Abstract
Recently, multiple cryptographic schemes for data collection with self-enforcing privacy were proposed by Golle et al. The schemes allow participants of electronic polls to prove a pollster’s guilt if he distributes responses. Introducing punitive damages for such misbehaviour creates incentives for a pollster to protect the respondents’ privacy. To achieve fairness, a proof must be feasible if and only if a pollster indeed leaked information. This paper analyses the scheme proposed for self-enforcing privacy with no release of data. Neither parameter publication nor cooperative indictment have been defined up to now. We show that both are of key importance to ensure fairness and describe potential attacks of a malicious pollster. After a detailed analysis, we propose two extensions preventing such actions. In addition, a possibility for the pollster to gain an unfair advantage in the basic scheme is identified and according checks put forward.
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Golle, P., McSherry, F., Mironov, I.: Data collection with self-enforcing privacy. In: CCS ’06: Proceedings of the 13th ACM Conference on Computer and Communications Security, pp. 69–78. ACM, New York (2006)
Golle, P., McSherry, F., Mironov, I.: Data collection with self-enforcing privacy. ACM Transactions on Information System Security (TISSEC) 12(2), 1–24 (2008)
Cox, I.J., Miller, M.L.: The First 50 Years of Electronic Watermarking. EURASIP Journal on Applied Signal Processing 2002(2), 126–132 (2002)
El Gamal, T.: A public key cryptosystem and a signature scheme based on discrete logarithms. In: Blakely, G.R., Chaum, D. (eds.) CRYPTO 1984. LNCS, vol. 196, pp. 10–18. Springer, Heidelberg (1985)
Camenisch, J., Stadler, M.: Proof Systems for General Statements about Discrete Logarithms. Technical Report 260, Department of Computer Science, ETH Zürich (2001)
Chaum, D., Pedersen, T.P.: Wallet Databases with Observers. In: Brickell, E.F. (ed.) CRYPTO 1992. LNCS, vol. 740, pp. 89–105. Springer, Heidelberg (1993)
Bella, G., Librizzi, F., Riccobene, S.: Realistic threats to self-enforcing privacy. In: IAS ’08: Proceedings of the 4th International Conference on Information Assurance and Security, Washington, DC, USA, pp. 155–160. IEEE Computer Society, Los Alamitos (2008)
Pollard, J.M.: Monte Carlo methods for index computation (mod p). Mathematics of Computation 32(143), 918–924 (1978)
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Stegelmann, M. (2010). Towards Fair Indictment for Data Collection with Self-Enforcing Privacy. In: Rannenberg, K., Varadharajan, V., Weber, C. (eds) Security and Privacy – Silver Linings in the Cloud. SEC 2010. IFIP Advances in Information and Communication Technology, vol 330. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15257-3_24
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DOI: https://doi.org/10.1007/978-3-642-15257-3_24
Publisher Name: Springer, Berlin, Heidelberg
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