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keys by conjugation with a random invertible matrix over an RSA modulus.
We provide a two known-ciphertexts cryptanalysis recovering a linear dependence among
the two encrypted keys.
In this paper, we investigate new and novel SSE designs which meet all practical properties, including one-round multi-keyword query, comprehensive and practical privacy protection, sublinear search time, and efficient dynamic data operation support. Moreover, our solutions can well support parallel search and run for very large-scale cloud databases. Compared to the existing SSE solutions,
our solution is highly compact, efficient and flexible. Its performance and security are carefully characterized by rigorous analysis. Experimental evaluations conducted over large representative real-word data sets demonstrate that compared with the state-of-the-art our solution indeed achieves desirable properties for large-scale encrypted database systems.
and to prove properties of their certificates in zero-knowledge.
This toolkit allows an issuer, such as an auditor, to sign the topology representation of an infrastructure. The prover, such as an infrastructure provider, can then convince a verifier of topology properties, such as partitions, connectivity or isolation, without disclosing the structure of the topology itself. By that, we can achieve the certification of the structure of critical systems, such as infrastructure clouds or outsourced systems, while still maintaining confidentiality. We offer zero-knowledge proofs of knowledge for a general specification language of security goals for virtualized infrastructures, such that high-level security goalscan be proven over the topology certificate. Our method builds upon the Camenisch-Lysyanskaya signature scheme, is based on honest-verifier proofs and the strong RSA assumption.
a massive scale, the privacy of individual users appears to be a major concern.
The main challenge is the design of a solution that allows the data analyzer to
compute global statistics over the set of individual inputs that are protected by
some confidentiality mechanism. Joye et al.  recently suggested a solution
that allows a centralized party to compute the sum of encrypted inputs collected
through a smart metering network. The main shortcomings of this solution are
its reliance on a trusted dealer for key distribution and the need for frequent key
updates. In this paper we introduce a secure protocol for aggregation of timeseries
data that is based on the Joye et al.  scheme and in which the main
shortcomings of the latter, namely, the requirement for key updates and for the
trusted dealer are eliminated. As such, during the protocol execution none of the
parties apart from the users themselves are aware of the secret keys. Moreover
our scheme supports a dynamic group management, whereby as opposed to Joye
et al.  leave and join operations do not trigger a key update at the users.