SecIVo: a quantitative security evaluation framework for internet voting schemes

Voting over the Internet is subject to a number of security requirements. Each voting scheme has its own bespoke set of assumptions to ensure these security requirements. The criticality of these assumptions depends on the election setting (e.g., how trustworthy the voting servers or the voting devi...

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Veröffentlicht in:Annales des télécommunications 2016-08, Vol.71 (7-8), p.337-352
Hauptverfasser: Neumann, Stephan, Volkamer, Melanie, Budurushi, Jurlind, Prandini, Marco
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Sprache:eng
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Zusammenfassung:Voting over the Internet is subject to a number of security requirements. Each voting scheme has its own bespoke set of assumptions to ensure these security requirements. The criticality of these assumptions depends on the election setting (e.g., how trustworthy the voting servers or the voting devices are). The consequence of this is that the security of different Internet voting schemes cannot easily be compared. We have addressed this shortcoming by developing SecIVo, a quantitative security evaluation framework for Internet voting schemes. On the basis of uniform adversarial capabilities, the framework provides two specification languages, namely qualitative security models and election settings. Upon system analysis, system analysts feed the framework with qualitative security models composed of adversarial capabilities. On the other side, election officials specify their election setting in terms of—among others—expected adversarial capabilities. The framework evaluates the qualitative security models within the given election setting and returns satisfaction degrees for a set of security requirements. We apply SecIVo to quantitatively evaluate Helios and Remotegrity within three election settings. It turns out that there is no scheme which outperforms the other scheme in all settings. Consequently, selecting the most appropriate scheme from a security perspective depends on the environment into which the scheme is to be embedded.
ISSN:0003-4347
1958-9395
1958-9395
DOI:10.1007/s12243-016-0520-0