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arXiv 2021年

作者： Li, Dongyang Yang, Lin Zhang, Hongguang Wang, Xiaolei Ma, Linru Xiao, Junchao College of Command Information System Army Engineering University of PLA Nanjing211101 China National Key Laboratory of Science and Technology on Information System Security Institute of System Engineering Academy of Military Sciences PLA Beijing100039 China

Insider threat detection has been a challenging task over decades, existing approaches generally employ the traditional generative unsupervised learning methods to produce normal user behavior model and detect significant deviations as anomalies. However, such approaches are insufficient in precision and computational complexity. In this paper, we propose a novel insider threat detection method, Image-based Insider Threat Detector via Geometric Transformation (IGT), which converts the unsupervised anomaly detection into supervised image classification task, and therefore the performance can be boosted via computer vision techniques. To illustrate, our IGT uses a novel image-based feature representation of user behavior by transforming audit logs into grayscale images. By applying multiple geometric transformations on these behavior grayscale images, IGT constructs a self-labelled dataset and then train a behavior classifier to detect anomaly in self-supervised manner. The motivation behind our proposed method is that images converted from normal behavior data may contain unique latent features which keep unchanged after geometric transformation, while malicious ones cannot. Experimental results on CERT dataset show IGT outperforms the classical autoencoder-based unsupervised insider threat detection approaches, and improves the instance and user based Area under the Receiver Operating Characteristic Curve (AUROC) by 4% and 2%, respectively. Copyright © 2021, The Authors. All rights reserved.

关键词： Unsupervised learning

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Survey on methods for automated measurement of the software scale

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International Journal of Performability engineering 2020年第2期16卷 255-264页

作者： Zhu, Jing Huang, Song Shi, Yaqing Chen, Mingyu Liu, Jialuo Liu, Erhu Command and Control Engineering College Army Engineering University of PLA Nanjing210007 China Training Management Department Navy Command College Nanjing210016 China 94973 Troop Hangzhou310021 China

Software scale automated measurement plays an increasingly important role in the early stage of software development. Mainstream software scale measurement methods are mainly based on function point methods, which are dependent on manpower. Therefore, software scale measurement based on automated acquisition of function points is one of the emphases of future research. In this paper, software scale measurement is discussed, and main algorithms based on the IFPUG function point method are introduced. These algorithms are compared and analyzed in order to summarize their advantages and disadvantages. Then, four steps that should be performed to automatically obtain function points are proposed, and the technical challenges of each step are pointed out. Finally, the future research direction is given. © 2020 Totem Publisher, Inc.

关键词： Software design

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Intersection Traffic Flow Counting Based on Hybrid Regression Model

Intersection Traffic Flow Counting Based on Hybrid Regressio...

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2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019

作者： Sun, Yaohang Liu, Zhen Pan, Zhisong College of Command and Control Engineering Army Engineering University Nanjing China

ISBN: (纸本)9781728123455

In this paper, we present a new method for vehicle counting using surveillance video used on the road. As the video passing through the road tends to be jammed and blocked, moving slowly and highly regularly, we propose a counting algorithm based on the regression model. We first process the surveillance video to extract features from the video. Then we use the SVM classifier to verify the vehicle density. Finally, we tested our approach using real pass-through video. Our experiments show that this method can count the flow with higher accuracy and lower computational cost. © 2019 IEEE.

关键词： Roads and streets

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QMPS: Q-learning based Message Prioritizing and Scheduling Algorithm for Flying Ad hoc Networks

QMPS: Q-learning based Message Prioritizing and Scheduling A...

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International Conference on Networking and Network Applications (NaNA)

作者： Jun Li Ming Chen Command & Control Engineering College Army Engineering University Nanjing China

ISBN: (数字)9781728189543

ISBN: (纸本)9781728189550

Flying ad hoc networks have become increasingly important in civilian applications, organized by several autonomous, small, and low-cost drones. Flying ad hoc networks often suffer from the degradation of performance or lost control of UAV node, caused by unexpected increased delay or packet loss of messages. So message scheduling is important to guarantee reliability and performance of flying ad hoc networks. We propose a novel message scheduling algorithm that provides reliable transmission of messages, named Q-learning based message prioritizing and scheduling algorithm (QMPS). First, we classify messages in the flying ad hoc network into two classes: delay-sensitive messages and delay-tolerant messages. Secondly, we design a new reward function based on the message metric and wireless link quality metric. Then, we use a Q-learning algorithm to assign different priorities to messages and then schedule them. Simulation results indicate that our proposed QMPS algorithm can improve flying ad hoc networks' performance under highly dynamic topology.

关键词： Wireless communication Schedules Scheduling algorithms Heuristic algorithms Simulation Dynamic scheduling Ad hoc networks

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Real-time 3D human action recognition based on Hyperpoint sequence

arXiv

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arXiv 2021年

作者： Li, Xing Huang, Qian Wang, Zhijian Yang, Tianjin Hou, Zhenjie Miao, Zhuang The Key Laboratory of Water Big Data Technology Ministry of Water Resources Hohai University School of Computer and Information Nanjing211100 China Changzhou University Changzhou213000 China Command and Control Engineering College Army Engineering University of PLA Nanjing210007 China

Real-time 3D human action recognition has broad industrial applications, such as surveillance, human-computer interaction, and healthcare monitoring. By relying on complex spatio-temporal local encoding, most existing point cloud sequence networks capture spatio-temporal local structures to recognize 3D human actions. To simplify the point cloud sequence modeling task, we propose a lightweight and effective point cloud sequence network referred to as SequentialPointNet for real-time 3D action recognition. Instead of capturing spatio-temporal local structures, SequentialPointNet encodes the temporal evolution of static appearances to recognize human actions. Firstly, we define a novel type of point data, Hyperpoint, to better describe the temporally changing human appearances. A theoretical foundation is provided to clarify the information equivalence property for converting point cloud sequences into Hyperpoint sequences. Secondly, the point cloud sequence modeling task is decomposed into a Hyperpoint embedding task and a Hyperpoint sequence modeling task. Specifically, for Hyperpoint embedding, the static point cloud technology is employed to convert point cloud sequences into Hyperpoint sequences, which introduces inherent frame-level parallelism;for Hyperpoint sequence modeling, a Hyperpoint-Mixer module is designed as the basic building block to learning the spatio-temporal features of human actions. Extensive experiments on three widely-used 3D action recognition datasets demonstrate that the proposed SequentialPointNet achieves competitive classification performance with up to 10X faster than existing approaches. Copyright © 2021, The Authors. All rights reserved.

关键词： Embeddings

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Design and implementation of a universal data quality management software based on data flow 10

Design and implementation of a universal data quality manage...

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

作者： Song, Jinyu Hao, Jiandong Gang, Chen Suojuan, Zhang Yiping, Guo Command and Control Engineering College Army Engineering University Nanjing China

ISBN: (纸本)9781728139173

Data quality problems are analyzed to get several typical problems, such as data missing, data duplication, data abnormality, data inconsistency and data logic error. In order to resolve these problems, a universal data quality management software is proposed. This software provides data cleaning method for each problem and evaluates the effect of these methods, and manages the plug-in components for use. The architecture and critical technologies are introduced in detail, and main steps are shown with a specific application. According to the feedback of users, this new software is powerful, adaptable, simple to use, easy to set processes, with high data cleaning efficiency and accurate effect evaluations. © 2019 IEEE.

关键词： Quality control

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A Lightweight Vulnerability Scanning and Security Enhanced System for Oracle Database 4

A Lightweight Vulnerability Scanning and Security Enhanced S...

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4th IEEE Advanced Information Technology, Electronic and Automation control Conference, IAEAC 2019

作者： Pan, Jing-Wei Min, Zhao Ping, Chen Xu, Wei-Guang Army Engineering University College of Command and Control Engineering Nanjing China

ISBN: (纸本)9781728119076

Databases store the important information of a company, and once it is leaked, it will bring immeasurable losses. Determining how to find vulnerabilities and effectively repair them were the main objectives, we design and implement a modular Oracle Vulnerability scanning and security enhanced system, which can effectively scan and repair known vulnerabilities of Oracle database. Users can customize and extend related functions for specific vulnerabilities. The experimental results showed that the system can effectively detect a variety of vulnerabilities and supplied easy to use automatic repair functions, which provided solution to the serious security problems of the Oracle database for SMEs (small to medium-sized enterprises). © 2019 IEEE.

关键词： Repair

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A Method of Colorimetric Thermometry with Auxiliary Grey-Body Materials for Rebuilding Dynamic Temperature Fields of Combustible Gases

SSRN

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SSRN 2022年

作者： Cheng, Yang-Fan Hu, Fang-Fang Zhu, Shou-Jun Li, Dan-Yi Ji, Chong Liu, Rong State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines Anhui University of Science and Technology Anhui Huainan232001 China School of Civil Engineering and Architecture Anhui University of Science and Technology Huainan232001 China School of Chemical Engineering Anhui University of Science and Technology Huainan232001 China College of Field Engineering Army Engineering University of PLA Nanjing210001 China

Traditional colorimetric thermometry is difficult to measure the temperature of combustible gases for lacking of grey-body in the burning processes. In the study, a visible burning facility for the combustible gases was designed, and the temperature characteristics were measured using an improved colorimetric pyrometer with auxiliary solid powders as the grey-body. In order to improve the temperature measurement accuracy of the system, the powder type, particle size and concentration as well as ignition delay time were studied, and these key parameters were determined as W powders, 7.9 μm, 21 g/m3 and 80 ms, respectively, after many debugging experiments. Finally, the improved colorimetric pyrometer was used to map the temperature distribution of the premixed 30% H 2 /70% air, and the results were corroborated with the thermocouple data and the previous studies. © 2022, The Authors. All rights reserved.

关键词： Color

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Influence of Weak Interlayer Thickness on Mechanical Response and Failure Behavior of Rock Under True Triaxial Stress Condition

SSRN

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SSRN 2024年

作者： Zhao, Honggang Deng, Bozhi Zhang, Dongming Li, Minghui Song, Zhenlong Chongqing Key Laboratory of Geomechanics & Geoenvironmental Protection Department of Military Installations Army Logistics Academy of PLA Chongqing401311 China State Key Laboratory of Coal Mine Disaster Dynamics and Control Chongqing University Chongqing400030 China School of Resources and Safety Engineering Chongqing University Chongqing400030 China Institute of Deep Earth Sciences and Green Energy College of Civil and Transportation Engineering Shenzhen University Shenzhen518060 China Department of Earth and Space Sciences Southern University of Science and Technology Shenzhen518055 China

In this study, we meticulously investigate the influence of weak interlayer thickness on mechanical response and failure behavior of rock in underground chamber excavation, with the aid of a true triaxial test system. We simulated the true triaxial stress condition of surrounding rocks containing weak interlayers proximate to the excavation boundary, where one face remains free, while others are subjected to loading stress and increasing tangential stress. The experimental results reveal a distinct change in the fracture morphology near the free surface as the weak interlayer thickness augments, concomitant with a gradual decrement in the fractal dimension. With the increase of the weak interlayer thickness, the failure characteristics of composite rock changes from "binary" feature to "unitary" feature, i.e. mixed tension-shear failure near the free surface and shear failure far away from the free surface changes to mixed tension-shear failure that only occurs near the free surface. Moreover, an inverse relationship is observed between the bearing capacity of the composite rock mass and the thickness of the weak interlayer. In opposition, there is an incremental trend in peak strain in the tangential stress direction, illustrating that the slip shear strain of the rock positioned above the weak interlayer chiefly governs the strain behavior of the composite rock mass in the tangential stress direction, and such strain intensifies with the enlargement of the weak interlayer. By employing the finite-discrete element method (FDEM), we replicated the failure process of the surrounding rock containing weak interlayer near the free surface of the tunnel, demonstrating considerable congruity with our physical test results. In light of the failure characteristics of the surrounding rock with the weak interlayer, we advocated for a localized area priority reinforcement support strategy, prioritizing regions with weak interlayers. Numerical simulations verified the effective

关键词： Shear strain

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HDSTF: A Hybrid Deep Spatio-Temporal Framework for Traffic Prediction

HDSTF: A Hybrid Deep Spatio-Temporal Framework for Traffic P...

引用

2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019

作者： Li, Wei Xia, Shiming Chen, Feiqiong Qiu, Junyang Liu, Xin Pan, Zhisong College of Command and Control Engineering Army Engineering University Nanjing China College of Field Engineering Army Engineering University Nanjing China

ISBN: (纸本)9781728123455

Spatiotemporal sequence forecasting (STSF) plays a significant role in many fields such as climate, traffic, economy and agriculture. Traffic prediction is a typical example of such kind of problems which requires accurate traffic results in the near future to pre-allocate vehicles timely. However, there lies two major challenges in how to model the complex relationships hidden in spatiotemporal data. On one hand, the spatial dependencies are difficult to be captured and will change as time goes by. On the other hand, the temporal relationships are periodical and diversified, which is difficult to characterize. To address these two challenges, we proposed a novel Hybrid Deep Spatio-Temporal Framework(HDSTF) to solve the traffic prediction problems. Our experiments on two real-world spatiotemporal datasets demonstrate that our proposed framework outperforms the state-of-art methods. © 2019 IEEE.

关键词： Forecasting

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