13,359 research outputs found

    Forward Private Searchable Symmetric Encryption with Optimized I/O Efficiency

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    Recently, several practical attacks raised serious concerns over the security of searchable encryption. The attacks have brought emphasis on forward privacy, which is the key concept behind solutions to the adaptive leakage-exploiting attacks, and will very likely to become mandatory in the design of new searchable encryption schemes. For a long time, forward privacy implies inefficiency and thus most existing searchable encryption schemes do not support it. Very recently, Bost (CCS 2016) showed that forward privacy can be obtained without inducing a large communication overhead. However, Bost's scheme is constructed with a relatively inefficient public key cryptographic primitive, and has a poor I/O performance. Both of the deficiencies significantly hinder the practical efficiency of the scheme, and prevent it from scaling to large data settings. To address the problems, we first present FAST, which achieves forward privacy and the same communication efficiency as Bost's scheme, but uses only symmetric cryptographic primitives. We then present FASTIO, which retains all good properties of FAST, and further improves I/O efficiency. We implemented the two schemes and compared their performance with Bost's scheme. The experiment results show that both our schemes are highly efficient, and FASTIO achieves a much better scalability due to its optimized I/O

    Limitations of Passive Protection of Quantum Information

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    The ability to protect quantum information from the effect of noise is one of the major goals of quantum information processing. In this article, we study limitations on the asymptotic stability of quantum information stored in passive N-qubit systems. We consider the effect of small imperfections in the implementation of the protecting Hamiltonian in the form of perturbations or weak coupling to a ground state environment. We prove that, regardless of the protecting Hamiltonian, there exists a perturbed evolution that necessitates a final error correcting step when the state of the memory is read. Such an error correction step is shown to require a finite error threshold, the lack thereof being exemplified by the 3D compass model. We go on to present explicit weak Hamiltonian perturbations which destroy the logical information stored in the 2D toric code in a time O(log(N)).Comment: 17 pages and appendice

    Large Scale Hierarchical K-Means Based Image Retrieval With MapReduce

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    Image retrieval remains one of the most heavily researched areas in Computer Vision. Image retrieval methods have been used in autonomous vehicle localization research, object recognition applications, and commercially in projects such as Google Glass. Current methods for image retrieval become problematic when implemented on image datasets that can easily reach billions of images. In order to process these growing datasets, we distribute the necessary computation for image retrieval among a cluster of machines using Apache Hadoop. While there are many techniques for image retrieval, we focus on systems that use Hierarchical K-Means Trees. Successful image retrieval systems based on Hierarchical K-Means Trees have been built using the tree as a Visual Vocabulary to build an Inverted File Index and implementing a Bag of Words retrieval approach, or by building the tree as a Full Representation of every image in the database and implementing a K-Nearest Neighbor voting scheme for retrieval. Both approaches involve different levels of approximation, and each has strengths and weaknesses that must be weighed in accordance with the needs of the application. Both approaches are implemented with MapReduce, for the first time, and compared in terms of image retrieval precision, index creation run-time, and image retrieval throughput. Experiments that include up to 2 million images running on 20 virtual machines are shown

    Topological quantum memory

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    We analyze surface codes, the topological quantum error-correcting codes introduced by Kitaev. In these codes, qubits are arranged in a two-dimensional array on a surface of nontrivial topology, and encoded quantum operations are associated with nontrivial homology cycles of the surface. We formulate protocols for error recovery, and study the efficacy of these protocols. An order-disorder phase transition occurs in this system at a nonzero critical value of the error rate; if the error rate is below the critical value (the accuracy threshold), encoded information can be protected arbitrarily well in the limit of a large code block. This phase transition can be accurately modeled by a three-dimensional Z_2 lattice gauge theory with quenched disorder. We estimate the accuracy threshold, assuming that all quantum gates are local, that qubits can be measured rapidly, and that polynomial-size classical computations can be executed instantaneously. We also devise a robust recovery procedure that does not require measurement or fast classical processing; however for this procedure the quantum gates are local only if the qubits are arranged in four or more spatial dimensions. We discuss procedures for encoding, measurement, and performing fault-tolerant universal quantum computation with surface codes, and argue that these codes provide a promising framework for quantum computing architectures.Comment: 39 pages, 21 figures, REVTe
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