Database Padding for Dynamic Symmetric Searchable Encryption

Dynamic symmetric searchable encryption (DSSE) that enables the search and update of encrypted databases outsourced to cloud servers has recently received widespread attention for leakage-abuse attacks against DSSE. In this paper, we propose a dynamic database padding method to mitigate the threat of data leakage during the update operation of outsourcing data. First, we introduce an outlier detection technology where bogus files are generated for padding according to the outlier factors, hiding the document information currently matching search keywords. Furthermore, we design a new index structure suitable for the padded database using the bitmap index to simplify the update operation of the encrypted index. Finally, we present an application scenario of the padding method and realize a forward and backward privacy DSSE scheme (named PDB-DSSE). The security analysis and simulation results show that our dynamic padding algorithm is suitable for DSSE scheme and PDB-DSSE scheme maintains the security and efficiency of the retrieval and update of the DSSE scheme.

Measurement and analysis of refractive index structure constant Cn2 profile over Delhi on diurnal and seasonal basis

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Energy Spectra of Atmospheric Turbulence for Calculating Cn2 Parameter. I. Maidanak and Suffa Observatories in Uzbekistan

Knowledge of the turbulence spectra is of interest for describing atmospheric conditions as applied to astronomical observations. This article discusses the deformations of the turbulence spectra with heights in a wide range of scales at the sites of the Maidanak and Suffa observatories. It is shown that the energy of baroclinic instability is high at the sites of these observatories and should be taken into account in the calculations of the refractive index structure constant Cn2.

Turbulence Detection in the Atmospheric Boundary Layer using Coherent Doppler Wind Lidar and Microwave Radiometer

The refractive index structure constant (Cn2) is a key parameter in describing the influence of turbulence on laser transmission in the atmosphere. A new method for continuous Cn2 profiling with both high temporal and spatial resolution is proposed and demonstrated. Under the assumption of the Kolmogorov “2/3 law”, the Cn2 profile can be calculated by using the wind field and turbulent kinetic energy dissipation rate (TKEDR) measured by coherent Doppler wind lidar (CDWL) and other meteorological parameters derived from microwave radiometer (MWR). In the horizontal experiment, a comparison between the results from our new method and measurements made by a large aperture scintillometer (LAS) is conducted. Except for the period of stratification stabilizing, the correlation coefficient between them in the six-day observation is 0.8389, the mean error and standard deviation is 1.09 × 10−15 m−2/3 and 2.14 × 10−15 m−2/3, respectively. In the vertical direction, the continuous observation results of Cn2 and other turbulence parameter profiles in the atmospheric boundary layer (ABL) are retrieved. More details of the atmospheric turbulence can be found in the ABL owe to the high temporal and spatial resolution of MWR and CDWL (spatial resolution of 26 m, temporal resolution of 147 s).

Atmospheric turbulence characterization using a neuromorphic camera-based imaging sensor

New capabilities for atmospheric turbulence spatio-temporal dynamics characterization and refractive index structure parameter (Cn2) sensing via white light imaging of remotely located non-cooperative targets using an optical system with a neuromorphic (event) based sensor are demonstrated through a set of experimental trials conducted over a 7 km imaging path and proposed event data processing technique.

Atmospheric Optical Turbulence Characteristics over the Ocean Relevant to Astronomy and Atmospheric Physics

Due to the space and time constraints of turbulence measurement equipment and the experiment scene, it is difficult to obtain the atmosphere refractive index structure constant over the ocean. In this paper, the characteristics of atmospheric optical turbulence in offshore and open ocean conditions are summarized by analyzing the meteorological data obtained from two ocean atmospheric optical parameter field experiments. Because of the influence of land undersurface, the turbulence strength in offshore conditions is roughly the same as that on land and presents different characteristics in open ocean. Compared with the offshore area, the turbulence strength over the open ocean near-surface decreases during the day and increases at night, and the diurnal variation characteristics weaken. The turbulence strength profiles over the offshore area show different characteristics at different times, where the turbulence strength in the morning is higher than that in the evening. By retrieving the meteorological factors affecting the turbulence, it is found that the temperature gradient and wind shear are in good agreement with turbulence strength in both offshore and open ocean areas. Furthermore, the integrated parameters for astronomy and optical telecommunication are derived from profiles over the offshore and open ocean areas. It is of great significance to research the turbulent characteristics of ocean atmosphere for optical transmission and astronomical observations.

Efficient Processing of Top-k Frequent Spatial Keyword Queries

The rapid popularization of high-speed mobile communication technology and the continuous development of mobile network devices have given spatial textual big data (STBD) new dimensions due to their ability to record geographical objects from multiple sources and with complex attributes. Data mining from spatial textual datasets has become a meaningful study. As a popular topic for STBD, the top-k spatial keyword query has been developed in various forms to deal with different retrievals requirements. However, previous research focused mainly on indexing locational attributes and retrievals of few target attributes, and these correlations between large numbers of the textual attributes have not been fully studied and demonstrated. To further explore interrelated-knowledge in the textual attributes, this paper defines the top-k frequent spatial keyword query (tfSKQ) and proposes a novel hybrid index structure, named RCL-tree, based on the concept lattice theory. We also develop the tfSKQ algorithms to retrieve the most frequent and nearest spatial objects in STBD. One existing method and two baseline algorithms are implemented, and a series of experiments are carried out using real datasets to evaluate its performance. Results demonstrated the effectiveness and efficiency of the proposed RCL-tree in tfSKQ with the complex spatial multi keyword query conditions.

Tree-Based Public Key Encryption with Conjunctive Keyword Search

Searchable public key encryption supporting conjunctive keyword search is an important technique in today’s cloud environment. Nowadays, previous schemes usually take advantage of forward index structure, which leads to a linear search complexity. In order to obtain better search efficiency, in this paper, we utilize a tree index structure instead of forward index to realize such schemes. To achieve the goal, we first give a set of keyword conversion methods that can convert the index and query keywords into a group of vectors and then present a novel algorithm for building index tree based on these vectors. Finally, by combining an efficient predicate encryption scheme to encrypt the index tree, a tree-based public key encryption with conjunctive keyword search scheme is proposed. The proposed scheme is proven to be secure against chosen plaintext attacks and achieves a sublinear search complexity. Moreover, both theoretical analysis and experimental result show that the proposed scheme is efficient and feasible for practical applications.