This dissertation includes three approaches we have been designed to tackle threats and challenges in network, software, and mobile security. The first approach demonstrates a new class of content masking attacks against the Adobe PDF standard, causing documents to appear to humans dissimilar to the underlying content extracted by information-based services. The second work protects sensitive data in binaries from being corrupted by cyber attackers. The last work proposes a mechanism which utilizes the unique walking patterns inherent to humans and differentiate our work from other walking behavior studies by using it as first-order authentication and developing matching methods fast enough to act as an actual anti-theft system.
| Identifer | oai:union.ndltd.org:USF/oai:scholarcommons.usf.edu:etd-9135 |
| Date | 30 May 2019 |
| Creators | Shen, Dakun |
| Publisher | Scholar Commons |
| Source Sets | University of South Flordia |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Graduate Theses and Dissertations |
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