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2nd International Conference on Algorithms, computing and Artificial Intelligence, ACAI 2019

作者： Zheng, Jianyun Pang, Jianmin Zhang, Xiaochuan Zhou, Xin Li, MingLiang Wang, Jun State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450002 China

ISBN: (纸本)9781450372619

Vulnerability detection, especially vulnerability automatic detection, have long been an area of active research. Considering that RNN can model dependencies automatically, we propose a recurrent neural network (RNN) based method for binary code vulnerability detection. We collected correspond to 4 types of vulnerabilities, including CWE-134, CWE-191, CWE-401 and *** find which RNN is better in vulnerability detection, we evaluated 6 different RNNs, including SRNN, BSRNN, LSTM, BLSTM, GRU and BGRU. The results demonstrated that BSRNN is better than others in vulnerability detection. © 2019 ACM.

关键词： Network security

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Steady-state Topology Discovery of Target Networks Based on Statistics Method 5th

Steady-State Topology Discovery of Target Networks Based on ...

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5th International Conference on Artificial Intelligence and Security, ICAIS 2019

作者： Yang, Di Liu, Yan Chen, Jing China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9783030242671

The progress of target network topology discovery research is slow due to the uncertainty of the target network range, and large-scale network measurement activities lead to a large accumulation of "false links" in the results, it is difficult to obtain a relatively accurate network topology. In this paper, we proposed a statistical-based target network steady-state topology discovery method. By statistical analyzing the characteristics of the measured data, we have proposed corresponding solutions to network boundary recognition, "false links" deletion and network steady-state topology construction, so that a relatively complete and accurate target network steady topology can be obtained. We also use this method to probe the HK (Hong Kong) and TW (Tai Wan) network and compare it with the data of CAIDA in the same period. Not only do the number of nodes and edges found are increased by two or three orders of magnitude, but also the number of "false links" in the results is greatly reduced. © 2019, Springer Nature Switzerland AG.

关键词： Network topology

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Research on Programmable Logic Controller Security 2

Research on Programmable Logic Controller Security

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

作者： Wu, Haolan Geng, Yangyang Liu, Ke Liu, Wenwen State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China

With the convergence of computer technology and industrial networks, attackers are not limited to attacking only individual users' computers, turning to attack industrial control systems that can cause major infrastructure problems. Programmable Logic Controllers (PLC) are the core components of industrial control systems. Its safety has a profound impact on the safety of the entire industrial system. This paper firstly classifies the security research of PLC according to the structure and function, and expounds the existing security defects of PLC from the aspects of firmware security, operation security and program security. Then it summarizes and analyzes four types of security protection measures: the integrity of verification firmware, protocol security encryption, code formal verification, and program security defence detection. Finally, according to the overall safety of the industrial system and the actual development of the current PLC, we discuss the development trend of safety research. © Published under licence by IOP Publishing Ltd.

关键词： Programmable logic controllers

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Truth discovery on multi-dimensional properties of data sources 19

Truth discovery on multi-dimensional properties of data sour...

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2019 ACM Turing Celebration Conference - China, ACM TURC 2019

作者： Zheng, Yan Yin, Meijuan Luo, Junyong He, Gongzhen State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450002 China

ISBN: (纸本)9781450371582

In the era of information explosion, data fusion has captured increasing attention from researchers as it plays an important part in data application. However, resolving the inconsistency of information generated by various data sources, i.e., truth discovery, has posed great challenges to data fusion. Although existing truth discovery methods mainly focus on source quality, they conduct the truth derivation iteratively only based on the accuracy of sources rather than the recall, which leads to the bad precision. Considering the assumption, sources are independent, cannot satisfy the reality of diverse correlations between them any more. A Gaussian Truth Finder with Correlations (GTFC) algorithm has been proposed in this paper. GTFC iteratively derives the truth, accuracy and recall of sources. The empirical results demonstrate that GTFC can significantly outperform the state-of-the-art algorithms. © 2019 Association for computing Machinery.

关键词： Data fusion

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Improvement of Differential Fault Attack Based on Lightweight Ciphers with GFN Structure 1

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5th International Conference on Artificial Intelligence and Security, ICAIS 2019

作者： Gao, Yang Wang, Yongjuan Yuan, Qingjun Wang, Tao Wang, Xiangbin State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China

ISBN: (数字)9783030242657

ISBN: (纸本)9783030242640

In this paper, we focus on differential fault attack on lightweight block ciphers with GFN (Generalized Feistel Networks) structure. With regard to fault injection model and differential equations solving, two improved DFA (Differential Fault Analysis) methods are proposed. Based on this, we present the improved attack process which aims at applying lightweight block ciphers with GFN structure. We conduct 10000 DFA experiments on TWINE and LBlock. Result shows that it only takes 9.18 and 8.42 faults on average to recover the main key K respectively. Moreover, time and space complexity are both negligible. © 2019, Springer Nature Switzerland AG.

关键词： Lyapunov methods

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Building smart classroom of combinatorial mathematics based on PBL teaching model 10

Building smart classroom of combinatorial mathematics based ...

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10th International Conference on Information Technology in Medicine and Education, ITME 2019

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

ISBN: (纸本)9781728139173

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. © 2019 IEEE.

关键词： Combination mathematics PBL teaching mode Smart classroom

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Asynchronous Functional Brain Network Construction with Spatiotemporal Transformer for MCI Classification

TechRxiv

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TechRxiv 2023年

作者： Tang, Xiang Zhang, Jianjia Wu, Xiaotong Zhou, Luping Wang, Lei Wu, Weiwen Shen, Dinggang The School of Biomedical Engineering Sun Yat-sen University China School of Electrical and Information Engineering University of Sydney Australia School of Computing and Information Technology University of Wollongong Australia The School of Biomedical Engineering State Key Laboratory of Advanced Medical Materials and Devices ShanghaiTech University Shanghai201210 China Shanghai United Imaging Intelligence Company Ltd. Shanghai200230 China Shanghai Clinical Research and Trial Center Shanghai201210 China

Construction and analysis of functional brain networks (FBNs) with rs-fMRI is a promising method to diagnose functional brain diseases. Nevertheless, the existing methods suffer from several limitations. First, the functional connectivities (FCs) of the FBN are usually measured by the temporal co-activation level between rs-fMRI time series from regions of interest (ROIs). While enjoying simplicity, the existing approach implicitly assumes simultaneous co-activation of all the ROIs, and models only their synchronous dependencies. However, the functional coactivation is not necessarily always synchronous due to the time lag of information flow and cross-time interactions between ROIs. Therefore, it is desirable to model the asynchronous functional interactions. Second, the traditional methods usually construct FBNs at individual level for feature extraction and classification, leading to large variability and degraded diagnosis accuracy when modeling asynchronous FBN. Third, the FBN construction and analysis are conducted in two independent steps without joint alignment for the target diagnosis task. To address the first limitation, this paper proposes an effective sliding-windowbased method to model spatiotemporal FCs in Transformer. Regarding the second limitation, we propose to learn common and individual FBNs adaptively with the common FBN as prior knowledge, thus alleviating the variability and enabling the network to focus on the individual diseasespecific asynchronous FCs. To address the third limitation, the common and individual asynchronous FBNs are built and analyzed by an integrated network, enabling end-to-end training and improving the flexibility and discriminativity. The effectiveness of the proposed method is consistently demonstrated on three data sets for MCI diagnosis. © 2023, CC BY-NC-SA.

关键词： Computer aided diagnosis

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Robust three-qubit search algorithm in Rydberg atoms via geometric control

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Physical Review A 2022年第5期106卷 052610-052610页

作者： Bing-Bing Liu Zheng Shan M.-R. Yun D.-Y. Wang B.-J. Liu L.-L. Yan M. Feng S.-L. Su Key Laboratory of Material Physics Ministry of Education School of Physics and Microelectronics Zhengzhou University Zhengzhou 450001 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450001 Henan China Department of Physics Southern University of Science and Technology Shenzhen Guangdong 518055 China State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics Wuhan Institute of Physics and Mathematics Innovation Academy of Precision Measurement Science and Technology Chinese Academy of Sciences Wuhan 430071 China Research Center for Quantum Precision Measurement Guangzhou Institute of Industry Technology Guangzhou 511458 China Department of Physics Zhejiang Normal University Jinhua 321004 China

Rydberg atoms possess long coherence time and inherent scalability, which makes it promising to implement quantum algorithms. An exact and robust quantum search algorithm (SA) is essential to some practical applications. Here we propose a multisolution three-qubit SA by employing quantum circuit and geometric operations, in which the target states can be successfully searched with the fidelity of at least 99.8% and the geometric operators guarantee robustness against systematic errors. In particular, the geometric three-qubit gate operators employed reduce the implementation time and help to resist against the detrimental influence of decoherence. Moreover, our scheme can be straightforwardly extended to multiqubit cases. We have carried out numerical simulations based on the master equation to illustrate the superiority of our scheme. We consider that our study provides an alternative method for executing quantum SAs with high success probability.

关键词： Geometric & topological phases Optimization problems Quantum algorithms Rydberg atoms & molecules

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Joint Beamforming Design for Intelligent Omni Surface Assisted Wireless Communication Systems

arXiv

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arXiv 2022年

作者： Cai, Wenhao Li, Ming Liu, Yang Wu, Qingqing Liu, Qian The School of Information and Communication Engineering Dalian University of Technology Dalian116024 China The State Key Laboratory of Internet of Things for Smart City University of Macau 999078 China Guangdong-Macau Joint Laboratory for Advanced and Intelligent Computing China The School of Computer Science and Technology Dalian University of Technology Dalian116024 China

Intelligent reflecting surface (IRS) has been widely considered as one of the key enabling techniques for future wireless communication networks owing to its ability of dynamically controlling the phase shift of reflected electromagnetic (EM) waves to construct a favorable propagation environment. While IRS only focuses on signal reflection, the recently emerged innovative concept of intelligent omni-surface (IOS) can provide the dual functionality of manipulating reflecting and transmitting signals. Thus, IOS is a new paradigm for achieving ubiquitous wireless communications. In this paper, we consider an IOS-assisted multi-user multi-input single-output (MU-MISO) system where the IOS utilizes its reflective and transmissive properties to enhance the MU-MISO transmission. Both power minimization and sum-rate maximization problems are solved by exploiting the second-order cone programming (SOCP), Riemannian manifold, weighted minimum mean square error (WMMSE), and block coordinate descent (BCD) methods. Simulation results verify the advancements of the IOS for wireless systems and illustrate the significant performance improvement of our proposed joint transmit beamforming, reflecting and transmitting phase-shift, and IOS energy division design algorithms. Compared with conventional IRS, IOS can significantly extend the communication coverage, enhance the strength of received signals, and improve the quality of communication links. © 2022, CC BY.

关键词： Mean square error

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Structure-Preserving Operator Learning: Modeling the Collision Operator of Kinetic Equations

arXiv

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arXiv 2024年

作者： Lee, Jae Yong Schotthöfer, Steffen Xiao, Tianbai Krumscheid, Sebastian Frank, Martin Center for Artificial Intelligence and Natural Sciences Korea Institute for Advanced Study Seoul Korea Republic of Oak Ridge National Laboratory Computer Science and Mathematics Division Oak RidgeTN United States State Key Laboratory of High Temperature Gas Dynamics Centre for Interdisciplinary Research in Fluids Institute of Mechanics Chinese Academy of Sciences Beijing China School of Engineering Science University of Chinese Academy of Sciences Beijing China Karlsruhe Institute of Technology Scientific Computing Center Karlsruhe76131 Germany

This work explores the application of deep operator learning principles to a problem in statistical physics. Specifically, we consider the linear kinetic equation, consisting of a differential advection operator and an integral collision operator, which is a powerful yet expensive mathematical model for interacting particle systems with ample applications, e.g., in radiation transport. We investigate the capabilities of the Deep Operator network (DeepONet) approach to modelling the high dimensional collision operator of the linear kinetic equation. This integral operator has crucial analytical structures that a surrogate model, e.g., a DeepONet, needs to preserve to enable meaningful physical simulation. We propose several DeepONet modifications to encapsulate essential structural properties of this integral operator in a DeepONet model. To be precise, we adapt the architecture of the trunk-net so the DeepONet has the same collision invariants as the theoretical kinetic collision operator, thus preserving conserved quantities, e.g., mass, of the modeled many-particle system. Further, we propose an entropy-inspired data-sampling method tailored to train the modified DeepONet surrogates without requiring an excessive expensive simulation-based data generation. © 2024, CC BY-NC-SA.

关键词： Kinetic energy

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