Neumann, Stephan ; Volkamer, Melanie ; Budurushi, Jurlind ; Prandini, Marco (2016)
SecIVo: a quantitative security evaluation framework for internet voting schemes.
In: >Annals of Telecommunications
doi: 10.1007/s12243-016-0520-0
Article, Bibliographie
Abstract
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.
Item Type: | Article |
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Erschienen: | 2016 |
Creators: | Neumann, Stephan ; Volkamer, Melanie ; Budurushi, Jurlind ; Prandini, Marco |
Type of entry: | Bibliographie |
Title: | SecIVo: a quantitative security evaluation framework for internet voting schemes |
Language: | German |
Date: | June 2016 |
Journal or Publication Title: | >Annals of Telecommunications |
DOI: | 10.1007/s12243-016-0520-0 |
Abstract: | 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. |
Uncontrolled Keywords: | Security, Usability and Society;Secure Data |
Identification Number: | TUD-CS-2016-0128 |
Divisions: | 20 Department of Computer Science > Theoretical Computer Science - Cryptography and Computer Algebra 20 Department of Computer Science > SECUSO - Security, Usability and Society LOEWE > LOEWE-Zentren > CASED – Center for Advanced Security Research Darmstadt Profile Areas > Cybersecurity (CYSEC) LOEWE > LOEWE-Zentren 20 Department of Computer Science Profile Areas LOEWE |
Date Deposited: | 28 Jul 2016 18:35 |
Last Modified: | 15 May 2018 10:33 |
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