Control Flow Checking at Virtual Edges

( Liping Liu ),( Linlin Ci ),( Wei Liu ),( Hui Yang ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.1

Dynamically checking the integrity of software at run-time is always a hot and difficult spot for trusted computing. Control-flow integrity is a basic and important safety property of software integrity. Many classic and emerging security attacks who introduce illegal control-flow to applications can cause unpredictable behaviors of computer-based systems. In this paper, we present a software-based approach to checking violation of control flow integrity at run-time. This paper proposes a high-performance and low-overhead software control flow checking solution, control flow checking at virtual edges (CFCVE). CFCVE assigns a unique signature to each basic block and then inserts a virtual vertex into each edge at compile time. This together with insertion of signature updating instructions and checking instructions into corresponding vertexes and virtual vertexes. Control flow faults can be detected by comparing the run-time signature with the saved one at compile time. Our experimental results show that CFCVE incurs only 10.61% performance overhead on average for several C benchmark programs and the average undetected error rate is only 9.29%. Compared with previous techniques, CFCVE has the characteristics of both high fault coverage and low memory and performance overhead.

Effects of Nitrate Addition on Rumen Fermentation, Bacterial Biodiversity and Abundance

Liping Zhao,Qingxiang Meng,Liping Ren,Wei Liu,Xinzhuang Zhang,Yunlong Huo,Zhenming Zhou 아세아·태평양축산학회 2015 Animal Bioscience Vol.28 No.10

This study examined changes of rumen fermentation, ruminal bacteria biodiversity and abundance caused by nitrate addition with Ion Torrent sequencing and real-time polymerase chain reaction. Three rumen-fistulated steers were fed diets supplemented with 0%, 1%, and 2% nitrate (dry matter %) in succession. Nitrate supplementation linearly increased total volatile fatty acids and acetate concentration obviously (p = 0.02; p = 0.02; p<0.01), butyrate and isovalerate concentration numerically (p = 0.07). The alpha (p>0.05) and beta biodiversityof ruminal bacteria were not affected by nitrate. Nitrate increased typical efficient cellulolytic bacteria species (Ruminococcus flavefaciens, Ruminococcus ablus, and Fibrobacter succinogenes) (p<0.01; p = 0.06; p = 0.02). Ruminobactr, Sphaerochaeta, CF231, and BF311 genus were increased by 1% nitrate. Campylobacter fetus, Selenomonas ruminantium, and Mannheimia succiniciproducens were core nitrate reducing bacteria in steers and their abundance increased linearly along with nitrate addition level (p<0.01; p = 0.02; p = 0.04). Potential nitrate reducers in the rumen, Campylobacter genus and Cyanobacteria phyla were significantly increased by nitrate (p<0.01; p = 0.01).To the best of our knowledge, this was the first detailed view of changes in ruminal microbiota by nitrate. This finding would provide useful information on nitrate utilization and nitrate reducer exploration in the rumen.

3D Model Compression For Collaborative Design

Liu, Jun,Wang, Qifu,Huang, Zhengdong,Chen, Liping,Liu, Yunhua Society for Computational Design and Engineering 2007 International Journal of CAD/CAM Vol.7 No.1

The compression of CAD models is a key technology for realizing Internet-based collaborative product development because big model sizes often prohibit us to achieve a rapid product information transmission. Although there exist some algorithms for compressing discrete CAD models, original precise CAD models are focused on in this paper. Here, the characteristics of hierarchical structures in CAD models and the distribution of their redundant data are exploited for developing a novel data encoding method. In the method, different encoding rules are applied to different types of data. Geometric data is a major concern for reducing model sizes. For geometric data, the control points of B-spline curves and surfaces are compressed with the second-order predictions in a local coordinate system. Based on analysis to the distortion induced by quantization, an efficient method for computation of the distortion is provided. The results indicate that the data size of CAD models can be decreased efficiently after compressed with the proposed method.

Identifying SDC-Causing Instructions Based on Random Forests Algorithm

( Liping Liu ),( Linlin Ci ),( Wei Liu ),( Hui Yang ) 한국인터넷정보학회 2019 KSII Transactions on Internet and Information Syst Vol.13 No.3

Silent Data Corruptions (SDCs) is a serious reliability issue in many domains of computer system. The identification and protection of the program instructions that cause SDCs is one of the research hotspots in computer reliability field at present. A lot of solutions have already been proposed to solve this problem. However, many of them are hard to be applied widely due to time-consuming and expensive costs. This paper proposes an intelligent approach named SDCPredictor to identify the instructions that cause SDCs. SDCPredictor identifies SDC-causing Instructions depending on analyzing the static and dynamic features of instructions rather than fault injections. The experimental results demonstrate that SDCPredictor is highly accurate in predicting the SDCs proneness. It can achieve higher fault coverage than previous similar techniques in a moderate time cost.

Genomics and LC-MS Reveal Diverse Active Secondary Metabolites in Bacillus amyloliquefaciens WS-8

Hongwei Liu,Yana Wang,Qingxia Yang,Wenya Zhao,Liting Cui,Buqing Wang,Liping Zhang,Huicai Cheng,Shuishan Song,Liping Zhang 한국미생물·생명공학회 2020 Journal of microbiology and biotechnology Vol.30 No.3

Bacillus amyloliquefaciens is an important plant disease-preventing and growth-promoting microorganism. B. amyloliquefaciens WS-8 can stimulate plant growth and has strong antifungal properties. In this study, we sequenced the complete genome of B. amyloliquefaciens WS-8 by Pacific Biosciences RSII (PacBio) Single Molecule Real-Time (SMRT) sequencing. The genome consists of one chromosome (3,929,787 bp) and no additional plasmids. The main bacteriostatic substances were determined by genome, transcriptome, and mass spectrometry data. We thereby laid a theoretical foundation for the utilization of the strain. By genomic analysis, we identified 19 putative biosynthetic gene clusters for secondary metabolites, most of which are potentially involved in the biosynthesis of numerous bioactive metabolites, including difficidin, fengycin, and surfactin. Furthermore, a potential class II lanthipeptide biosynthetic gene cluster and genes that are involved in auxin biosynthesis were found. Through the analysis of transcriptome data, we found that the key bacteriostatic genes, as predicted in the genome, exhibited different levels of mRNA expression. Through metabolite isolation, purification, and exposure experiments, we found that a variety of metabolites of WS-8 exert an inhibitory effect on the necrotrophic fungus Botrytis cinerea, which causes gray mold; by mass spectrometry, we found that the main substances are mainly iturins and fengycins. Therefore, this strain has the potential to be utilized as an antifungal agent in agriculture.

Effects of Nitrate Addition on Rumen Fermentation, Bacterial Biodiversity and Abundance

Zhao, Liping,Meng, Qingxiang,Ren, Liping,Liu, Wei,Zhang, Xinzhuang,Huo, Yunlong,Zhou, Zhenming Asian Australasian Association of Animal Productio 2015 Animal Bioscience Vol.28 No.10

This study examined changes of rumen fermentation, ruminal bacteria biodiversity and abundance caused by nitrate addition with Ion Torrent sequencing and real-time polymerase chain reaction. Three rumen-fistulated steers were fed diets supplemented with 0%, 1%, and 2% nitrate (dry matter %) in succession. Nitrate supplementation linearly increased total volatile fatty acids and acetate concentration obviously (p = 0.02; p = 0.02; p<0.01), butyrate and isovalerate concentration numerically (p = 0.07). The alpha (p>0.05) and beta biodiversityof ruminal bacteria were not affected by nitrate. Nitrate increased typical efficient cellulolytic bacteria species (Ruminococcus flavefaciens, Ruminococcus ablus, and Fibrobacter succinogenes) (p<0.01; p = 0.06; p = 0.02). Ruminobactr, Sphaerochaeta, CF231, and BF311 genus were increased by 1% nitrate. Campylobacter fetus, Selenomonas ruminantium, and Mannheimia succiniciproducens were core nitrate reducing bacteria in steers and their abundance increased linearly along with nitrate addition level (p<0.01; p = 0.02; p = 0.04). Potential nitrate reducers in the rumen, Campylobacter genus and Cyanobacteria phyla were significantly increased by nitrate (p<0.01; p = 0.01).To the best of our knowledge, this was the first detailed view of changes in ruminal microbiota by nitrate. This finding would provide useful information on nitrate utilization and nitrate reducer exploration in the rumen.

A Configurable Software-based Approach for Detecting CFEs Caused by Transient Faults

( Wei Liu ),( Linlin Ci ),( Liping Liu ) 한국인터넷정보학회 2021 KSII Transactions on Internet and Information Syst Vol.15 No.5

Transient faults occur in computation units of a processor, which can cause control flow errors (CFEs) and compromise system reliability. The software-based methods perform illegal control flow detection by inserting redundant instructions and monitoring signature. However, the existing methods not only have drawbacks in terms of performance overhead, but also lack of configurability. We propose a configurable approach CCFCA for detecting CFEs. The configurability of CCFCA is implemented by analyzing the criticality of each region and tuning the detecting granularity. For critical regions, program blocks are divided according to space-time overhead and reliability constraints, so that protection intensity can be configured flexibly. For other regions, signature detection algorithms are only used in the first basic block and last basic block. This helps to improve the fault-tolerant efficiency of the CCFCA. At the same time, CCFCA also has the function of solving confusion and instruction self-detection. Our experimental results show that CCFCA incurs only 10.61% performance overhead on average for several C benchmark program and the average undetected error rate is only 9.29%. CCFCA has high error coverage and low overhead compared with similar algorithms. This helps to meet different cost requirements and reliability requirements.

The Prediction of Code Clone Quality Based on Bayesian Network

Dongrui Liu,Dongsheng Liu,Liping Zhang,Min Hou,Chunhui Wang 보안공학연구지원센터 2016 International Journal of Software Engineering and Vol.10 No.4

This paper researched on the quality of code clone in the software, evaluated the code clone quality of the current versions. Then using Bayesian network to train the existing sample data to get the prediction model of code clone that is able to predict the quality. The prediction results are able to help developers decide which code clone should be reconstructed or efficiently reused. The experiment shows that the method can be used to predict the quality of code clone in software more accurately.

Reliable Localization for Wireless Sensor Networks in Complex Environments

Xiaolei Liu,Yongji Ren,Xuguang Xin,Liping Zhang,Jixiang Chen 보안공학연구지원센터 2014 International Journal of Control and Automation Vol.7 No.10

Although localization has been widely studied for Wireless Sensor Networks (WSNs), the complex environments and the large network scale pose severe challenges and make it necessary to develop new reliable localization algorithms. In this paper, we propose a novel Multi-Hop Localization Algorithm for large-scale WSNs in complex environments. This work is based on the consideration that the localization process would encounter several kinds of adverse factors with different nature at the same time (e.g. anisotropic network characteristics, ranging uncertainty, link quality of multihop paths, etc.), which lead to obvious degradation of localization performance. Unlike most of the existing schemes, we transform the localization problem in complex environments into a hybrid constraint satisfaction problem (CSP) which is composed of three different kinds of constraints, i.e. spatial constraint, network situation constraint, and confidence constraint. Set-membership approach and interval analysis method have been utilized to deal with the CSP and determine the positions of sensor nodes. Simulation results show that our scheme is an effective and efficient approach to localization in large-scale WSNs.

Research on Trustiness of Software Behavior Based on Cross-References

Wei LIU,Linlin CI,Liping LIU 보안공학연구지원센터 2015 International Journal of Security and Its Applicat Vol.9 No.5