PREFENDER: A Prefetching Defender against Cache Side Channel Attacks as A Pretender

Cache side channel attacks are increasingly alarming in modern processors due to the recent emergence of Spectre and Meltdown attacks. A typical attack performs intentional cache access and manipulates cache states to leak secrets by observing the victim's cache access patterns. Different countermeasures have been proposed to defend against both general and transient execution based attacks. Despite their effectiveness, they mostly trade some level of performance for security, or have restricted security scope. In this paper, we seek an approach to enforcing security while maintaining performance. We leverage the insight that attackers need to access cache in order to manipulate and observe cache state changes for information leakage. Specifically, we propose Prefender, a secure prefetcher that learns and predicts attack-related accesses for prefetching the cachelines to simultaneously help security and performance. Our results show that Prefender is effective against several cache side channel attacks while maintaining or even improving performance for SPEC CPU 2006 and 2017 benchmarks.Comment: Submitting to a journa

Credit Ratings and Capital Structure Empirical analysis from listed companies in China

Abstract This paper discusses the influence of credit ratings near adjustment on corporate capital structure and whether the CR-CS model is more suitable for companies with external financing needs. The data sample contains the credit rating data and financial data of non-financial firms listed on the “ShangHai A share” and “ShenZhen A share” from 2012 to 2017. There are three hypotheses in this paper. The writer firstly focuses on the impact of the credit ratings near adjustment on the companies’ capital structure under broad ratings and micro ratings. Finally, she does tests about whether the external financing needs will influence the extent to which the enterprises are concerned with the credit rating In general, the writer finds that although the external financing needs will not influence the extent to which the enterprises are concerned with the credit rating, the credit rating still has a significant impact on the capital structure decisions of Chinese enterprises. Key words: credit ratings, capital structure, ratings near adjustment, external financing need

Hemicellulose-g-PAAc/TiO2 Nanocomposite Hydrogel for Dye Removal

Dyes pollution on urban environment is of great concern because of the human health hazards associated with this kind of contaminants, and the use of low-cost photocatalytic composite material is an efficient treatment method to minimize the environmental impact. A novel hemicellulose-g-PAAc/TiO2 composite hydrogel was prepared as a promising alternative material for dye removal. Wheat straw hemicellulose and TiO2 nanoparticles were first modified and then incorporated into hydrogel via covalent bonds. Effects of gel dosage, pH, initial concentration and contact time on the adsorption amount of methylene blue were systematically studied using the prepared hydrogel. The equilibrium adsorption data was fitted well to the Freundlich isotherm model, and Langmuir isotherm analysis indicated that the adsorption capacity of the hemicellulose-g-PAAc/TiO2 composite hydrogel was 389.1 mg/g, and adsorption kinetic study showed that the adsorption process can be described by the pseudo second-order kinetic model. The prepared composite hydrogel exhibited high photodegradation ability for methylene blue under alkaline conditions, and all results indicated that the hemicellulose-g-PAAc/TiO2 composite hydrogel had excellent photocatalytic degradability for dyes, which can be used in practical process

Combined strategies for improving production of a thermo-alkali stable laccase in Pichia pastoris

Background: Laccases are copper-containing enzymes which have been used as green biocatalysts for many industrial processes. Although bacterial laccases have high stabilities which facilitate their application under harsh conditions, their activities and production yields are usually very low. In this work, we attempt to use a combinatorial strategy, including site-directed mutagenesis, codon and cultivation optimization, for improving the productivity of a thermo-alkali stable bacterial laccase in Pichia pastoris. Results: A D500G mutant of Bacillus licheniformis LS04 laccase, which was constructed by site-directed mutagenesis, demonstrated 2.1-fold higher activity when expressed in P. pastoris. The D500G variant retained similar catalytic characteristics to the wild-type laccase, and could efficiently decolorize synthetic dyes at alkaline conditions. Various cultivation factors such as medium components, pH and temperature were investigated for their effects on laccase expression. After cultivation optimization, a laccase activity of 347 \ub1 7 U/L was finally achieved for D500G after 3 d of induction, which was about 9.3 times higher than that of wild-type enzyme. The protein yield under the optimized conditions was about 59 mg/L for D500G. Conclusions: The productivity of the thermo-alkali stable laccase from B. licheniformis expressed in P. pastoris was significantly improved through the combination of site-directed mutagenesis and optimization of the cultivation process. The mutant enzyme retains good stability under high temperature and alkaline conditions, and is a good candidate for industrial application in dye decolorization

VibHead: An Authentication Scheme for Smart Headsets through Vibration

Recent years have witnessed the fast penetration of Virtual Reality (VR) and Augmented Reality (AR) systems into our daily life, the security and privacy issues of the VR/AR applications have been attracting considerable attention. Most VR/AR systems adopt head-mounted devices (i.e., smart headsets) to interact with users and the devices usually store the users' private data. Hence, authentication schemes are desired for the head-mounted devices. Traditional knowledge-based authentication schemes for general personal devices have been proved vulnerable to shoulder-surfing attacks, especially considering the headsets may block the sight of the users. Although the robustness of the knowledge-based authentication can be improved by designing complicated secret codes in virtual space, this approach induces a compromise of usability. Another choice is to leverage the users' biometrics; however, it either relies on highly advanced equipments which may not always be available in commercial headsets or introduce heavy cognitive load to users. In this paper, we propose a vibration-based authentication scheme, VibHead, for smart headsets. Since the propagation of vibration signals through human heads presents unique patterns for different individuals, VibHead employs a CNN-based model to classify registered legitimate users based the features extracted from the vibration signals. We also design a two-step authentication scheme where the above user classifiers are utilized to distinguish the legitimate user from illegitimate ones. We implement VibHead on a Microsoft HoloLens equipped with a linear motor and an IMU sensor which are commonly used in off-the-shelf personal smart devices. According to the results of our extensive experiments, with short vibration signals ($\leq 1s$), VibHead has an outstanding authentication accuracy; both FAR and FRR are around 5%

Students' Intention of Visiting Urban Green Spaces after the COVID-19 Lockdown in China.

This study addresses students' perceptions of using urban green spaces (UGSs) after the easing of COVID-19 lockdown in China. We questioned whether they are still mindful of the risks from the outdoor gathering, or conversely, starting to learn the restoration benefits from the green spaces. Online self-reported surveys were distributed to the Chinese students aging from 14 to 30 who study in Hunan and Jiangsu Provinces, China. We finally obtained 608 complete and valid questionnaire forms from all participants. Their intentions of visiting UGSs were investigated based on the extended theory of planned behavior model. Structural equation modeling was employed to test the hypothesized psychological model. The results have shown good estimation performance on risk perception and perceived knowledge to explain the variances in their attitudes, social norms, and perceived behavior control. Among these three endogenous variables, the perceived behavior control owns the greatest and positive influence on the behavioral intention, inferring that controllability is crucial for students to make decisions of visiting green spaces in a post-pandemic context

K-Space-Aware Cross-Modality Score for Synthesized Neuroimage Quality Assessment

The problem of how to assess cross-modality medical image synthesis has been largely unexplored. The most used measures like PSNR and SSIM focus on analyzing the structural features but neglect the crucial lesion location and fundamental k-space speciality of medical images. To overcome this problem, we propose a new metric K-CROSS to spur progress on this challenging problem. Specifically, K-CROSS uses a pre-trained multi-modality segmentation network to predict the lesion location, together with a tumor encoder for representing features, such as texture details and brightness intensities. To further reflect the frequency-specific information from the magnetic resonance imaging principles, both k-space features and vision features are obtained and employed in our comprehensive encoders with a frequency reconstruction penalty. The structure-shared encoders are designed and constrained with a similarity loss to capture the intrinsic common structural information for both modalities. As a consequence, the features learned from lesion regions, k-space, and anatomical structures are all captured, which serve as our quality evaluators. We evaluate the performance by constructing a large-scale cross-modality neuroimaging perceptual similarity (NIRPS) dataset with 6,000 radiologist judgments. Extensive experiments demonstrate that the proposed method outperforms other metrics, especially in comparison with the radiologists on NIRPS