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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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A Survey on Knowledge Graph Representation Learning with Text Information 21

A Survey on Knowledge Graph Representation Learning with Tex...

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Proceedings of the 3rd World Symposium on Software engineering

作者： Ling Wang Jicang Lu Gang Zhou State Key Laboratory of Mathematical Engineering and Advanced Computing China

ISBN: (纸本)9781450384094

Knowledge graph representation learning provides a lot of help for subsequent tasks such as knowledge graph completion, information retrieval, and intelligent question answering. By representing the knowledge graph as low-dimensional dense vectors, these tasks can improve efficiency significantly. However, limited by the sparseness and huge scale of the actual structure, representation learning only from a structural perspective can no longer meet the research *** improve the performance, researchers introduced auxiliary information into representation learning. This paper focuses on models using text as auxiliary information, dividing all text-combined models into two categories: Closed-world assumption models and Open-world assumption models. The former is limited by the model's demand for the structural representation of the graph itself, and can only predict the entities and relationships that already exist in the knowledge graph. The latter can handle entities that have not previously been seen during model training, and connect brand-new entities to the knowledge graph, which is more in line with the dynamic trend of the knowledge graph in real world. Open-world assumption models can be further subdivided into multiple types according different joint functions, such as alignment function, fusion function, score function and transformation function. This paper summarizes existing methods in detail and looks forward to future possible research directions.

关键词： Open-world assumption Representation learning Knowledge graph Text information

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Malware Detection Method based on Control Flow Analysis 2019

Malware Detection Method based on Control Flow Analysis

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Proceedings of the 2019 7th International Conference on Information Technology: IoT and Smart City

作者： Peng Shan Qingbao Li Ping Zhang Yanyang Gu State Key Laboratory of Mathematical Engineering and Advanced Computing China

ISBN: (纸本)9781450376631

With the rapid development of computer technology and the iteration of malware, numerous computer malware detection methods have been proposed, among which malware detection based on machine learning has become an important research direction. Opcode sequences are often used as an important feature of machine learning models for training and testing. However, opcode sequences extracted orderly from raw disassembly text may not adequately reflect the behavior of executables. In order to solve this problem, this paper proposes a new malware detection method based on the control flow of executables. This method analyzes the control flow of executables and extracts execution traces from by the unit of function. This paper uses the execution traces to represent the behavior of the executables and present the execution traces by opcode sequences. In order to improve the training efficiency and reduce the feature dimensionality, this paper propose an x86 intermediate code. Then we convert the opcode sequences into the corresponding intermediate code sequences and vectorize them using Vector Space Model (VSM) for training and testing. This paper implements Naïve Bayes Classifier, Support Vector Machines and Random Forest for classification. The experiment result shows that the Random Forest algorithm has the best performance, with an accuracy of 90.8% and the model establishment time is 22s. Compared with the traditional methods based on disassembly text, the accuracy is improved by 1.4%, compared with the methods using x86 opcode, the efficiency is increased by 62%.

关键词： Control Flow Analysis Machine Learning Intermediate Code Malware Detection

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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 Sample-Based Approximate Ranking Method for Large Graphs

A Sample-Based Approximate Ranking Method for Large Graphs

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International Conference on advanced Cloud and Big Data (CBD)

作者： Rujun Sun Lufei Zhang Zuoning Chen State Key Laboratory of Mathematical Engineering and Advanced Computing China

Graph centrality can be estimated by random walk algorithms such as PageRank. These algorithms are useful when ranking items with relationships, and are based on global structure of the graph. It needs to traverse the entire edge-set more than once to get a convergent result. However, when it comes to large graphs, traversing the whole graph is costly, especially when a single node's information is wanted. How to get a rough look at the rank of a specific node? Can the methods be simpler that don't bother to scan the entire graph? How to scale up the method to get more information of the graph? In this paper, we proposed a simple and light algorithm to get approximate rank value of a node. It could be simplified by sampling and expanded to distributed environment. Experiments on representative public graphs have shown that the method can provide an approximate ranking. And the higher ranking a node has by global algorithms, the more accurate the approximate rank will be. Our method also reduces the computation to several orders of magnitude than traditional global algorithms. With sampling techniques, it can outperforms the basic method by additionally reducing computation. It is useful in both estimation and edge computing.

关键词： Approximation algorithms Peer-to-peer computing Indexes Semantics Estimation Edge computing Distributed databases

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Path test data generation using adaptive simulated annealing particle swarm optimization

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Soft computing 2024年第17-18期28卷 9587-9607页

作者： Jiao, Chongyang Zhou, Qinglei State Key Laboratory of Mathematical Engineering and Advanced Computing PLA Strategic Support Force Information Engineering University Zhengzhou450001 China Henan Information Engineering School Zhengzhou Vocational College of Industrial Safety Zhengzhou450000 China School of Computer and Artificial Intelligence Zhengzhou University Zhengzhou450001 China

Software testing is an effective means of ensuring software quality. The cost of software testing is the main component of the total cost of software development. The generation of test data is very important in testing, because the efficiency of testing depends on the test data used. A significant part of software testing automation is the test data generation. How to automatically generate test datasets is still an open problem. Search-based software testing (SBST) is a process of generating test data that employs meta-heuristic methods to resolve tough NP-hard problems. The test data generation problem belongs to NP-hard problems. This paper focuses on the automatic generation of test data for path coverage based on control flow criteria in structural testing. Some meta-heuristic algorithms have been used to search for software test data. To advance the efficiency and effectiveness of path test data generation, an adaptive simulated annealing particle swarm optimization (ASAPSO) algorithm is proposed. The probabilistic jumping property of simulated annealing (SA) algorithm is introduced into the particle swarm optimization (PSO) algorithm to make the particle accept bad solution at a certain probability during the searching process, and therefore boost the capacity of the proposed algorithm to bounce from the local optimum. The fitness function is constructed by the branch function superposition to properly guide the search process. In addition, to improve the convergence speed of the algorithm, an adaptive adjustment scheme based on inertial weight and an adjustment scheme based on learning factor are proposed as well. The experimental results show that the proposed method can effectually avoid premature convergence and effectively upgrades the efficiency of generating test data automatically. It is also competitive in solving other complicated optimization problems. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Natur

关键词： Software testing

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Software Vulnerability Mining Techniques Based on Data Fusion and Reverse engineering

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Wireless Communications and Mobile computing 2022年第0期2022卷

作者： Liu, Tieming State Key Laboratory of Mathematical Engineering and Advanced Computing Henan Zhengzhou450001 China

Software vulnerability mining is an important component of network attack and defense technology. To address the problems of high leakage rate and false positive rate of existing static analysis methods, this paper proposes a static analysis vulnerability detection technique based on data fusion for source code. By parsing the analysis results of different detection methods and fusing the data, the technique can effectively reduce the false positive rate and the false positive rate. A prototype of a scalable source code static analysis tool is designed and implemented, which can be automatically optimized by user feedback. Finally, an example is given to demonstrate how to uncover buffer overflow software vulnerabilities in the helpctr program based on reverse engineering techniques. The experimental results show that the false positive and false negative rates are significantly reduced compared to individual vulnerability detection methods. © 2022 Tieming Liu.

关键词： Data fusion

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Accountable multi-authority ciphertext-policy attribute-based encryption without key escrow and key abuse 9th

Accountable multi-authority ciphertext-policy attribute-base...

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9th International Symposium on Cyberspace Safety and Security, CSS 2017

作者： Yu, Gang Ma, Xiaoxiao Cao, Zhenfu Zhu, Weihua Zeng, Junjie State Key Laboratory of Mathematical Engineering and Advanced Computing Information Science and Technology Institute Zhengzhou450001 China Shanghai Key Lab for Trustworthy Computing East China Normal University Shanghai200062 China Zheng Zhou Vocational University of Information and Technology Zhengzhou450046 China

ISBN: (纸本)9783319694702

Ciphertext-policy attribute-based encryption (CP-ABE) is a promising public key encryption primitive enabling fine-grained access control on shared data in public cloud. However, two quite challenging issues, the prevention of key escrow and key abuse, still exist in CP-ABE system. In this paper, we propose a multi-authority CP-ABE scheme without key escrow and key abuse. To prevent key escrow, multiple authorities are employed to perform the same procedure of key generation for an attribute. Thus, no individual authority or colluded authorities that manage no common attribute can decrypt any ciphertext, and it can also resist collusion attack from curious authority with the help of dishonest users. To prevent key abuse of dishonest users, user’s global identifier along with a signature is embedded into the secret key. Thus, any third party can learn the identity from a shared secret key and publicly verify its validity. An advantage of simultaneously preventing key escrow and key abuse is that the proposed scheme can achieve accountability, i.e. an auditor can publicly audit a user or authorities abuse the secret key. At last, the proposed scheme is fully secure in the random oracle model, and due to a key aggregate algorithm its efficiency is comparable to the decentralizing CP-ABE scheme [18] on which it is based. © 2017, Springer International Publishing AG.

关键词： Access control

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A robust image steganography method resistant to scaling and detection

A robust image steganography method resistant to scaling and...

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作者： Zhang, Yue Luo, Xiangyang Wang, Jinwei Yang, Chunfang Liu, Fenlin State Key Laboratory of Mathematical Engineering and Advanced Computing China School of Computer and Software Nanjing University of Information Science and Technology China Zhengzhou Science and Technology Institute China

The current image steganography algorithms mainly focus on the anti-detectability rather than the robustness to scaling attacks. Therefore, it is difficult to extract the secret messages correctly after stego images subject to scaling attacks. To this end, an image steganography method for the nearest-neighbor interpolation method in image scaling is proposed, which can resist both scaling attack and statistical detection. First, the principle of nearest-neighbor interpolation method is analyzed and summarized, which is using the resized pixel coordinates to find the original adjacent pixels, and obtaining the weights of the adjacent original pixels by the distance between resized pixel and the original adjacent pixels, finally calculating the resized pixel value. Second, the scaling invariant pixels are extracted using the principle of nearest-neighbor interpolation method to generate a new cover image. Then the distortion functions in WOW, S-UNIWARD and MiPOD are used to calculate the new cover’s distortion to minimize the distortion embedding using STCs coding. Finally, resize the stego image to the original size. The steganalysis experiments based on BossBase-1.01 image library and SPAM, maxSRM features demonstrate that the proposed method has good resistance of scaling attack and Statistical detection under various scaling factors and payloads. © 2018 Taiwan Academic Network Management Committee. All rights reserved.

关键词： Pixels

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Open Set Recognition for Encrypted Traffic using Intra-class Partition and Boundary Sample Generation 5

Open Set Recognition for Encrypted Traffic using Intra-class...

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

作者： Li, Xue Fei, Jinlong Qi, Zan Lv, Zhuo Jiang, Heng PLA Information Engineering University State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China PLA Information Engineering University National Digital Switching System Engineering Technological Research Center Zhengzhou China

ISBN: (纸本)9781665479677

Existing deep learning-based encrypted traffic recognition methods can achieve high precision identification performance while protecting user privacy, but almost all of them focus on closed sets, in which training data and test data come from the same label space. However, the real network environment is open, and it is necessary for traffic identification systems to deal with previously unseen categories. To classify known categories at a fine granularity and identify unknown ones, we propose a novel open-set recognition method for encrypted traffic. The decision boundary sample generation method based on constrained Generative Adversarial Networks is presented to generate samples from low-density regions in the known data space. Furthermore, an end-to-end open-set classifier is built using the accurate and diverse simulative samples of unknown classes through intra-class partition and boundary sample generation. Finally, the effectiveness of the proposed method is validated through numerical experiments. © 2022 IEEE.

关键词： Deep learning

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