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Ontological lockdown assessment : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Information Technology at Massey University, Palmerston North, New Zealand

In order to keep shared access computers secure and stable system administrators resort to locking down the computing environment in order to prevent intentional and unintentional damage by users. Skilled attackers are often able to break out of locked down computing environments and intentionally misuse shared access computers. This misuse has resulted in cases of mass identity theft and fraud, some of which have had an estimated cost ranging in millions. In order to determine if it is possible to break out of locked down computing environments an assessment method is required. Although a number of vulnerability assessment techniques exist, none of the existing techniques are sufficient for assessing locked down shared access computers. This is due to the existing techniques focusing on traditional, application specific, software vulnerabilities. Break out path vulnerabilities (which are exploited by attackers in order to break out of locked down environments) differ substantially from traditional vulnerabilities, and as a consequence are not easily discovered using existing techniques. Ontologies can be thought of as a modelling technique that can be used to capture expert knowledge about a domain of interest. The method for discovering break out paths in locked down computers can be considered expert knowledge in the domain of shared access computer security. This research proposes an ontology based assessment process for discovering break out path vulnerabilities in locked down shared access computers. The proposed approach is called the ontological lockdown assessment process. The ontological lockdown assessment process is implemented against a real world system and successfully identifies numerous break out path vulnerabilities.

Identiferoai:union.ndltd.org:ADTP/241336
Date January 2008
CreatorsSteele, Aaron
PublisherMassey University
Source SetsAustraliasian Digital Theses Program
LanguageEnglish
Detected LanguageEnglish

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