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20th IEEE International Conference on Mobile Ad Hoc and Smart Systems, MASS 2023

作者： Ma, Yongqiang Luo, Xiangyang Li, Ruixiang Du, Shaoyong Liu, Wenyan State Key Laboratory of Mathematical Engineering and Advanced Computing Key Laboratory of Cyberspace Situation Awareness of Henan Province Zhengzhou China

ISBN: (纸本)9798350324334

Rapid and accurate localization of illicit micro-recorders, cameras, and other wireless network devices is of great significance for ensuring public privacy and security. However, existing methods are susceptible to environmental noise, have low localization accuracy, high localization time overhead, and require extensive manual involvement. To address these issues, we propose LENSER, a channel state information based indoor localization scheme for illicit wireless network devices. First, we set detection points to capture signal amplitude distribution changes during the antenna array rotation process, thus determining whether there is a line-of-sight propagation relationship between the detection point and the malicious device. Next, we identify the room containing the malicious device based on the line-of-sight propagation relationship and calibrate the measured position and estimate the direction of the malicious device using existing methods within the room. Finally, we establish a linear space based on the direction of the malicious device and propose an iterative comparison method based on received signal strength indicator to localize malicious devices accessing public Wi-Fi networks within the room. We conducted 1200 experiments in four buildings with different layouts and building materials. The results show that LENSER's average localization time is 12.5 minutes, and the average localization accuracy is 26.4 centimeters, an improvement of 11.1% to 86.1% in average localization accuracy and a reduction of 11.1% to 58.2% in average localization time compared to existing methods, such as Spotfi, Lumos, SCamF, SNOOPDOG, and Region Division. © 2023 IEEE.

关键词： Channel state information

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An landmark evaluation algorithm based on router identification and delay measurement 5th

An landmark evaluation algorithm based on router identificat...

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

作者： Ma, Te Liu, Fenlin Zhang, Fan Luo, Xiangyang State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Science and Technology Institute Zhengzhou China

ISBN: (纸本)9783030242701

City-level landmarks serve as an important foundation for achieving city-level and higher-precision IP geolocation. On the basis of the feature that router host names in network-developed areas often imply geographical location information, this paper proposes a city-level landmark evaluation algorithm based on router identification. Firstly, router host name matching rules are formulated by using plenty of network topology information obtained through probing. Secondly, the matching rules are used to extract router host names;the geographical locations corresponding to routers are queried through the established geographical location dictionary;and the nearest router that can obtain a city-level location in the probing path is reserved. Finally, candidate landmarks are evaluated based on the rule that the physical distance between network entities is less than the delay conversion distance. The experimental results show that the proposed algorithm can effectively evaluate the reliability of landmarks: among the experimental results on 8000 network landmarks in 4 cities in the United states, compared with the typical database query-based landmark obtaining, the city-level accuracy rates of landmarks are increased by 4.4%, 6.85%, 4.35% and 7.05% respectively. © Springer Nature Switzerland AG 2019.

关键词： Location

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Identification of global histogram equalization by modeling gray-level cumulative distribution

Identification of global histogram equalization by modeling ...

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2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013

作者： Yuan, Hai-Dong Zhengzhou Information Science and Technology Institute State Key Laboratory of Mathematical Engineering and Advanced Computing China

ISBN: (纸本)9781479910434

Previous studies have shown how to 'fingerprint' certain image processing operation. In this paper, we model the gray-level cumulative distribution of histogram-equalized image as discrete identity function, which is an intrinsic fingerprint produced by global histogram equalization processing. This model is shown to match well with the observed gray-level cumulative distribution. Based on the new model, a classification method is proposed for identifying the use of global histogram equalization processing. In comparison to previous arts, the proposed method can accurately distinguish global histogram equalization from other kinds of contrast enhancement techniques. The effectiveness of the proposed method is exhaustively evaluated in the context of histogram-equalized image identification and resistance against attacks. © 2013 IEEE.

关键词： Image processing

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A Non-Stop Double Buffering Mechanism for Dataflow Architecture

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Journal of Computer Science & Technology 2018年第1期33卷 145-157页

作者： Xu Tan Xiao-Wei Shen Xiao-Chun Ye Da Wang Dong-Rui Fan Lunkai Zhang Wen-Ming Li Zhi-Min Zhang Zhi-Min Tang State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing 100049 China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214125 China Department of Computer Science The University of Chicago Chicago IL 60637 U.S.A.

Double buffering is an effective mechanism to hide the latency of data transfers between on-chip and off-chip memory. However, in dataflow architecture, the swapping of two buffers during the execution of many tiles decreases the performance because of repetitive filling and draining of the dataflow accelerator. In this work, we propose a non-stop double buffering mechanism for dataflow architecture. The proposed non-stop mechanism assigns tiles to the processing element array without stopping the execution of processing elements through optimizing control logic in dataflow architecture. Moreover, we propose a work-flow program to cooperate with the non-stop double buffering mechanism. After optimizations both on control logic and on work-flow program, the filling and draining of the array needs to be done only once across the execution of all tiles belonging to the same dataflow graph. Experimental results show that the proposed double buffering mechanism for dataftow architecture achieves a 16.2% average efficiency improvement over that without the optimization.

关键词： non-stop double buffering dataflow architecture high-performance computing

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A parallel target-directed analysis method for malware behaviors

A parallel target-directed analysis method for malware behav...

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International Conference on Cyberspace Technology, CCT 2014

作者： Qin, Yanfeng Wang, Qingxian Zeng, Yongjun Xi, Qi State Key Laboratory of Mathematical Engineering and Advanced Computing China Luoyang University of Foreign Languages China

ISBN: (纸本)9781849199285

To improve the efficiency of analyzing malware behaviors and increase the validity of the test data, this paper proposes a parallel target-directed analysis method for malware behaviors, which combines static analysis with concolic testing techniques. It first uses static analysis techniques to identify and locate those interactive or input points and sensitive behavior functions. Then based on the distributed platform, by combining symbolic execution and concrete dynamic execution together and taking malware sensitive behaviors as the leading target, the parallel target-directed algorithm of searching sensitive paths and the method of leading and approaching sensitive behaviors are designed. It leads to traverse the sensitive functions, obtain the sensitive paths which can reach the sensitive behavior areas by path backtracking, and generate the corresponding test data. Finally, it finishes the analysis and test of malware behaviors. Experiments show that, compared with fuzz and full paths covering and traversing technique, this method can generate test data more efficiently, reduce the number of paths to be analyzed, and improve the analysis speed and efficiency of malware behaviors.

关键词： Malware

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Interest Points Analysis for Internet Forum Based on Long-Short Windows Similarity

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Computers, Materials & Continua 2022年第8期72卷 3247-3267页

作者： Xinghai Ju Jicang Lu Xiangyang Luo Gang Zhou Shiyu Wang Shunhang Li Yang Yang State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001China School of Computing and Information Systems Singapore Management University188065Singapore College of Computer Science and Big Data Fuzhou UniversityFuzhou350116China

For Internet forum Points of Interest(PoI),existing analysis methods are usually lack of usability analysis under different conditions and ignore the long-term variation,which lead to blindness in method *** address this problem,this paper proposed a PoI variation prediction framework based on similarity analysis between long and short *** on the framework,this paper presented 5 PoI analysis algorithms which can be categorized into 2 types,i.e.,the traditional sequence analysis methods such as autoregressive integrated moving average model(ARIMA),support vector regressor(SVR),and the deep learning methods such as convolutional neural network(CNN),long-short term memory network(LSTM),Transformer(TRM).Specifically,this paper firstly divides observed data into long and short windows,and extracts key words as PoI of each ***,the PoI similarities between long and short windows are calculated for training and ***,series of experiments is conducted based on real Internet forum *** results show that,all the 5 algorithms could predict PoI variations well,which indicate effectiveness of the proposed *** the length of long window is small,traditional methods perform better,and SVR is the *** the contrary,the deep learning methods show superiority,and LSTM performs *** results could provide beneficial references for PoI variation analysis and prediction algorithms selection under different parameter configurations.

关键词： Point of interest(PoI)analysis long and short windows sequential analysis deep learning

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Lattice QCD determination of unpolarized TMDPDFs of the nucleon 10

Lattice QCD determination of unpolarized TMDPDFs of the nucl...

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10th International Conference on Quarks and Nuclear Physics, QNP 2024

作者： Zhang, Qi-An He, Jin-Chen Chu, Min-Huan Hua, Jun Ji, Xiangdong Schäfer, Andreas Su, Yushan Wang, Wei Yang, Yi-Bo Zhang, Jian-Hui School of Physics Beihang University Beijing102206 China Yang Yuanqing Scientific Computering Center Tsung-Dao Lee Institute Shanghai Jiao Tong University Shanghai200240 China School of Physics and Astronomy Shanghai Jiao Tong University Shanghai200240 China Department of Physics University of Maryland College ParkMD20742 United States Guangdong Provincial Key Laboratory of Nuclear Science Institute of Quantum Matter South China Normal University Guangzhou510006 China Guangdong-Hong Kong Joint Laboratory of Quantum Matter Southern Nuclear Science Computing Center South China Normal University Guangzhou510006 China Institut für Theoretische Physik Universität Regensburg RegensburgD-93040 Germany Institute of Modern Physics Chinese Academy of Sciences Guangdong Province Huizhou516000 China CAS Key Laboratory of Theoretical Physics Institute of Theoretical Physics Chinese Academy of Sciences Beijing100190 China School of Fundamental Physics and Mathematical Sciences Hangzhou Institute for Advanced Study UCAS Hangzhou310024 China International Centre for Theoretical Physics Asia-Pacific Beijing China School of Physical Sciences University of Chinese Academy of Sciences Beijing100049 China School of Science and Engineering The Chinese University of HongKong Shenzhen518172 China Center of Advanced Quantum Studies Department of Physics Beijing Normal University Beijing100875 China

We present a first calculation of the unpolarized nucleon’s isovector transverse-momentum-dependent parton distribution functions (TMDPDFs) from lattice QCD, which are essential to predict observables of multi-scale, semi-inclusive processes in the standard model. We use a Nf = 2 + 1 + 1 MILC ensemble with valence clover fermions on a highly improved staggered quark (HISQ) sea to compute the quark momentum distributions in a large-momentum nucleon on the lattice. The state-of-the-art techniques in renormalization and extrapolation in the correlation distance on the lattice are adopted. The perturbative kernel up to next-to-next-to-leading order is taken into account, and the dependence on the pion mass and the hadron momentum is explored. Our results are qualitatively comparable with phenomenological TMDPDFs, which provide an opportunity to predict high energy scatterings from first principles. © Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0).

关键词： Crystal lattices

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Delay-Distance Correlation Study for IP Geolocation

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Wuhan University Journal of Natural Sciences 2017年第2期22卷 157-164页

作者： DING Shichang LUO Xiangyang YE Dengpan LIU Fenlin The State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450001 Henan China School of Computer Wuhan University Wuhan 430072Hubei China

Although many classical IP geolocation algorithms are suitable to rich-connected networks, their performances are seriously affected in poor-connected networks with weak delay-distance correlation. This paper tries to improve the performances of classical IP geolocation algorithms by finding rich-connected sub-networks inside poor-connected networks. First, a new delay-distance correlation model （RTD-Corr model） is proposed. It builds the relationship between delay-distance correlation and actual network factors such as the tortuosity of the network path and the ratio of propagation delay. Second, based on the RTD-Corr model and actual network characteristics, this paper discusses about how to find rich-connected networks inside China Intemet which is a typical actual poor-connected network. Then we find rich-connected sub-networks of China Intemet through a large-scale network measurement which covers three major ISPs and thirty provinces. At last, based on the founded rich-connected sub-networks, we modify two classical IP geolocation algorithms and the experiments in China Intemet show that their accuracy is significantly increased.

关键词： IP geolocation delay-distance correlation network security network measurement rich-connected sub-networks

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Integrating a weighted-average method into the random walk framework to generate individual friend recommendations

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Science China(Information Sciences) 2017年第11期60卷 43-64页

作者： Jibing GONG Xiaoxia GAO Hong CHENG Jihui LIU Yanqing SONG Mantang ZHANG Yi ZHAO School of Information Science and Engineering Yanshan University The Key Lab for Computer Virtual Technology and System Integration Yanshan University State Key Lab of Mathematical Engineering and Advanced Computing Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong

Friend recommendation is a fundamental service in both social networks and practical applications,and is influenced by user behaviors such as interactions, interests, and activities. In this study, we first conduct in-depth investigations on factors that affect recommendation results. Next, we design Friend++, a hybrid multi-individual recommendation model that integrates a weighted average method(WAM) into the random walk(RW) framework by seamlessly employing social ties, behavior context, and personal information. In Friend++, the first plus signifies recommending a new friend through network features, while the second plus stands for using node features. To verify our method, we conduct experiments on three social datasets crawled from the Sina microblog system(Weibo). Experimental results show that the proposed method significantly outperforms six baseline methods in terms of recall, precision, F1-measure, and MAP. As a final step, we describe a case study that demonstrates the scalability and universality of our method. Through discussion, we reach a meaningful conclusion: although common interests are more important than user activities in making recommendations, user interactions may be the most important factor in finding the most appropriate potential friends.

关键词： multi-individual friend recommendation architecture behavior context analysis Intimacy degree random walk framework social networks

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Graph Neural Network Enabled Fluid Antenna Systems: A Two-Stage Approach

arXiv

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arXiv 2025年

作者： He, Changpeng Lu, Yang Chen, Wei Ai, Bo Wong, Kai-Kit Niyato, Dusit State Key Laboratory of Advanced Rail Autonomous Operation China School of Computer Science and Technology Beijing Jiaotong University Beijing100044 China School of Electronics and Information Engineering Beijing Jiaotong University Beijing100044 China Department of Electronic and Electrical Engineering University College London LondonWC1E 6BT United Kingdom Yonsei Frontier Laboratory The School of Integrated Technology Yonsei University Seoul03722 Korea Republic of College of Computing and Data Science Nanyang Technological University Singapore639798 Singapore

An emerging fluid antenna system (FAS) brings a new dimension, i.e., the antenna positions, to deal with the deep fading, but simultaneously introduces challenges related to the transmit design. This paper proposes an "unsupervised learning to optimize" paradigm to optimize the FAS. Particularly, we formulate the sum-rate and energy efficiency (EE) maximization problems for a multiple-user multiple-input single-output (MU-MISO) FAS and solved by a two-stage graph neural network (GNN) where the first stage and the second stage are for the inference of antenna positions and beamforming vectors, respectively. The outputs of the two stages are jointly input into a unsupervised loss function to train the two-stage GNN. The numerical results demonstrates that the advantages of the FAS for performance improvement and the two-stage GNN for real-time and scalable optimization. Besides, the two stages can function separately. © 2025, CC BY.

关键词： Graph neural networks

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