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IEEE International Symposium on Information (IT) in Medicine and Education, ITME

作者： Benchao Yang Guang Zeng Gang Yu State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

With the prevalence of artificial intelligence and the continuous development of information-based teaching, the emergence of smart classrooms has provided a new teaching environment for classroom teaching. As a new and efficient teaching mode, smart classroom has entered schools. Based on the classical PBL teaching method, this paper attempts to construct the question-driven smart classroom of combinatorial mathematics, and shares some teaching experience and experience from the aspects of teaching preparation, teaching implementation and teaching evaluation.

关键词： Education Data analysis Task analysis Information technology Combinatorial mathematics mathematical model

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INSTRCR: Lightweight instrumentation optimization based on coverage-guided fuzz testing

INSTRCR: Lightweight instrumentation optimization based on c...

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IEEE International Conference on Computer and Communication engineering Technology (CCET)

作者： Cao Zhang Wei Yu Dong Yu Zhu Ren State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

In Fuzzing facing binary coverage, the main role of instrumentation is feedback code coverage (in the case of Fuzz for binary, instrumentation can provide coverage information, which plays an important role in guiding the operation of seeds in Fuzz) . The current instrumentation optimization technique mainly relies on the control flow graph (CFG) to select key basic blocks at the basic block level, but the accuracy of this method is not high enough. Considering that the actual path in the actual operation of the binary may be different from the CFG generated in advance, this paper is based on the indirect jump that cannot be accurately analyzed in the CFG, and some of the basic blocks that can be optimized for high-frequency interpolation. According to the algorithm proposed in this paper, The combination of static analysis and dynamic analysis is used to continuously adjust and select key basic block nodes for instrumentation. It is verified by experiments that this kind of instrumentation method can effectively improve the coverage rate and reduce the overhead, and provide effective guidance for Fuzzing, which can effectively reduce the Fuzzer's false negatives.

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The Stacked Seq2seq-attention Model for Protocol Fuzzing

The Stacked Seq2seq-attention Model for Protocol Fuzzing

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International Conference on Computer Science and Network Technology (ICCSNT)

作者： Zicong Gao Weiyu Dong Rui Chang Chengwei Ai State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781728133003

Fuzzing is an effective approach to discover vulnerabilities in software by generating the amount of unexcepted data as inputs to a program. It is difficult to fuzz the protocol automatically because it is necessary to manually construct a template that satisfies the protocol specification to generate test cases. In this paper, we establish stacked seq2seq-attention models to generate protocol test cases automatically. Seq2seq-attention is a machine learning technique which has an encoder-decoder structure to output text sequences based on context. We evaluate the training effect of seq2seq-attention models with different layers of LSTM and point out that the highest correctness of test cases is achieved by 3 layers LSTM. Besides, we implement a fuzzer based on stacked seq2seq attention model and compare with grammar-based fuzzer, which result indicates the test cases generated by our fuzzer discover more unique basic blocks.

关键词： Protocols Fuzzing Training Decoding Security Machine learning Cyberspace

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A survey of industrial control system testbeds 2

A survey of industrial control system testbeds

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2019 2nd International Conference on advanced Materials, Intelligent Manufacturing and Automation, AMIMA 2019

作者： Geng, Yangyang Wang, Yi Liu, Wenwen Wei, Qiang Liu, Ke Wu, Haolan State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China Department of Research and Development Center Beijing Sifang Automation Co. Ltd Beijing100085 China

Industrial Control System(ICS) testbed is the basis of ICS safety research. In order to build an ICS testbed, it is necessary to have a deep understanding of the current research status. This paper introduced the structure and composition of the typical ICS system. Then it simply analyzed the technical characteristics, system framework and advantages and disadvantages of four types of typical ICS testbeds. Finally, it summarized application scenarios of ICS testbed and pointed out some problems in testbed construction and the development direction of ICS testbed with the fusion of cyber and physical. © Published under licence by IOP Publishing Ltd.

关键词： Testbeds

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Field-aware Evolutionary Fuzzing Based on Input Specifications and Vulnerability Metrics

Field-aware Evolutionary Fuzzing Based on Input Specificatio...

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IEEE International Conference on Software engineering and Service Sciences (ICSESS)

作者： Yunchao Wang Zehui Wu Qiang Wei Qingxian Wang State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (数字)9781728109459

ISBN: (纸本)9781728109466

Evolutionary fuzzing technology based on genetic algorithm has become one of the most effective vulnerability discovery techniques due to its fast and scalable advantages. How to effectively mutate the seed input plays a crucial role in improving the efficiency of the fuzzing. A good mutation strategy can increase code coverage and vulnerability triggering probability. Existing fuzzing tools generally focus on how to mutate smartly to improve code coverage to find more vulnerabilities (such as passing the branch with magic bytes), but they still face two challenges which substantially reduces the efficiency of vulnerability discovery. First, the input space is huge and current fuzzers are not aware of the input format, resulting in many mutated inputs are invalid. Second, they believe all bytes are equal and mutate them sequentially, wasting lots of time testing some uninteresting bytes. To this end, this paper proposes a field-aware mutation strategy that can find more vulnerabilities by generating fewer but more effective inputs. Specifically, we extract the field and type information of the seed input through the existing input specifications to ensure that the mutation is performed in field level instead of byte level and the optimal mutation strategy is selected. At the same time, the input fields are scored by code assessment based on vulnerability metrics, thus the more important fields (i.e., fields that are more likely to trigger the vulnerability) are prioritized to be mutated. We implemented a prototype tool, FaFuzzer, and evaluated it on two different datasets consisting of a variety of real-world applications. Experiments show that our field-aware strategy can find more vulnerabilities with fewer inputs than existing tools, while maintaining high code coverage. We found many unknown bugs in five widely used real-world applications and reported them to the relevant vendors.

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DSA-NIE: Double Static Attributes Based Node Importance Evaluation of Inter-Domain Routing System

DSA-NIE: Double Static Attributes Based Node Importance Eval...

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International Conference on Computer and Communications (ICCC)

作者： Huihu Zhu Han Qiu Junhu Zhu Qingxian Wang State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (数字)9781728147437

ISBN: (纸本)9781728147444

Assessing the importance of AS nodes is important for the protection of inter-domain routing system security. However, the existing literature on node importance evaluation methods based on static attributes are difficult to accurately characterize nodes. And which based on dynamic attributes have high time complexity. To address these problems, we analyze the relationship between static structural attributes and dynamic attributes after node failure. It is found that the degree can indirectly reflect the impact of the UPDATE packet propagation and the number of routing paths can reflect the impact caused by load redistribution. And then, we build static attribute characterization model of node failure effect. After that an evaluation method DSA-NIE is put forward. Given the two static attributes, DSA-NIE could effectively assessment of the importance of nodes. When compared with SD-KNI algorithm, the time complexity has been reduced to O(lmn). And the experiment result shows that the failure effect of the key nodes assessed by the DSA-NIE is 7.4% higher than the average, and up to 12.9% higher.

关键词： Routing Time complexity Kernel Power system faults Power system protection Security Load modeling

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Observations of cosmic-ray Sun’s shadow with LHAASO-WCDA 38

Observations of cosmic-ray Sun’s shadow with LHAASO-WCDA

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38th International Cosmic Ray Conference, ICRC 2023

作者： Cui, Ming-Yang Xia, Jie He, Jia-Yin Shi, Guang-Lu Feng, Li Yuan, Qiang Zhang, Yi Cao, Zhen Aharonian, F. An, Q. Axikegu Bai, Y.X. Bao, Y.W. Bastieri, D. Bi, X.J. Bi, Y.J. Cai, J.T. Cao, Q. Cao, W.Y. Cao, Zhe Chang, J. Chang, J.F. Chen, A.M. Chen, E.S. Chen, Liang Chen, Lin Chen, Long Chen, M.J. Chen, M.L. Chen, Q.H. Chen, S.H. Chen, S.Z. Chen, T.L. Chen, Y. Cheng, N. Cheng, Y.D. Cui, M.Y. Cui, S.W. Cui, X.H. Cui, Y.D. Dai, B.Z. Dai, H.L. Dai, Z.G. Danzengluobu della Volpe, D. Dong, X.Q. Duan, K.K. Fan, J.H. Fan, Y.Z. Fang, J. Fang, K. Feng, C.F. Feng, L. Feng, S.H. Feng, X.T. Feng, Y.L. Gabici, S. Gao, B. Gao, C.D. Gao, L.Q. Gao, Q. Gao, W. Gao, W.K. Ge, M.M. Geng, L.S. Giacinti, G. Gong, G.H. Gou, Q.B. Gu, M.H. Guo, F.L. Guo, X.L. Guo, Y.Q. Guo, Y.Y. Han, Y.A. He, H.H. He, H.N. He, J.Y. He, X.B. He, Y. Heller, M. Hor, Y.K. Hou, B.W. Hou, C. Hou, X. Hu, H.B. Hu, Q. Hu, S.C. Huang, D.H. Huang, T.Q. Huang, W.J. Huang, X.T. Huang, X.Y. Huang, Y. Huang, Z.C. Ji, X.L. Jia, H.Y. Jia, K. Jiang, K. Jiang, X.W. Jiang, Z.J. Jin, M. Kang, M.M. Ke, T. Kuleshov, D. Kurinov, K. Li, B.B. Li, Cheng Li, Cong Li, D. Li, F. Li, H.B. Li, H.C. Li, H.Y. Li, J. Li, Jian Li, Jie Li, K. Li, W.L. Li, W.L. Li, X.R. Li, Xin Li, Y.Z. Li, Zhe Li, Zhuo Liang, E.W. Liang, Y.F. Lin, S.J. Liu, B. Liu, C. Liu, D. Liu, H. Liu, H.D. Liu, J. Liu, J.L. Liu, J.Y. Liu, M.Y. Liu, R.Y. Liu, S.M. Liu, W. Liu, Y. Liu, Y.N. Lu, R. Luo, Q. Lv, H.K. Ma, B.Q. Ma, L.L. Ma, X.H. Mao, J.R. Min, Z. Mitthumsiri, W. Mu, H.J. Nan, Y.C. Neronov, A. Ou, Z.W. Pang, B.Y. Pattarakijwanich, P. Pei, Z.Y. Qi, M.Y. Qi, Y.Q. Qiao, B.Q. Qin, J.J. Ruffolo, D. Sáiz, A. Semikoz, D. Shao, C.Y. Shao, L. Shchegolev, O. Sheng, X.D. Shu, F.W. Song, H.C. Key Laboratory of Dark Matter and Space Astronomy Purple Mountain Observatory Chinese Academy of Sciences Nanjing210023 China School of Astronomy and Space Science University of Science and Technology of China Hefei230026 China Key Laboratory of Particle Astrophyics & Experimental Physics Division & Computing Center Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China University of Chinese Academy of Sciences Beijing100049 China TIANFU Cosmic Ray Research Center Sichuan Chengdu China Dublin Institute for Advanced Studies 31 Fitzwilliam Place Dublin 2 Ireland Max-Planck-Institut for Nuclear Physics P.O. Box 103980 Heidelberg69029 Germany State Key Laboratory of Particle Detection and Electronics China University of Science and Technology of China Anhui Hefei230026 China School of Physical Science and Technology School of Information Science and Technology Southwest Jiaotong University Sichuan Chengdu610031 China School of Astronomy and Space Science Nanjing University Jiangsu Nanjing210023 China Center for Astrophysics Guangzhou University Guangdong Guangzhou510006 China Hebei Normal University Hebei Shijiazhuang050024 China Key Laboratory of Dark Matter and Space Astronomy Key Laboratory of Radio Astronomy Purple Mountain Observatory Chinese Academy of Sciences Jiangsu Nanjing210023 China Tsung-Dao Lee Institute School of Physics and Astronomy Shanghai Jiao Tong University Shanghai200240 China Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai200030 China Key Laboratory of Cosmic Rays [Tibet University Ministry of Education Tibet Lhasa850000 China National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China School of Physics and Astronomy Sun Yat-sen University Zhuhai519000 China School of Physics Guangdong Guangzhou510275 China Sino-French Institute of Nuclear Engineering and Technology Sun Yat-sen Unive

During the propagation of cosmic rays (CRs) in the solar system, they are blocked by the Sun and deflected by the magnetic field, resulting in a shadow on the celestial map. As CRs travel from the vicinity of the Sun to the Earth, they encounter deflection from the coronal magnetic field (CMF), the interplanetary magnetic field (IMF), and finally the geomagnetic field (GMF). The extent of deflection is determined by the magnetic field’s intensity, direction, and energy of the CRs. Variations in the magnetic field cause corresponding changes in the position and size of the Sun’s shadow. By observing the Sun’s shadow of CRs, we can investigate the magnetic fields between the Sun and the Earth, complementing other measurements on these magnetic fields. Furthermore, it serves as a means to validate magnetic field models. The Large High Altitude Air Shower Observatory (LHAASO) is a new generation cosmic-ray and gamma-ray experiment in Daocheng, western China. With a vast Water Cherenkov Detector Array (WCDA) spanning 78,000 m2, LHAASO can successfully observe the significant Sun’s shadow within just a few days. Our study uses the WCDA to measure the Sun’s shadow effect caused by CRs over multiple Carrington rotation periods. Subsequently, we compare these results with simulations based on different magnetic field models. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Cosmic rays

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A TrustEnclave-Based Architecture for Ensuring Run-Time Security in Embedded Terminals

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Tsinghua Science and Technology 2017年第5期22卷 447-457页

作者： Rui Chang Liehui Jiang Wenzhi Chen Yaobin Xie Zhongyong Lu the State Key Laboratory of Mathematic Engineering and Advanced Computing the Department of Computer Zhejiang University

The run-time security guarantee is a hotspot in current cyberspace security research, especially on embedded terminals, such as smart hardware as well as wearable and mobile devices. Typically, these devices use universal hardware and software to connect with public networks via the Internet, and are probably open to security threats from Trojan viruses and other malware. As a result, the security of sensitive personal data is threatened and economic interests in the industry are compromised. To address the run-time security problems efficiently, first, a TrustEnclave-based secure architecture is proposed, and the trusted execution environment is constructed by hardware isolation technology. Then the prototype system is implemented on real TrustZone-enabled hardware devices. Finally, both analytical and experimental evaluations are provided. The experimental results demonstrate the effectiveness and feasibility of the proposed security scheme.

关键词： run-time security trusted execution environment hardware isolation TrustZone

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Highlight of LHAASO science results on PeVatrons 38

Highlight of LHAASO science results on PeVatrons

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38th International Cosmic Ray Conference, ICRC 2023

作者： Wu, Sha Chen, Songzhan Cao, Zhen Aharonian, F. An, Q. Axikegu Bai, Y.X. Bao, Y.W. Bastieri, D. Bi, X.J. Bi, Y.J. Cai, J.T. Cao, Q. Cao, W.Y. Cao, Zhe Chang, J. Chang, J.F. Chen, A.M. Chen, E.S. Chen, Liang Chen, Lin Chen, Long Chen, M.J. Chen, M.L. Chen, Q.H. Chen, S.H. Chen, S.Z. Chen, T.L. Chen, Y. Cheng, N. Cheng, Y.D. Cui, M.Y. Cui, S.W. Cui, X.H. Cui, Y.D. Dai, B.Z. Dai, H.L. Dai, Z.G. Danzengluobu della Volpe, D. Dong, X.Q. Duan, K.K. Fan, J.H. Fan, Y.Z. Fang, J. Fang, K. Feng, C.F. Feng, L. Feng, S.H. Feng, X.T. Feng, Y.L. Gabici, S. Gao, B. Gao, C.D. Gao, L.Q. Gao, Q. Gao, W. Gao, W.K. Ge, M.M. Geng, L.S. Giacinti, G. Gong, G.H. Gou, Q.B. Gu, M.H. Guo, F.L. Guo, X.L. Guo, Y.Q. Guo, Y.Y. Han, Y.A. He, H.H. He, H.N. He, J.Y. He, X.B. He, Y. Heller, M. Hor, Y.K. Hou, B.W. Hou, C. Hou, X. Hu, H.B. Hu, Q. Hu, S.C. Huang, D.H. Huang, T.Q. Huang, W.J. Huang, X.T. Huang, X.Y. Huang, Y. Huang, Z.C. Ji, X.L. Jia, H.Y. Jia, K. Jiang, K. Jiang, X.W. Jiang, Z.J. Jin, M. Kang, M.M. Ke, T. Kuleshov, D. Kurinov, K. Li, B.B. Li, Cheng Li, Cong Li, D. Li, F. Li, H.B. Li, H.C. Li, H.Y. Li, J. Li, Jian Li, Jie Li, K. Li, W.L. Li, W.L. Li, X.R. Li, Xin Li, Y.Z. Li, Zhe Li, Zhuo Liang, E.W. Liang, Y.F. Lin, S.J. Liu, B. Liu, C. Liu, D. Liu, H. Liu, H.D. Liu, J. Liu, J.L. Liu, J.Y. Liu, M.Y. Liu, R.Y. Liu, S.M. Liu, W. Liu, Y. Liu, Y.N. Lu, R. Luo, Q. Lv, H.K. Ma, B.Q. Ma, L.L. Ma, X.H. Mao, J.R. Min, Z. Mitthumsiri, W. Mu, H.J. Nan, Y.C. Neronov, A. Ou, Z.W. Pang, B.Y. Pattarakijwanich, P. Pei, Z.Y. Qi, M.Y. Qi, Y.Q. Qiao, B.Q. Qin, J.J. Ruffolo, D. Sáiz, A. Semikoz, D. Shao, C.Y. Shao, L. Shchegolev, O. Sheng, X.D. Shu, F.W. Song, H.C. Stenkin, Yu.V. Stepanov, V. Su, Y. Sun, Q.N. Sun, X.N. Sun, Z.B. Tam, P.H.T. Key Laboratory of Particle Astrophysics Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China Key Laboratory of Particle Astrophysics Experimental Physics Division Computing Center Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China University of Chinese Academy of Sciences Beijing100049 China TIANFU Cosmic Ray Research Center Sichuan Chengdu China Dublin Institute for Advanced Studies 31 Fitzwilliam Place Dublin 2 Ireland Max-Planck-Institut for Nuclear Physics P.O. Box 103980 Heidelberg69029 Germany State Key Laboratory of Particle Detection and Electronics China University of Science and Technology of China Anhui Hefei230026 China School of Physical Science and Technology School of Information Science and Technology Southwest Jiaotong University Sichuan Chengdu610031 China School of Astronomy and Space Science Nanjing University Jiangsu Nanjing210023 China Center for Astrophysics Guangzhou University Guangdong Guangzhou510006 China Hebei Normal University Hebei Shijiazhuang050024 China Key Laboratory of Dark Matter and Space Astronomy Key Laboratory of Radio Astronomy Purple Mountain Observatory Chinese Academy of Sciences Jiangsu Nanjing210023 China Tsung-Dao Lee Institute School of Physics and Astronomy Shanghai Jiao Tong University Shanghai200240 China Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai200030 China Key Laboratory of Cosmic Rays Tibet University Ministry of Education Tibet Lhasa850000 China National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China School of Physics and Astronomy Sun Yat-sen University Zhuhai519000 China School of Physics Sun Yat-sen University Guangdong Guangzhou510275 China Sino-French Institute of Nuclear Engineering and Technology Sun Yat-sen University Zhuhai519000 China School of Physics and Astronomy Yunnan University Yunnan

The observation of ultra-high energy (UHE, E>100 TeV) gamma-ray sources plays a crucial role in identifying Galactic PeV accelerators, also known as PeVatrons. The Large High Altitude Air Shower Observatory (LHAASO) is a large hybrid extensive air shower array, constructed at Haizi Mountain, 4410 m a.s.l., in China. With its wide field of view and high sensitivity, LHAASO is an ideal instrument for the detection and study of PeVatrons within our Galaxy. Since July 2021, the whole LHAASO detector array has been completed and operated in good states. Through an all-sky survey, we have observed ultra-high energy gamma-ray emissions in 43 regions associated with pulsars, supernova remnants (SNR), young star clusters, and other celestial objects. In this proceeding, we will present the results obtained from representative gamma-ray sources and discuss our observations of diffuse gamma-ray emissions along the Galactic plane. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Supernovae

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Creation of magnetic skyrmions in two-dimensional van der Waals ferromagnets by lattice distortion

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Materials Today 2025年

作者： Tingjia Zhang Chendi Yang Xiaowei Lv Tuoyu Zhao Wu Shi Wei Li Jia Liang Renchao Che School of Materials and Chemistry University of Shanghai for Science and Technology Shanghai 200093 China Laboratory of Advanced Materials Shanghai Key Lab of Molecular Catalysis and Innovative Materials Academy for Engineering and Technology Advanced Coatings Research Center of Ministry of Education of China Fudan University Shanghai 200438 China State Key Laboratory of Surface Physics and Institute for Nanoelectronic Devices and Quantum Computing Fudan University Shanghai 200433 China Zhangjiang Fudan International Innovation Center Fudan University Shanghai 201210 China Department of Physics Fudan University Shanghai 200433 China College of Smart Materials and Future Energy and State Key Laboratory of Photovoltaic Science and Technology Fudan University Shanghai 200433 China

Two-dimensional (2D) van der Waals (vdW) ferromagnets provide an excellent platform for exploring exotic physical phenomena such as magnetic skyrmions and quantum topological phases. However, the centrosymmetric crystal structure inherent in these 2D vdW ferromagnets theoretically precludes the formation of magnetic skyrmions and topological phases. In this study, we investigate the origin of the absence of magnetic skyrmions in 2D vdW ferromagnets and propose an effective strategy to induce lattice distortion through doping, thereby enabling the formation of magnetic skyrmions. Specifically, through the integration of density functional theory (DFT) calculations and multiple experimental characterizations, we demonstrate that Co doping in Fe 3 GeTe 2 induces substantial lattice distortion, resulting in a transformation from a centrosymmetric to a non-centrosymmetric crystal structure. This structural modification enables the emergence of a considerable Dzyaloshinskii-Moriya interaction (DMI), which is a necessary condition for skyrmion formation. While the DFT results do not directly predict specific spin textures, the presence of Néel-type skyrmions is verified through Lorentz transmission electron microscopy (LTEM). Additionally, the scalar spin chirality of these magnetic skyrmions acts as a virtual magnetic field, thereby inducing the topological Hall effect (THE) in Co-doped Fe 3 GeTe 2 . Our findings present a reliable method to manipulate spin textures and induce the THE in 2D vdW ferromagnets with non-zero DMI through lattice distortion, offering a promising route for the development of vdW ferromagnet-based spintronic devices.

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