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Performance Evaluation of an Anomaly-Detection Algorithm for keystroke-Typing Based Insider Detection

Tsinghua science and technology 2018年第5期23卷 513-525页

作者： Liang He Zhixiang Li Chao Shen National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu 610041 China Ministry of Education Key Lab for Intelligent Networks and Network Security Xi'an Jiaotong University Xi'an 710004 China

keystroke dynamics is the process to identify or authenticate individuals based on their typing rhythm behaviors. Several classifications have been proposed to verify a user＇s legitimacy, and the performances of these classifications should be confirmed to identify the most promising research direction. However, classification research contains several experiments with different conditions such as datasets and methodologies. This study aims to benchmark the algorithms to the same dataset and features to equally measure all performances. Using a dataset that contains the typing rhythm of 51 subjects, we implement and evaluate 15 classifiers measured by Fl-measure, which is the harmonic mean of a false-negative identification rate and false-positive identification rate. We also develop a methodology to process the typing data. By considering a case in which the model will reject the outsider, we tested the algorithms on an open set. Additionally, we tested different parameters in random forest and k nearest neighbors classifications to achieve better results and explore the cause of their high performance. We also tested the dataset on one-class classification and explained the results of the experiment. The top-performing classifier achieves an Fl-measure rate of 92% while using the normalized typing data of 50 subjects to train and the remaining data to test. The results, along with the normalization methodology, constitute a benchmark for comparing the classifiers and measuring the performance of keystroke dynamics for insider detection.

关键词： keystroke dynamics insider identification Fl-measure normalization one-class classification

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Robust and Passive Motion Detection with COTS WiFi Devices

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Tsinghua science and technology 2017年第4期22卷 345-359页

作者： Hai Zhu Fu Xiao Lijuan Sun Xiaohui Xie Panlong Yang Ruchuan Wang the College of Computer Nanjing University of Posts and Telecommunications the Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Key Lab of Broadband Wireless Communication and Sensor Network Technology of Ministry of Education and College of Computer Nanjing University of Posts and Telecommunications the College of Computer Science and Technology University of Science and Technology of China

Device-free Passive（DfP） detection has received increasing attention for its ability to support various pervasive applications. Instead of relying on variable Received Signal Strength（RSS）, most recent studies rely on finer-grained Channel State Information（CSI）. However, existing methods have some limitations, in that they are effective only in the Line-Of-Sight（LOS） or for more than one moving individual. In this paper, we analyze the human motion effect on CSI and propose a novel scheme for Robust Passive Motion Detection（R-PMD）. Since traditional low-pass filtering has a number of limitations with respect to data denoising, we adopt a novel Principal Component Analysis（PCA）-based filtering technique to capture the representative signals of human motion and extract the variance profile as the sensitive metric for human detection. In addition, existing schemes simply aggregate CSI values over all the antennas in MIMO systems. Instead, we investigate the sensing quality of each antenna and aggregate the best combination of antennas to achieve more accurate and robust detection. The R-PMD prototype uses off-the-shelf WiFi devices and the experimental results demonstrate that R-PMD achieves an average detection rate of 96.33% with a false alarm rate of 3.67%.

关键词： device-free passive detection Received Signal Strength（RSS） channel state information MIMO

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Analysis and Measurement of the Displacement Sensor Based on an Up-tapered Mach-Zehnder Interferometer

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Chinese Physics Letters 2014年第3期31卷 65-68页

作者： WEN Xiao-Dong NING Ti-Gang YOU Hai-Dong KANG Ze-Xin LI Jing LI Chao FENG Ting YU Shao-Wei JIAN Wei Key Lab of All Optical Network and Advanced Telecommunication Network of Ministry of Education Institute of Lightwave Technology Beijing Jiaotong University Beijing 100044 Science and Information College Qingdao Agricultural University Qingdao 266109

A displacement sensor based on an up-tapered Mach–Zehnder interferometer （MZI） is proposed and demonstrated experimentally. For this purpose, a fiber MZI is fabricated by using a commercial fusion splicer. Then the transmission spectra of the sensors with different middle fiber lengths are measured by bending the MZIs with different movements of the moving stage. The maximum sensitivity of 2.457 nm/mm is achieved while the shifting of the moving stage changes from 3 mm to 3.5 mm. Note that this kind of up-taper configuration is strong in strength, easy to fabricate and low in cost.

关键词： INTERFEROMETERS RESEARCH DETECTORS OPTICAL fibers INTERFEROMETRY PHYSICS research

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Leveraging LLMs for Utility-Focused Annotation: Reducing Manual Effort for Retrieval and RAG

arXiv

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arXiv 2025年

作者： Zhang, Hengran Tang, Minghao Bi, Keping Guo, Jiafeng Liu, Shihao Shi, Daiting Yin, Dawei Cheng, Xueqi CAS Key Lab of Network Data Science and Technology ICT CAS University of Chinese Academy of Sciences Beijing China Baidu Inc Beijing China Nankai University Tianjin China

Retrieval models typically rely on costly human-labeled query-document relevance annotations for training and evaluation. To reduce this cost and leverage the potential of Large Language Models (LLMs) in relevance judgments, we aim to explore whether LLM-generated annotations can effectively replace human annotations in training retrieval models. Retrieval usually emphasizes relevance, which indicates "topic-relatedness" of a document to a query, while in RAG, the value of a document (or utility), depends on how it contributes to answer generation. Recognizing this mismatch, some researchers use LLM performance on downstream tasks with documents as labels, but this approach requires manual answers for specific tasks, leading to high costs and limited generalization. In another line of work, prompting LLMs to select useful documents as RAG references eliminates the need for human annotation and is not task-specific. If we leverage LLMs’ utility judgments to annotate retrieval data, we may retain cross-task generalization without human annotation in large-scale corpora. Therefore, we investigate utility-focused annotation via LLMs for large-scale retriever training data across both in-domain and out-of-domain settings on the retrieval and RAG tasks. To reduce the impact of low-quality positives labeled by LLMs, we design a novel loss function, i.e., Disj-InfoNCE. Our experiments reveal that: (1) Retrievers trained on utility-focused annotations significantly outperform those trained on human annotations in the out-of-domain setting on both tasks, demonstrating superior generalization capabilities. (2) LLM annotation does not replace human annotation in the in-domain setting. However, incorporating just 20% human-annotated data enables retrievers trained with utility-focused annotations to match the performance of models trained entirely with human annotations, while adding 100% human annotations further significantly enhances performance on both tasks. We hope our wor

关键词： Human engineering

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A Caching Strategy Based on Many-to-Many Matching Game in D2D networks

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Tsinghua science and technology 2021年第6期26卷 857-868页

作者： Kaihang Yu Zhonggui Ma Runyu Ni Tao Zhang School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China Key Lab of Information Network Security Ministry of Public SecurityShanghai 201204China

Wireless edge caching has been proposed to reduce data traffic congestion in backhaul links, and it is being envisioned as one of the key components of next-generation wireless networks. This paper focuses on the influences of different caching strategies in Device-to-Device(D2D) networks. We model the D2D User Equipments(DUEs) as the Gauss determinantal point process considering the repulsion between DUEs, as well as the caching replacement process as a many-to-many matching game. By analyzing existing caching placement strategies, a new caching strategy is proposed, which represents the preference list of DUEs as the ratio of content popularity to cached probability. There are two distinct features in the proposed caching strategy.(1) It can cache other contents besides high popularity contents.(2) It can improve the cache hit ratio and reduce the latency compared with three caching placement strategies: Least Recently Used(LRU), Equal Probability Random Cache(EPRC), and the Most Popular Content Cache(MPC). Meanwhile, we analyze the effect of caching on the system performance in terms of different content popularity factors and cache capacity. Simulation results show that our proposed caching strategy is superior to the three other comparison strategies and can significantly improve the cache hit ratio and reduce the latency.

关键词： caching strategy Device-to-Device(D2D)networks Gauss determinantal point process many-to-many matching game

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Modeling retail transaction data for personalized shopping recommendation 14

Modeling retail transaction data for personalized shopping r...

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23rd ACM International Conference on Information and Knowledge Management, CIKM 2014

作者： Wang, Pengfei Guo, Jiangfeng Lan, Yanyan Cheng, Xueqi Key Lab. of Network Data Science and Technology ICT Beijing China

ISBN: (纸本)9781450325981

Retail transaction data conveys rich preference information on brands and goods from customers. How to mine the transaction data to provide personalized recommendation to customers becomes a critical task for retailers. Previous recommendation methods either focus on the user-product matrix and ignore the transactions, or only use the partial information of transactions, leading to inferior performance in recommendation. Inspired by association rule mining, we introduce association pattern as a basic unit to capture the correlation between products from both intra- and intertransactions. A Probabilistic model over the Association Patterns (PAP for short) is then employed to learn the potential shopping interests and also to provide personalized recommendations. Experimental results on two real world retail data sets show that our proposed method can outperform the state-of-the-art recommendation methods. Copyright 2014 ACM.

关键词： Sales

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Flexible user-centric service selection algorithm for Internet of Things services

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Journal of China Universities of Posts and Telecommunications 2014年第SUPPL. 1期21卷 64-70页

作者： Nwe, Nwe Htay Win Bao, Jian-Min Cui, Gang School of Computer Science and Technology Harbin Institute of Technology Harbin 15001 China Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing 210003 China

In Internet of Things (IoT), the similar functional services are evolving in different quality of services (QoS) due to the widespread deployment of spatially distributed things on dynamic networks through the web. Therefore, the user involvement in service selection systems becomes a vital role to enhance the system performance by taking into account of subjective factors. This paper proposes a flexible QoS-based service selection algorithm (FQSA) which mainly targets to the users to be able to give their subjective preferences in an easy and friendly manner. The FQSA algorithm selects the services based on subjective information provided by the service consumers and objective information supported by the service providers. It adopts artificial neural network backpropagation algorithm to find the objective factors and applies similarity aggregation method to evaluate the creditability of the user subjective factors which have already been evaluated by ontological reasoning with the help of proposed QoS ontology. The comparative study and experimental results show that our FQSA algorithm is superior to other service selection approaches. © 2014 The Journal of China Universities of Posts and Telecommunications.

关键词： Neural networks

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Predicting links and their building lime: A path-based approach 30

Predicting links and their building lime: A path-based appro...

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30th AAAI Conference on Artificial Intelligence, AAAI 2016

作者： Li, Manling Jia, Yantao Wang, Yuanzhuo Zhao, Zeya Cheng, Xueqi Institute of Computing Technology Key lab of Network Data Science and Technology CAS Beijing100190 China

ISBN: (纸本)9781577357605

Predicting links and their building time in a knowledge network has been extensively studied in recent years. Most structure-based predictive methods consider structures and the time information of edges separately, which fail to characterize the correlation between them. In this paper, we propose a structure callcd the Time-Difference-labeled Path, and a link prediction method (TDLP). Experiments show that TDLP outperforms the state-of-the-art methods. Links and Building Time Prediction. © 2016, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Lime

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Trajectory Tracking of Mobile Robots Based on Model Predictive Control Using Primal Dual Neural network 33

Trajectory Tracking of Mobile Robots Based on Model Predicti...

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第三十三届中国控制会议

作者： DENG Jun LI Zhijun SU Chun-Yi The Key Lab of Autonomous System and Network Control College of Automation Science and Engineering South China University of Technology

ISBN: (纸本)9781479947249

Mobile robots' motion is constrained by the maximum velocity its actuators can provide,when it tracks a reference trajectory which imposes demanding requirements on the robot's driving *** this paper,a model predictive control(MPC) scheme is proposed for trajectory tracking control of two-wheel mobile *** on the derived tracking-error kinematics of the robot,the proposed MPC approach can be iteratively formulated as a quadratic programming(QP) problem,which can be solved using a linear variable inequality based primal-dual neural network(LVI-PDNN) over a finite receding *** applied neural networks are both stable in the sense of Lyapunov and globally convergent to the exact optimal solutions of reformulated convex programming *** smoothness of the robot motion is improved,a reasonable magnitudes of the robot velocities and a better tracking performance are *** and experimental results are provided to demonstrate the effectiveness and characteristics of the proposed LVI-PDNN based MPC approaches to trajectory tracking control.

关键词： Model Predictive Control(MPC),Quadratic Programming(QP) Problem,LVI-based Primal-dual Neural network(LVI-PDNN),Trajectory Tracking

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Development of multi-fingered dexterous hand for grasping manipulation

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science China(Information sciences) 2014年第12期57卷 76-85页

作者： LIN GuoDong LI ZhiJun LIU Lan SU Hang YE WenJun The Key Lab of Autonomous System and Network Control Ministry of EducationCollege of Automation Science and Engineering South China University of Technology School of Material Science and Engineering South China University of Technology Department of Mechanical and Industrial Engineering Concordia University

In this paper,a developed multi-fingered dexterous hand with flexible tactile skin is *** dexterous hand has 5-fingers with 6-DOFs and each finger is equipped with a small harmonic drive gear and a fine high-power mini *** achieve the goal of grasping with high accuracy,each fingertip is covered with the tactile array sensors for determination of the force between the finger and the grasped *** preliminary experiments are conducted to illustrate the performance of the grasping of the developed dexterous hand.

关键词： multi-fingered dexterous hand grasping tactile sensors

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