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Cross-architecture Binary Function Similarity Detection based on Composite Feature Model
( Xiaonan Li ),( Guimin Zhang ),( Qingbao Li ),( Ping Zhang ),( Zhifeng Chen ),( Jinjin Liu ),( Shudan Yue ) 한국인터넷정보학회 2023 KSII Transactions on Internet and Information Syst Vol.17 No.8
Recent studies have shown that the neural network-based binary code similarity detection technology performs well in vulnerability mining, plagiarism detection, and malicious code analysis. However, existing cross-architecture methods still suffer from insufficient feature characterization and low discrimination accuracy. To address these issues, this paper proposes a cross-architecture binary function similarity detection method based on composite feature model (SDCFM). Firstly, the binary function is converted into vector representation according to the proposed composite feature model, which is composed of instruction statistical features, control flow graph structural features, and application program interface calling behavioral features. Then, the composite features are embedded by the proposed hierarchical embedding network based on a graph neural network. In which, the block-level features and the function-level features are processed separately and finally fused into the embedding. In addition, to make the trained model more accurate and stable, our method utilizes the embeddings of predecessor nodes to modify the node embedding in the iterative updating process of the graph neural network. To assess the effectiveness of composite feature model, we contrast SDCFM with the state of art method on benchmark datasets. The experimental results show that SDCFM has good performance both on the area under the curve in the binary function similarity detection task and the vulnerable candidate function ranking in vulnerability search task.
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One-pot Process of 2'-Deoxyguanylic Acid Catalyzed by a Multi-enzyme System
Yanyu Li,Qingbao Ding,Ling Ou,Yahui Qian,Jiao Zhang 한국생물공학회 2015 Biotechnology and Bioprocess Engineering Vol.20 No.1
2'-Deoxyguanylic acid (deoxyguanosine-5'-monophosphate, dGMP) is a substance required by livingcells that is used extensively in reagents, fine chemicalsand other industrial fields. Traditionally, dGMP is separatedfrom DNA degradation products, which is low-yieldingand time-consuming. Herein, we investigated a novel, onepotmulti-enzymatic cascade reaction to produce dGMP. This reaction involved purine nucleoside phosphorylase(PNPase) and acetate kinase (ACKase) from Escherichiacoli, N-deoxyribosytransferase II (NDT-II) from Lactobacillusdelbrueckii and deoxyguanosine kinase (dGKase) fromBacillus subtilis. During the reaction, the initial guanosinesubstrate was cleaved into guanine and ribose-1-phosphateby PNPase. Then, deoxyguanosine (dGR) was subsequentlyproduced from a reaction between guanine and thymidinecatalysed by NDT-II. Finally, the intermediate dGR wasphosphorylated to dGMP by dGKase and a cytidinetriphosphate (CTP) regeneration system that utilised acetylphosphate via ACKase. A very small amount of CTP wasadded because CTP regeneration was efficient to transfer aphosphate group from acetyl phosphate to dGR. After 12 hof incubation, a maximal dGMP yield of up to 76% wasobtained based on the addition of 5 mM guanosine and 5mM thymidine.
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Defending Non-control-data Attacks using Influence Domain Monitoring
( Guimin Zhang ),( Qingbao Li ),( Zhifeng Chen ),( Ping Zhang ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.8
As an increasing number of defense methods against control-data attacks are deployed in practice, control-data attacks have become challenging, and non-control-data attacks are on the rise. However, defense methods against non-control-data attacks are still deficient even though these attacks can produce damage as significant as that of control-data attacks. We present a method to defend against non-control-data attacks using influence domain monitoring (IDM). A definition of the data influence domain is first proposed to describe the characteristics of a variable during its life cycle. IDM extracts security-critical non-control data from the target program and then instruments the target for monitoring these variables’ influence domains to ensure that corrupted variables will not be used as the attackers intend. Therefore, attackers may be able to modify the value of one security-critical variable by exploiting certain memory corruption vulnerabilities, but they will be prevented from using the variable for nefarious purposes. We evaluate a prototype implementation of IDM and use the experimental results to show that this method can defend against most known non-control-data attacks while imposing a moderate amount of performance overhead.
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Review on the research of contact parameters calibration of particle system
Xuewen Wang,Haozhou Ma,Bo Li,Tiejun Li,Rui Xia,Qingbao Bao 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.3
With the widespread application of the discrete element method, research on accurate simulation of particle systems has attracted significant attention. However, there is no accurate process for the parameter calibration of particle systems. Most calibrations use a direct measurement method or test-simulation combined calibration method. Both methods have their advantages and disadvantages. This study reviews the calibration of contact parameters of particle systems, introduces the main calibration methods of different contact parameters, and summarizes the advantages and disadvantages of two main measurement methods. For the parameter measurement of particle systems, the accurate representation of particle shape and the reasonable optimization of simulation time are still not perfect. Furthermore, the correction of parameters after calibration applied to subsequent simulation needs further discussion.
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