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SSRN 2024年

作者： Liu, Lili Yao, Jinyang Li, Yingying Zhang, Ping Xu, Jinlong Zhao, Bo Shan, Zheng State Key Laboratory of Mathematical Engineering and Advanced Computing Henan Zhengzhou450001 China

With the continuous development of computing technology, an increasing number of vendors have integrated SIMD extension components into processors. These components can accelerate program execution efficiency and have been widely applied in various fields. Past research on SIMD components has primarily focused on loop-level and superword-level, while function-level vectorization can further exploit the parallel potential of these components, thereby enhancing application performance. Currently, OpenMP can achieve function vectorization based on directives. However, this method requires directives to be added to both the loop where the call point is located and the called functions, which is cumbersome and increases the burden on programmers. This paper proposes a directive-based function vectorization method. First, we extend the clauses in OpenMP directives concerning function vectorization data parallelism. Secondly, we implement in the compiler the functionality to automatically add corresponding directives to called functions within functions with the omp simd clone attribute and within OMP_SIMD loops. Finally, we achieve vectorization of loops containing function calls through directives. This method fully exploits the advantages of SIMD instructions, improving application performance. We selected 16 benchmarks from ISPC benchmarks and SIMD library benchmarks to evaluate our method. Experimental results show that compared to scalar, the average speedup reached 4.716x. © 2024, The Authors. All rights reserved.

关键词： Application programming interfaces (API)

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An Abnormal Domain Name Generation Method Based on a Character-Level Model 22

An Abnormal Domain Name Generation Method Based on a Charact...

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Proceedings of the 2022 4th International Conference on Robotics, Intelligent Control and Artificial Intelligence

作者： Chunbing Wu Jinlong Fei State Key Laboratory of Mathematical Engineering and Advanced Computing China

ISBN: (纸本)9781450398343

Internet technology develops by leaps and bounds, new types of botnet attacks are springing up. Currently, most malware are stealthy when implementing attacks since they can bypass detection strategies such as blacklists and sinkholes. These malware mainly use DGA to generate many random domain names to prevent C&C server IP addresses from being traced to the source. To resist botnet attacks, machine-learning methods have been proposed for detecting abnormal domain names. However, there are still some inadequacies, e.g., detection methods based on manual feature extraction couldn't identify novel variant DGA domains, and existing neural network detection methods have weak generalization ability and lack training data for new variant DGA domain names. To address the above problems, this paper proposes an abnormal domain name data generation technology based on a character-level model. Firstly, combining specific text generation-related ideas improves the character-level language model. Secondly, the Bi-GRU network model and attention mechanism are used to thoroughly learn the internal correlation features, and simulate the generation of abnormal domain names. The experimental results show that this method's abnormal domain name data is highly similar to the actual domain name in relative entropy and character composition. Furthermore, it verifies the feasibility of the generated data as training data set for a new variant DGA domain name, which to a certain extent, helps to improve the generalization ability of the abnormal domain name detection model.

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Automatically Generating High-performance Matrix Multiplication Kernels on the Latest Sunway Processor 22

Automatically Generating High-performance Matrix Multiplicat...

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Proceedings of the 51st International Conference on Parallel Processing

作者： Xiaohan Tao Yu Zhu Boyang Wang Jinlong Xu Jianmin Pang Jie Zhao State Key Laboratory of Mathematical Engineering and Advanced Computing China

ISBN: (纸本)9781450397339

We present an approach to the automatic generation of efficient matrix multiplication code on the latest Sunway processor, which will be employed by the next-generation machine of Sunway TaihuLight, one of the fastest supercomputers on earth. The method allows users to write simple C code and automatically generates high-performance matrix multiplication kernels. It uses polyhedral transformations to implement rapid compute decomposition, data exchanges across memory hierarchy and memory latency hiding. An assembly routine is finally integrated into the generated kernels. While achieving up to 90.14% of the theoretical peak performance, our method surpasses a highly tuned library by 9.44%. Compared with existing techniques, our approach reduces the software development life cycle to generate efficient matrix code from months to seconds. We also take into account batched matrix multiplication and some fusion patterns for deep learning (DL), outperforming the library-based implementations by 1.30 × and 1.67 ×.

关键词： high-performance computing basic linear algebra subprograms polyhedral compilation Sunway TaihuLight matrix multiplication

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Searching for similar binary code based on the influence of basic block vertex 3

Searching for similar binary code based on the influence of ...

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2021年第三届先进计算机技术、信息科学与通信国际会议(CTISC2021)

作者： Xiaodong Zhu Liehui Jiang Zeng Chen Lin Yan State key laboratory of mathematical engineering and advanced computing

ISBN: (纸本)9781665418683

Binary code similarity detection(BCSD) has many security applications and has attracted a lot of focus. But existing solutions for BCSD problems mainly focus on comparing the similarity between two binary functions and what need to be compared is not always a pair of equal-size binary *** solve the problem of searching similar binary code for a small size program in a large size program, in this manuscript,we propose a searching method based on the influence of basic block vertex. Firstly, we formalize the similar code searching problem as a subgraph matching problem and extract the attributed control flow graphs(ACFGs) of the binary ***, we propose a novel metrics to measure the influence of each basic block vertex in query ACFGs and choose the vertex with the largest influence value as the central node. Next, we take the matching nodes of the central node in target ACFG as seed nodes and extending each candidate sub-area from the seed nodes. At last, these candidate sub-areas are further filtered and similar subgraphs are verified in these *** results indicate that the proposed method can find similar binary code efficiently.

关键词： Measurement Matched filters Information science Binary codes Search problems Security Flow graphs

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Accelerating Command Injection Vulnerability Discovery in Embedded Firmware with Static Backtracking Analysis 22

Accelerating Command Injection Vulnerability Discovery in Em...

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Proceedings of the 12th International Conference on the Internet of Things

作者： Xiaokang Yin Ruijie Cai Yizheng Zhang Lukai Li Qichao Yang Shengli Liu State Key Laboratory of Mathematical Engineering and Advanced Computing China

ISBN: (纸本)9781450396653

Command injection vulnerability is a severe threat to the embedded device. Most methods detect command injection vulnerability with taint analysis and symbolic execution and achieve promising results. However, they waste too much time analyzing secure sink call-sites, resulting in less efficient vulnerability detection. To tackle the above problem, we propose a novel sink call-site classification method named CINDY to accelerate the command injection vulnerability discovery in embedded firmware with static backtracking analysis. CINDY first performs sink call-sites detection in the binary executables and constructs the data flow for function call parameters. Then, CINDY analyzes whether the parameters passed to sink functions are derived from constant string or not and labels them “secure" or “risky". According to the labels, CINDY classifies the sink call-sites into risky and secure sink call-sites. Finally, CINDY performs taint analysis with symbolic execution to check whether a risky sink call-site is vulnerable. To demonstrate the efficacy of CINDY, we compare CINDY with the state-of-the-art method SaTC, using the dataset published by SaTC. Compared with SaTC, CINDY can filter out more of the secure sink call-sites, with a 35% decrease, and the efficiency is improved by 17% than SaTC.

关键词： Backtracking Analysis Taint Analysis Command Injection Vulnerability Firmware

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A Honeywords Generation Method Based on Deep Learning and Rule-Based Password Attack 4th

A Honeywords Generation Method Based on Deep Learning and Ru...

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4th EAI International Conference on Security and Privacy in New computing Environments, SPNCE 2021

作者： Yang, Kunyu Hu, Xuexian Zhang, Qihui Wei, Jianghong Liu, Wenfen State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Guilin University of Electronic Technology Guilin China

ISBN: (纸本)9783030967901

Honeywords is a simple and efficient method that can help the authentication server to detect password leaks. The indistinguishability between generated honeywords and real passwords is the key to the honeywords generation methods. However, the current honeywords generation methods are difficult to achieve that and are vulnerable to the Top-PW attack. In order to improve the security of the honeywords generation method, this paper combines the deep learning and rule-based password attacks to propose a new honeywords generation method called GHDR. The method first builds a deep learning model to learn whether the rules used in the rule-based password attack are effective for different passwords. When a user sets a password, effective rules will be selected by the model according to the entered password, and then these selected rules will be used to transform the user’s password to generate honeywords. Experimental results show that the proposed honeywords generation method can better resist Top-PW attacks than the state-of-the-art methods. © 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Authentication

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Detecting Double Mixed Compressed Images Based on Quaternion Convolutional Neural Network

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Chinese Journal of Electronics 2024年第3期33卷 657-671页

作者： Hao WANG Jinwei WANG Xuelong HU Bingtao HU Qilin YIN Xiangyang LUO Bin MA Jinsheng SUN Department of Automation Nanjing University of Science and Technology Engineering Research Center of Digital Forensics Ministry of Education Department of Computer and Software Nanjing University of Information Science and Technology School of Management Nanjing University of Posts and Telecommunications Department of Computer Science and Engineering Guangdong Province Key Laboratory of Information Security Technology Sun Yat-sen University State Key Laboratory of Mathematical Engineering and Advanced Computing Qilu University of Technology

Detection of color images that have undergone double compression is a critical aspect of digital image *** the existence of various methods capable of detecting double Joint Photographic Experts Group(JPEG) compression,they are unable to address the issue of mixed double compression resulting from the use of different compression *** particular,the implementation of Joint Photographic Experts Group 2000(JPEG2000)as the secondary compression standard can result in a decline or complete loss of performance in existing *** tackle this challenge of JPEG+JPEG2000 compression,a detection method based on quaternion convolutional neural networks(QCNN) is *** QCNN processes the data as a quaternion,transforming the components of a traditional convolutional neural network(CNN) into a quaternion *** relationships between the color channels of the image are preserved,and the utilization of color information is ***,the method includes a feature conversion module that converts the extracted features into quaternion statistical features,thereby amplifying the evidence of double *** results indicate that the proposed QCNN-based method improves,on average,by 27% compared to existing methods in the detection of JPEG+JPEG2000 compression.

关键词： Color image forensics JPEG JPEG2000 Mixed double compression Quaternion convolutional neural network

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Stepwise DOA Estimation for Coherent and Uncorrelated Mixed Signals on Coprime Array 5

Stepwise DOA Estimation for Coherent and Uncorrelated Mixed ...

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5th IEEE advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2022

作者： Jiang, Heng Li, Lichun Zhang, Hailong Pan, Hongyi Li, Xue College of Information System Engineering Information Engineering University Zhengzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665479677

The coprime array constructs virtual array to obtain higher degrees of freedom (DOF), but the premise of doing so is that the signals are independent of each other. Once there are coherent signals, the signal model of virtual array is destroyed and the method fails. To solve these problems, we propose the stepwise estimation of the Direction of Arrival (DOA) for a mixture of coherent and uncorrelated signals. Firstly, the symmetry of the two coprime subarrays is used to eliminate the uncorrelated signals, and combined with the properties of prime numbers, the coherent source DOA is jointly estimated. The obtained coherent source DOA was combined with the optimization algorithm to remove the coherent signal in the mixed signal. Finally, the virtual domain signal processing method was used to estimate the independent source DOA. This method can effectively reduce the influence of coherent signals on the accuracy of DOA estimation without loss of degrees of freedom. In this paper, the feasibility of the proposed method is proved by theoretical derivation, and the effectiveness of the method is also verified by experimental simulations. © 2022 IEEE.

关键词： Direction of arrival

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A Modeling Method of Cyberspace Security Structure Based on Layer-Level Division 5

A Modeling Method of Cyberspace Security Structure Based on ...

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5th IEEE International Conference on Computer and Communication engineering Technology, CCET 2022

作者： Zhu, Yuwen Yu, Lei State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Information Security Institute of Information Engineering Beijing100000 China

ISBN: (数字)9781665467353

ISBN: (纸本)9781665467353

As the cyberspace structure becomes more and more complex, the problems of dynamic network space topology, complex composition structure, large spanning space scale, and a high degree of self-organization are becoming more and more important. In this paper, we model the cyberspace elements and their dependencies by combining the knowledge of graph theory. Layer adopts a network space modeling method combining virtual and real, and level adopts a spatial iteration method. Combining the layer-level models into one, this paper proposes a fast modeling method for cyberspace security structure model with network connection relationship, hierarchical relationship, and vulnerability information as input. This method can not only clearly express the individual vulnerability constraints in the network space, but also clearly express the hierarchical relationship of the complex dependencies of network individuals. For independent network elements or independent network element groups, it has flexibility and can greatly reduce the computational complexity in later applications. © 2022 IEEE.

关键词： Graph theory

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A Further Understanding of Differential-Linear Cryptanalysis

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Chinese Journal of Electronics 2020年第4期29卷 660-666页

作者： REN Jiongjiong CHEN Shaozhen State Key Laboratory of Mathematical Engineering and Advanced Computing State Key Laboratory of Cryptology

Differential-linear cryptanalysis has attracted much attention since proposed to attack DES in 1994, and then some generalized theories are developed to complement and unify the ***, the links between differential-linear cryptanalysis and other important cryptanalysis methods have been still *** motivation is to fix the *** establishing some boolean equations, we propose the mathematical links among differential, linear and differential-linear *** then generalise the definition of capacity and present some properties of the capacity of differential *** links and properties are employed to explore the relationships between multidimensional differential-linear hulls and integral *** show that a multidimensional differential-linear hull of certain correlation always implies the existence of an integral distinguisher and a zero-correlation linear hull, while a special integral distinguisher indicates the existence of a multidimensional differential-linear hull.

关键词： Block cipher Differential cryptanalysis Linear cryptanalysis Differential-linear cryptanalysis Integral distinguisher Zero-correlation

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