temporal accountability schemes for the MSN. In the meantime, these schemes also provide privacy-preserving ability. | en_US |
| dc.format.extent | 171 p. | |
| dc.format.medium | electronic | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.other | u0015_0000001_0001177 | |
| dc.identifier.other | Liu_alatus_0004D_11441 | |
| dc.identifier.uri | https://ir.ua.edu/handle/123456789/1653 | |
| dc.language | English | |
| dc.language.iso | en_US | |
| dc.publisher | University of Alabama Libraries | |
| dc.relation.hasversion | born digital | |
| dc.relation.ispartof | The University of Alabama Electronic Theses and Dissertations | |
| dc.relation.ispartof | The University of Alabama Libraries Digital Collections | |
| dc.rights | All rights reserved by the author unless otherwise indicated. | en_US |
| dc.subject | Computer science | |
| dc.subject | Computer engineering | |
| dc.title | Accountability in smart grid and medical sensor network | en_US |
| dc.type | thesis | |
| dc.type | text | |
| etdms.degree.department | University of Alabama. Department of Computer Science | |
| etdms.degree.discipline | Computer Science | |
| etdms.degree.grantor | The University of Alabama | |
| etdms.degree.level | doctoral | |
| etdms.degree.name | Ph.D. |
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