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arXiv 2019年

作者： Liu, Xu Di, Xiaoqiang Li, Jinqing Wang, Huan Zhao, Jianping Yang, Huamin Cong, Ligang Jiang, Yuming School of Computer Science and Technology Changchun University of Science and Technology Changchun China Jilin Province Key Laboratory of Network and Information Security Changchun China Department of Information Security and Communication Technology Norwegian University of Science and Technology Trondheim Norway

Resource allocation is the process of optimizing the rare resources. In the area of security, how to allocate limited resources to protect a massive number of targets is especially challenging. This paper addresses this resource allocation issue by constructing a game theoretic model. A defender and an attacker are players and the interaction is formulated as a tradeoff between protecting targets and consuming resources. The action cost which is a necessary role of consuming resource, is considered in the proposed model. Additionally, a bounded rational behavior model (Quantal Response, QR), which simulates a human attacker of the adversarial nature, is introduced to improve the proposed model. To validate the proposed model, we compare the different utility functions and resource allocation strategies. The comparison results suggest that the proposed resource allocation strategy performs better than others in the perspective of utility and resource effectiveness. Copyright © 2019, The Authors. All rights reserved.

关键词： Resource allocation

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Deep Reinforcement Learning Based Intelligent Reflecting Surface for Secure Wireless communications

arXiv

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arXiv 2020年

作者： Yang, Helin Xiong, Zehui Zhao, Jun Niyato, Dusit Xiao, Liang Wu, Qingqing School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore Department of Information and Communication Engineering Key Laboratory of Digital Fujian on IoT Communication Architecture and Security Technology Xiamen University Xiamen361005 China Department of Electrical and Computer Engineering National University of Singapore Singapore119260 Singapore

In this paper, we study an intelligent reflecting surface (IRS)-aided wireless secure communication system for physical layer security, where an IRS is deployed to adjust its reflecting elements to secure the communication of multiple legitimate users in the presence of multiple eavesdroppers. Aiming to improve the system secrecy rate, a design problem for jointly optimizing the base station (BS)’s beamforming and the IRS’s reflecting beamforming is formulated considering different quality of service (QoS) requirements and time-varying channel conditions. As the system is highly dynamic and complex, and it is challenging to address the non-convex optimization problem, a novel deep reinforcement learning (DRL)-based secure beamforming approach is firstly proposed to achieve the optimal beamforming policy against eavesdroppers in dynamic environments. Furthermore, post-decision state (PDS) and prioritized experience replay (PER) schemes are utilized to enhance the learning efficiency and secrecy performance. Specifically, PDS is capable of tracing the environment dynamic characteristics and adjust the beamforming policy accordingly. Simulation results demonstrate that the proposed deep PDS-PER learning based secure beamforming approach can significantly improve the system secrecy rate and QoS satisfaction probability in IRS-aided secure communication systems. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep learning

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Joint object contour points and semantics for instance segmentation

arXiv

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arXiv 2020年

作者： Zhang, Wenchao Fu, Chong Zhu, Mai Cao, Lin Tie, Ming Sham, Chiu-Wing School of Computer Science and Engineering Northeastern University Shenyang110819 China Engineering Research Center of Security Technology of Complex Network System Ministry of Education China Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Northeastern University Shenyang110819 China School of Information and Communication Engineering Beijing Information Science and Technology University Beijing100101 China Science and Technology on Space Physics Laboratory Beijing100076 China School of Computer Science University of Auckland New Zealand

The attributes of object contours has great significance for instance segmentation task. However, most of the current popular deep neural networks do not pay much attention to the object edge information. Inspired by the human annotation process when making instance segmentation datasets, in this paper, we propose Mask Point R-CNN aiming at promoting the neural network’s attention to the object boundary. Specifically, we innovatively extend the original human keypoint detection task to the contour point detection of any object. Based on this analogy, we present an contour point detection auxiliary task to Mask R-CNN, which can boost the gradient flow between different tasks by effectively using feature fusion strategies and multi-task joint training. As a consequence, the model will be more sensitive to the edges of the object and can capture more geometric features. Quantitatively, the experimental results show that our approach outperforms vanilla Mask R-CNN by 3.8% on Cityscapes dataset and 0.8% on COCO dataset. Copyright © 2020, The Authors. All rights reserved.

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BotCapturer: Detecting botnets based on two-layered analysis with graph anomaly detection and network traffic clustering

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International Journal of Performability Engineering 2018年第5期14卷 1050-1059页

作者： Wang, Wei Wang, Yang Tan, Xinlu Liu, Ya Yang, Shuangmao Beijing Key Laboratory of Security and Privacy in Intelligent Transportation Beijing Jiaotong University Beijing100044 China Science and Technology on Electronic Information Control Laboratory Chengdu610036 China

Botnets have become one of the most serious threats on the Internet. On the platform of botnets, attackers conduct series of malicious activities such as distributed denial-of-service (DDoS) or virtual currencies mining. Network traffic has been widely used as the data source for the detection of botnets. However, there are two main issues on the detection of botnets with network traffic. First, many traditional filtering methods such as whitelisting are not able to process the very large amount of traffic data in real-time due to their limited computational capability. Second, many existing detection methods, based on network traffic clustering, result in high false positive rates. In this work, we are motivated to resolve the above two issues by proposing a lightweight botnet detection system called BotCapturer, based on two-layered analysis with anomaly detection in graph and network communication traffic clustering. First, we identify anomalous nodes that correspond to C&C (control and Command) servers with anomaly scores in a graph abstracted from the network traffic. Second, we take advantage of clustering algorithms to check whether the nodes interacting with an anomalous node share similar communication pattern. In order to minimize irrelevant traffic, we propose a traffic reduction method to reduce more than 85% background traffic. The reduction is conducted by filtering the packets that are unrelated to the hosts like C&C server. We collect a very big dataset by simulating five different botnets and mixing the collected traffic with background traffic obtained from ISP. Extensive experiments are conducted and evaluation results based on our own dataset show that BotCapturer reduces more than 85% input raw packet traces and achieves a high detection rate (100%) with a low false positive rate (0.01%), demonstrating that it is very effective and efficient in detecting latest botnets. © 2018 Totem Publisher, Inc. All rights reserved.

关键词： Intrusion detection

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Measurement and analysis of motor-noise in underwater glider

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IOP Conference Series: Earth and Environmental science 2021年第1期725卷

作者： Qing Zhou Yihao Zhao Maofa Wang Science and Technology on Communication Information Security Control Laboratory Jiaxing 314033 China No.36 Research Institute of CETC Jiaxing 314033 China Ocean Engineering Research Center Hangzhou Dianzi University Hangzhou 310018 China

Self-noise is a very disadvantageous factor for underwater glider to observe ocean ambient noise, in which the noise caused by motor is very significant. In order to grasp the characteristics of the motor-noise and its influence on the measurement of ocean ambient noise, a long-term sea trial was conducted in the South China Sea in May 2020, and the self-noise data of underwater glider under different working conditions are obtained. By analyzing the noise level and spectrum level of the motor noise, we obtained the self-noise spectrum characteristics and know that the influence of control motor noise on the noise measurement of head and tail hydrophone is mainly below 5 kHz band, and the influence of full-frequency noise level brought by motor is within 10dB and 5dB respectively. The results lay an important foundation for further analysis of ocean ambient noise measured by underwater glider.

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Asymmetric parametric generation of images with nonlinear dielectric metasurfaces

arXiv

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arXiv 2021年

作者： Kruk, Sergey S. Wang, Lei Sain, Basudeb Dong, Zhaogang Yang, Joel Zentgraf, Thomas Kivshar, Yuri Department of Physics Paderborn University Paderborn33098 Germany Nonlinear Physics Center Research School of Physics Australian National University CanberraACT2601 Australia National Mobile Communications Research Laboratory Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing210096 China Purple Mountain Laboratories Nanjing211111 China Singapore138634 Singapore Singapore University of Technology and Design Singapore487372 Singapore

Subwavelength dielectric resonators assembled into metasurfaces have become a versatile tool for miniaturising optical components approaching the nanoscale1-3. An important class of metasurface functionalities is associated with asymmetry in both generation and transmission of light with respect to reversals of the positions of emitters and receivers4-6. Nonlinear light-matter interaction in metasurfaces7-9 offers a promising pathway towards miniaturisation of the asymmetric control of light. Here we demonstrate asymmetric parametric generation of light in nonlinear metasurfaces. We assemble dissimilar nonlinear dielectric resonators into translucent metasurfaces that produce images in the visible spectral range being illuminated by infrared radiation. By design, the metasurfaces produce different and completely independent images for the reversed direction of illumination, that is when the positions of the infrared emitter and the visible light receiver are exchanged. Nonlinearity-enabled asymmetric control of light by subwavelength resonators paves the way towards novel nanophotonic components via dense integration of large quantities of nonlinear resonators into compact metasurface designs. © 2021, CC BY.

关键词： Infrared radiation

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Research on performance analysis and optimization methods of bistatic collaborative detection 13

Research on performance analysis and optimization methods of...

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13th ACM International Conference on Underwater Networks and Systems, WUWNet 2018

作者： Guo, Longxiang Zhou, Qing Liu, Ting Zou, Jiayun Sheng, Xueli Science and Technology on Communication Information Security Control Laboratory JiaxingZhejiang China College of Underwater Acoustic Engineering Acoustic Science and Technology Laboratory Harbin Engineering University HarbinHeilongjiang China

ISBN: (纸本)9781450361934

Compared with the monostatic sonar system, the bistatic sonar system has numerous advantages, such as being quick and flexible to deploy, utilizing strong concealment, and having a large detection range. The detection performance analysis system, which consists of the sound source and propagation loss level, the interfering noise level, the marine reverberation average strength level, and the target echo sound level, was established in this study. Aiming at a specified area, this study realizes a performance analysis based on the detection probabilities of targets in different locations. In terms of detection performance, the bistatic sonar system especially faces considerable direct wave interference. Therefore, a method for restraining direct wave interference based on zero constraint beam-forming was developed. This method can mitigate the both narrow-band and broadband direct wave interference problems. Another method based on space timeadaptive processingwas also developed. This method can also solve direct wave interference problem. Using the above performance analysis system, considering the influence of strong direct wave interference, the detection range can increase 35% by using the zero constraint beam-forming method, thus further enhancing the detection performance. © 2018 Association for Computing Machinery.

关键词： Sonar

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Wireless communication Signal Strength Prediction Method Based on the K-nearest Neighbor Algorithm

Wireless Communication Signal Strength Prediction Method Bas...

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2019国际计算机前沿大会

作者： Zhao Chen Ning Xiong Yujue Wang Yong Ding Hengkui Xiang Chenjun Tang Lingang Liu Xiuqing Zou Decun Luo Key Lab on Cognitive Radio and Information Processing School of Information and CommunicationGuilin University of Electronic Technology Guangxi Key Laboratory of Cryptography and Information Security School of Computer Science and Information SecurityGuilin University of Electronic Technology

Existing interference protection systems lack automatic evaluation methods to provide scientific,objective and accurate assessment *** address this issue,this paper develops a layout scheme by geometrically modeling the actual scene,so that the hand-held full-band spectrum analyzer would be able to collect signal field strength values for indoor complex *** improved prediction algorithm based on the K-nearest neighbor non-parametric kernel regression was proposed to predict the signal field strengths for the whole plane before and after being *** the highest accuracy set of data could be picked out by *** experimental results show that the improved prediction algorithm based on the K-nearest neighbor non-parametric kernel regression can scientifically and objectively predict the indoor complex scenes' signal strength and evaluate the interference protection with high accuracy.

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Using Reduced Graphene Oxide to Generate Q-Switched Pulses in Er-Doped Fiber Laser

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Chinese Physics Letters 2018年第11期35卷 32-34页

作者： Lu Li Rui-Dong Lv Si-Cong Liu Zhen-Dong Chen Jiang Wang Yong-Gang Wang Wei Ren School of Science Xi＇an University of Posts and TelecommunicationsXi＇an 710121 School of Physics and information Technology Shaanxi Normal UniversityXi＇an 710119 Shaanxi Key Laboratory of Information Communication Network and Security Xi＇an University of Posts and TelecommunicationsXi＇an 710121

Using the reduced graphene oxide（rGO） as a saturable absorber（SA） in an Er-doped fiber（EDF） laser cavity,we obtain the Q-switching operation. The rGO SA is prepared by depositing the GO on fluorine mica（FM） using the thermal reduction method. The modulation depth of rGO/FM is measured to be 3.2%. By incorporating the rGO/FM film into the EDF laser cavity, we obtain stable Q-switched pulses. The shortest pulse duration is3.53 μs, and the maximum single pulse energy is 48.19 nJ. The long-term stability of working is well *** experimental results show that the rGO possesses potential photonics applications.

关键词： EDF GO Using Reduced Graphene Oxide to Generate Q-Switched Pulses in Er-Doped Fiber Laser SA

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A Dynamic Time Warping Based Wake-Up Signal Detection Method for Underwater Acoustic communication Networks 2

A Dynamic Time Warping Based Wake-Up Signal Detection Method...

引用

2nd IEEE Advanced information Management, Communicates, Electronic and Automation control Conference, IMCEC 2018

作者： Ma, Lu Fan, Cheng Sun, Wei Qiao, Gang Science and Technology on Communication Information Security Control Laboratory Jiaxing Zhejiang China College of Underwater Acoustic Engineering Harbin Engineering University Harbin China

ISBN: (纸本)9781538618035

T400 conventional underwater acoustic (UWA) wakeup signals detection methods for both underwater cooperative nodes and non-cooperative nodes are FFT based signal detection and matched-filtered based signal detection. While there is a big performance degradation of these conventional frequency-offset sensitive methods due to the relative motion between nodes, complex underwater noise environment, channel time-varying and other interference sources. This paper proposes a dynamic time warping (DTW) algorithm to detect the wake-up signal in UWA communication networks, which is frequency-offset insensitive and performs better than the conventional methods in severe frequency-offset environment by simulations based on the true UWA channel measured from sea trial. © 2018 IEEE.

关键词： Signal detection

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