New PDF release: Data Privacy Management and Autonomous Spontaneous Security:

By Joaquin Garcia-Alfaro, Georgios Lioudakis, Nora Cuppens-Boulahia, Simon Foley, William M. Fitzgerald (eds.)

ISBN-10: 364254567X

ISBN-13: 9783642545672

ISBN-10: 3642545688

ISBN-13: 9783642545689

This publication constitutes the revised chosen papers of the eighth overseas Workshop on information privateness administration, DPM 2013, and the sixth overseas Workshop on self reliant and Spontaneous safeguard, SETOP 2013, held in Egham, united kingdom, in September 2013 and co-located with the 18th ecu Symposium on examine in laptop safeguard (ESORICS 2013). the amount comprises thirteen complete papers chosen out of forty six submissions and 1 keynote lecturer from the DPM workshop and six complete papers including five brief papers chosen between quite a few submissions to the SETOP workshop. The papers hide subject matters relating to the administration of privacy-sensitive details and automatic configuration of safeguard, focusing particularly on system-level privateness rules, management of delicate identifiers, information integration and privateness, engineering authentication and authorization, cellular safety and vulnerabilities.

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Additional info for Data Privacy Management and Autonomous Spontaneous Security: 8th International Workshop, DPM 2013, and 6th International Workshop, SETOP 2013, Egham, UK, September 12-13, 2013, Revised Selected Papers

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Yasuda and et al. It mainly requires only one time homomorphic multiplication when we precompute C1 , C2 and C1 ∗ C2 . 5 Comparison with Related Work In Table 1, we give a comparison of our protocol with related work described in Sect. 1 on the performance and the encrypted data size for secure Hamming distance (all encryption schemes are estimated to have more than 80-bit security). Table 1 shows that our protocol has the best performance in the state-of-theart work. Due to our packing method, our protocol is much faster and more compact than SCiFI [25] and the protocol of [2] using additively homomorphic encryption.

308–318. Springer, Heidelberg (1998) 29. 0: Technical report, French Network and Information Security Agency (Agence Nationale de la Scurit des Systmes dInformation (ANSSI)). pdf (2009) 30. Atmel: At90sc256144rcft datasheet. pdf (2007) 31. NIST: Gemxpresso r4 e36/e72 pk—multiapp id 36k/72k—top im gx4. http://csrc. jp Abstract. Somewhat homomorphic encryption is public key encryption supporting a limited number of both additions and multiplications on encrypted data, which is useful for performing fundamental computations with protecting the data confidentiality.

T : an integer with t < q to determine a plaintext space Rt := Ft [x]/(f (x)). σ : the parameter to define a discrete Gaussian error distribution χ := DZn ,σ with the standard deviation σ. In practice, we take σ = 4 ∼ 8. Key Generation. We choose an element R ⇐ s ← χ, and then sample a random element a1 ∈ Rq and an error R ⇐ e ← χ. Set pk = (a0 , a1 ) with a0 := −(a1 · s + t · e) as the public key and sk = s as the secret key. Encryption. For a plaintext m ∈ Rt and pk = (a0 , a1 ), the encryption samples R ⇐ u, f, g ← χ and compute the ‘fresh’ ciphertext given by Enc(m, pk) = (c0 , c1 ) = (a0 u + tg + m, a1 u + tf ) ∈ (Rq )2 , where m ∈ Rt is considered as an element of Rq in the natural way.

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Data Privacy Management and Autonomous Spontaneous Security: 8th International Workshop, DPM 2013, and 6th International Workshop, SETOP 2013, Egham, UK, September 12-13, 2013, Revised Selected Papers by Joaquin Garcia-Alfaro, Georgios Lioudakis, Nora Cuppens-Boulahia, Simon Foley, William M. Fitzgerald (eds.)


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