An Accountability Scheme for Oblivious RAMs

In outsourced data services, revealing users’ data access pattern may lead to the exposure of a wide range of sensitive information even if data is encrypted. Oblivious RAM has been a well-studied provable solution to access pattern preservation. However, it is not resilient to attacks towards data integrity from the users or the server. In this paper, we study the problem of protecting access pattern privacy and data integrity together in outsourced data services, and propose a scheme that introduces accountability support into a hash-based ORAM design. The proposed scheme can detect misconduct committed by malicious users or server, and identify the attacker, while not interfering with the access pattern preservation mechanisms inherent from the underlying ORAM. This is accomplished at the cost of slightly increased computational, storage, and communication overheads compared with the original ORAM

Privacy-Preserving Accountable Cloud Storage

In cloud storage services, a wide range of sensitive information may be leaked to the host server via the exposure of access pattern albeit data is encrypted. Many security-provable schemes have been proposed to preserve the access pattern privacy; however, they may be vulnerable to attacks towards data integrity or availability from malicious users. This is due to the fact that, preserving access pattern privacy requires data to be frequently re-encrypted and re-positioned at the storage server, which can easily conceal the traces that are needed for account- ability support to detect misbehaviors and identify attackers. To address this issue, this paper proposes a scheme that integrates accountability support into hash-based ORAMs. Security analysis shows that the proposed scheme can detect misconduct committed by malicious users and identify the attackers, while preserving the access pattern privacy. Overhead analysis shows that the proposed accountability support incurs only slightly increased storage, communication, and computational overheads

Panoramic mosaics from Chang’E-3 PCAM images at Point A

This paper presents a unique approach for panoramic mosaics based on Moon surface images from the Chang’E-3 (CE-3) mission, with consideration of the exposure time and external illumination changes in CE-3 Panoramic Camera (PCAM) imaging. The engineering implementation involves algorithms of image feature points extraction by using Speed-Up Robust Features (SURF), and a newly defined measure is used to obtain the corresponding points in feature matching. Then, the transformation matrix is calculated and optimized between adjacent images by the Levenberg–Marquardt algorithm. Finally, an image is reconstructed by using a fade-in-fade-out method based on linear interpolation to achieve a seamless mosaic. The developed algorithm has been tested with CE-3 PCAM images at Point A (one of the rover sites where the rover is separated from the lander). This approach has produced accurate mosaics from CE-3 PCAM images, as is indicated by the value of the Peak Signal to Noise Ratio (PSNR), which is greater than 31 dB between the overlapped region of the images before and after fusion

Standards and Protocols for Characterization of Algae-Based Biofuels

Recently, algae have been considered as the third-generation biofuel feedstock, which can be converted to the precursor chemicals of drop-in fuels via either the algal lipid upgrading (ALU) pathway or the hydrothermal liquefaction (HTL) pathway. These precursors could be further processed and upgraded to fuels. This article reviews the standards and protocols that are suitable for characterization of drop-in algal biofuels. Applicable ASTM standards and European standards (EN) were summarized. The protocols that have been used by researches and the National Institute of Standards and Technology were also introduced.Citation: Yang, C., Zhang, B., Cui, C., Wu, J., Ding, Y., and Wu, Y. (2016). Standards and Protocols for Characterization of Algae-Based Biofuels. Trends in Renewable Energy, 2(2), 56-60. DOI: 10.17737/tre.2016.2.2.002

Few-Mode Fibers With Uniform Differential Mode Group Delay for Microwave Photonic Signal Processing

We present a novel design of few-mode fiber (FMF) with a uniform differential mode group delay (U-DMGD) among propagating modes and apply the FMF to a single-fiber delay line module for implementing microwave photonic finite impulse response (FIR) filters. By optimizing key parameters such as the core grading exponent and the dimension of the trench of FMF, a U-DMGD between adjacent modes among four modes (LP 01 , LP 11 , LP 02 and LP 31 ) over the entire C band is achieved. Wavelength dependence is entirely removed. An FIR microwave photonic filter (MPF) implemented using the designed 1-km FMF is investigated through numerical simulations. The free spectral range (FSR) of the MPF is 5.7 GHz, the 3-dB bandwidth is 1.26 GHz, and the main lobe-to-side lobe ratio (MSR) is 10.42 dB. Discussions on fabrication aspects have also been presented. The proposed single-fiber delay line structure based on FMF can significantly reduce the system complexity of microwave photonic signal processing

A universal interatomic potential for perovskite oxides

With their celebrated structural and chemical flexibility, perovskite oxides have served as a highly adaptable material platform for exploring emergent phenomena arising from the interplay between different degrees of freedom. Molecular dynamics (MD) simulations leveraging classical force fields, commonly depicted as parameterized analytical functions, have made significant contributions in elucidating the atomistic dynamics and structural properties of crystalline solids including perovskite oxides. However, the force fields currently available for solids are rather specific and offer limited transferability, making it time-consuming to use MD to study new materials systems since a new force field must be parameterized and tested first. The lack of a generalized force field applicable to a broad spectrum of solid materials hinders the facile deployment of MD in computer-aided materials discovery (CAMD). Here, by utilizing a deep-neural network with a self-attention scheme, we have developed a unified force field that enables MD simulations of perovskite oxides involving 14 metal elements and conceivably their solid solutions with arbitrary compositions. Notably, isobaric-isothermal ensemble MD simulations with this model potential accurately predict the experimental phase transition sequences for several markedly different ferroelectric oxides, including a 6-element ternary solid solution, Pb(In$_{1/2}$Nb$_{1/2}$)O$_3$--Pb(Mg$_{1/3}$Nb$_{2/3}$)O$_3$--PbTiO$_3$. We believe the universal interatomic potential along with the training database, proposed regression tests, and the auto-testing workflow, all released publicly, will pave the way for a systematic improvement and extension of a unified force field for solids, potentially heralding a new era in CAMD.Comment: 18 pages, 4 figure

Intelligent Information Dissemination Scheme for Urban Vehicular Ad Hoc Networks

In vehicular ad hoc networks (VANETs), a hotspot, such as a parking lot, is an information source and will receive inquiries from many vehicles for seeking any possible free parking space. According to the routing protocols in literature, each of the vehicles needs to flood its route discovery (RD) packets to discover a route to the hotspot before sending inquiring packets to the parking lot. As a result, the VANET nearby an urban area or city center may incur the problem of broadcast storm due to so many flooding RD packets during rush hours. To avoid the broadcast storm problem, this paper presents a hotspot-enabled routing-tree based data forwarding method, called the intelligent information dissemination scheme (IID). Our method can let the hotspot automatically decide when to build the routing-tree for proactive information transmissions under the condition that the number of vehicle routing discoveries during a given period exceeds a certain threshold which is calculated through our developed analytical packet delivery model. The routing information will be dynamically maintained by vehicles located at each intersection near the hotspot if the maintaining cost is less than that of allowing vehicles to discover routes themselves. Simulation results show that this method can minimize routing delays for vehicles with lower packets delivery overheads