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2022 International Conference on Neural Networks, Information, and Communication engineering, NNICE 2022

作者： Qiao, Meng Gui, Hairen Tang, Ke State Key Laboratory of Mathematical Engineering and Advanced Computing Henan450001 China

ISBN: (纸本)9781510655171

We introduce the AT-GCN (Adaptive Threshold filtering Graph Convolutional Neural network model). AT-GCN is a recommendation model based on graph structure. Compared with the commonly used graph structure recommendation model, AT-GCN can effectively solve the problem of edge representation and information transfer, and improve the recommendation effect. In the experimental part, several groups of experiments were carried out on AT-GCN, and the above conclusions were finally verified by the experimental results. © 2022 SPIE.

关键词： Recommender systems

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Binary vulnerability mining technology based on neural network feature fusion 5

Binary vulnerability mining technology based on neural netwo...

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5th International Conference on advanced Electronic Materials, Computers and Software engineering, AEMCSE 2022

作者： Han, Wenjie Pang, Jianmin Zhou, Xin Zhu, Di State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450002 China

ISBN: (数字)9781665484749

ISBN: (纸本)9781665484749

The high complexity of software and the diversity of security vulnerabilities have brought severe challenges to the research of software security vulnerabilities Traditional vulnerability mining methods are inefficient and have problems such as high false positives and high false negatives, which can not meet the growing needs of software security. To solve the above problems, this paper proposes a binary vulnerability mining technology based on neural network feature fusion. Firstly, this method constructs binary vulnerability data sets containing multiple vulnerability types, then decompile them to the pcode intermediate language level, and then extracts relevant feature vectors from binary vulnerability data sets according to Bert fine tuning model and bilstm model respectively. In order to fully obtain the semantic information of vulnerabilities, this method standardized the two, fused them, and carried out relevant experiments. The experimental results show that the accuracy of vulnerability detection on SARD data set is 96.92%, which is higher than other binary vulnerability detection methods based on neural network. © 2022 IEEE.

关键词： Deep neural networks

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Analysis of security capability of MVX based on probabilistic attack and defense models 3

Analysis of security capability of MVX based on probabilisti...

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3rd International Conference on Computer Science and Communication Technology, ICCSCT 2022

作者： Liu, Zijing Zhang, Zheng Xi, Ruicheng Zhu, Pengzhe State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China

ISBN: (纸本)9781510661240

Multi Variant eXecution (MVX) is a security defense technique that uses software diversity to protect system from attacks. MVX improves security capability by enhancing system endogenous security compared to traditional passive defense techniques. However, the current MVX technique lacks formal theoretical analysis and cannot effectively assess the overall security of the system. To address the constraint relationship between complex attack means and dynamic defense environment, we construct a novel atomic combination attack chain model, which decomposes macro attack means into single atomic attack behaviors and provides theoretical support for analyzing the security capability of dynamic systems. Then, the defense model of the MVX system is established, and the defense model's security capability is analyzed using the attack model. Finally, the advantages and shortcomings of the security defense capability of the MVX system are evaluated based on a typical kernel attack example, and system optimization improvement measures are proposed. © 2022 SPIE.

关键词： Network security

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A Bidirectional Data Packet Tampering Method for Linux System

A Bidirectional Data Packet Tampering Method for Linux Syste...

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2022 International Conference on Network Communication and Information Security, ICNCIS 2022

作者： Lv, Siou Yang, Pengfei Liu, Shengli State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China

ISBN: (纸本)9781510661134

Network data security is very important for each user and service provider, and every process of network data transmission is at risk of being tampered with. In this paper, we proposed a bidirectional tampering method of network data for Linux system. In this method we uses the combination of Netfilter and iptables, and uses the NetfilterQueue module in Python to tamper with the packets entering and leaving a Linux host. This tampering operation is transparent to upper users and may cause domain name redirection or many other serious consequences which threaten the security of hosts. Finally, the feasibility of this tampering method is verified by experiments. © 2022 SPIE.

关键词： Python

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A Binary Function Name Prediction Method Based on Variable Alignment and Translation Model 4

A Binary Function Name Prediction Method Based on Variable A...

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4th International Conference on Machine Learning and Computer Application, ICMLCA 2023

作者： Xia, Bing Yin, Jiabin Ge, Yunxiang Yang, Ruinan ZhongYuan University of Technology Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China ZhongYuan University of Technology Zhengzhou China

ISBN: (纸本)9798400709449

Binary function naming is a code analysis task that generates functional descriptions of functions, and its results can be applied in the fields of malicious code analysis, vulnerability causation analysis, and algorithm governance. Aiming at the shortcomings of the pseudocode abstract syntax tree being difficult to extract and the binary function naming scheme having low accuracy rate, a binary function naming prediction model A2N based on variable alignment and sequence translation model is proposed. First, A2N extracts the function variable features of binary files from debugging information and performs variable alignment with the pseudocode obtained from decompiling;then, it obtains the hierarchical structure of the binary functions and designs the node extraction rules to generate an abstract syntax tree AST for each function;then, extract the paths between the leaf nodes of the AST and serialize the tree structure to represent it;finally, with the help of the neural network translation model, establish a mapping between the AST and the binary function names to realize the prediction function. The experimental results show that compared with Dire, Nero and XFL models, the F1 value of A2N is improved by 84%, 44% and 14% on file-level isolation experiments respectively, and the F1 value reaches 80.94% on function-level isolation experiments. © 2023 ACM.

关键词： Forecasting

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Multiuser Computation Offloading for Long-Term Sequential Tasks in Mobile Edge computing Environments

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Tsinghua Science and Technology 2023年第1期28卷 93-104页

作者： Huanhuan Xu Jingya Zhou Wenqi Wei Baolei Cheng School of Computer Science and Technology Soochow UniversitySuzhou 215006China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214125China Provincial Key Laboratory for Computer Information Processing Technology Soochow UniversitySuzhou 215006China School of Computer Science Georgia Institute of TechnologyAtlantaGA 30332USA

Mobile edge computing has shown its potential in serving emerging latency-sensitive mobile applications in ultra-dense 5G networks via offloading computation workloads from the remote cloud data center to the nearby network ***,current computation offloading studies in the heterogeneous edge environment face multifaceted challenges:Dependencies among computational tasks,resource competition among multiple users,and diverse long-term *** applications typically consist of several functionalities,and one huge category of the applications can be viewed as a series of sequential *** this study,we first proposed a novel multiuser computation offloading framework for long-term sequential ***,we presented a comprehensive analysis of the task offloading process in the framework and formally defined the multiuser sequential task offloading ***,we decoupled the long-term offloading problem into multiple single time slot offloading problems and proposed a novel adaptive method to solve *** further showed the substantial performance advantage of our proposed method on the basis of extensive experiments.

关键词： mobile edge computing sequential tasks computation offloading dependency

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An Improved Authenticated key Agreement Protocol for IoT and Cloud Server 5th

An Improved Authenticated Key Agreement Protocol for IoT an...

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5th International Conference on Security and Privacy in New computing Environments, SPNCE 2022

作者： Ma, Yongliu Ma, Yuqian Cheng, Qingfeng State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Strategic Support Force Information Engineering University Zhengzhou450001 China

ISBN: (纸本)9783031306228

The internet of things (IoT) is a complex network system with applications in all walks of life. However, there are various risks in the process of information transmission between IoT devices and servers. Recently, research on the security of authenticated key agreement (AKA) protocols in the IoT environment has gradually increased. Iqbal et al. proposed an AKA protocol between IoT and cloud servers and proved that it was secure under the eCK model. This paper shows that the Iqbal et al.’s protocol has two security flaws, which are resisting ephemeral key leakage attack and key compromise impersonation attack, and proposes a new AKA protocol in the IoT environment. Through the security proof and formal analysis, it is proved that the new protocol is secure under the eCK model. Comparing the protocol proposed in this paper with other similar protocols, it is found that the protocol in this paper achieves a balance between security performance and communication consumption. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Internet of things

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Haica: A High Performance computing & Artificial Intelligence Fused computing Architecture 1

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22nd International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2022

作者： Chen, Zhengbo Zheng, Fang Guo, Feng Yu, Qi Chen, Zuoning Information Engineering University Zhengzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China Chinese Academy of Engineering Beijing China

ISBN: (数字)9783031226779

ISBN: (纸本)9783031226762

In recent years, HPC and AI fusion, which refers to applying AI technology to traditional HPC applications, has become a new trend. HPC and AI fusion requires supports for multiple precisions used in both domains. While, supporting multiple precisions in a single computing unit is not easy. Prior research typically targets on modifying a high-precision FMA to support low precisions. However, such efforts suffer from disadvantages of increased latency and limited compute throughput for low-precision operations, high area and power overhead, and limited support of new data formats appeared in AI domain. To address this issue, we propose Haica, a double-precision FMA and low-precision systolic array fused architecture, to achieve HPC and AI fusion. Our work has two innovations. First, we propose a low-cost multiple-low-precision FMA by taking advantage of the commonality among FP16, BF16, and TF32. Second, inspired by the idea of splicing high precision with low precision, we replace the multiply and merge modules in a double-precision FMA with a modified systolic array that is composed of the proposed low-precision FMAs. We implement the logic design of Haica using RTL and evaluate its overhead. Results show that compared to the naive combination of a double-precision FMA and single-half-mixed-precision systolic array, Haica provides extra support for BF16 and TF32 with only 7.87% area and 33.26% power overhead. This demonstrates that Haica achieves HPC and AI fusion in a cost-effective manner. © 2023, Springer Nature Switzerland AG.

关键词： Artificial intelligence

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Optimal weight support vector regression ensemble with cluster-based subsampling for electricity price forecasting

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Journal of Intelligent and Fuzzy Systems 2024年第1期1卷 1-16页

作者： Li, Yuerong Zhang, Yuhua Che, Jinxing School of Science Nanchang Institute of Technology Jiangxi Nanchang China Key Laboratory of Engineering Mathematics and Advanced Computing Nanchang Institute of Technology Jiangxi Nanchang China

Accurate prediction of short-term electricity price is the key to obtain economic benefit and also an important index of power system planning and management. Support vector regression (SVR) based ensemble works have gained remarkable achievements in terms of high accuracy and steady performance, but they are highly dependent on data representativeness and have a high computational complexity O (k ∗ N 3) of data samples and parameter selection. To further improve the data representativeness and reduce its computational complexity, this paper develops a new approach to forecast electricity price via optimal weighted ensemble. In the model, the cluster-based subsampling algorithm is proposed to categorize the inputs being seasonally decomposed into several groups, and representative data are drawn from each group in a certain proportion to ensure that each subset trained with SVR has the same representativeness and features. Moreover, the optimal weighted combination method is presented to assign weights to the sub-SVRs to obtain the optimal support vector regression ensemble model (OWSSVRE). The experimental results show that the improved support vector regression ensemble model with the same features and representativeness of the subset has better performance in electricity price forecasting. As a result, it is suitable to support decision making in the energy and other sectors. © 2024 - IOS Press. All rights reserved.

关键词： K-means clustering

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An enhanced key exchange protocol exhibiting key compromise impersonation attacks resistance in mobile commerce environment

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Science China(Information Sciences) 2021年第9期64卷 249-251页

作者： Ting CHEN Xinghua LI Qingfeng CHENG School of Cyber Engineering Xidian University State Key Laboratory of Mathematical Engineering and Advanced Computing

Dear editor,Numerous three-party authenticated key exchange(3 PAKE)protocols have been presented, which allow the establishment of a secure session by utilizing a session key shared between two clients with the assistance of a server trusted by both the clients via an unprotected network communication environment. The 3 PAKE protocols can be applied to various scenarios, including mobile commerce environment.

关键词： three-party authentication key exchange key compromise impersonation attack mobile-commerce environments security analysis

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