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AsIDPS: Auto-Scaling Intrusion Detection and Prevention System for Cloud

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AsIDPS: Auto-Scaling Intrusion Detection and Prevention Syst...

International Conference on Telecommunications (ICT)

作者： Junchi Xing Haifeng Zhou Jinfan Shen Kai Zhu Yansong Wangt Chunming Wu Wei Ruan College of Computer Science and Technology Zhejiang University ZTE Corporation College of Control Science and Engineering

Distributed Denial-of-Service (DDoS) attack has been a “nightmare” for cloud. A countermeasure is to establish an Intrusion Detection and Prevention System (IDPS) for cloud. Nevertheless, current IDPSes fail to achieve the detection and prevention in a flexible and lightweight way. In this paper, we propose a novel scheme of IDPS for overcoming the above problem, termed as Auto-scaling IDPS (AsIDPS). AsIDPS is based on Software-Defined Networking (SDN) and Docker container technologies. It first detects abnormal traffic based on the flow statistics collected in SDN switches in real-time. By the SDN controller, the abnormal traffic will be directed to the created Docker containers with Snort running on them for further detection and clean-up. Particularly, the Docker containers can be automatically scaled out or scaled down on demand. The Snort will also deliver an alert to the SDN controller if it detects attack traffic so as to perform a countermeasure if necessary. Benefitting from the flexible network management offered by SDN and the lightweight Docker container, AsIDPS is able to build a flexible and lightweight defense against DDoS attack in cloud. Based on our prototype implementation, we validate the effectiveness of AsIDPS in defending DDoS attack, and also verify its flexibility and lightweight.

关键词： Cloud computing Containers computer crime control systems Real-time systems IP networks

Edge-Enhanced Dual Discriminator Generative Adversarial Network for Fast MRI with Parallel Imaging Using Multi-view Information

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arXiv 2021年

作者： Huang, Jiahao Ding, Weiping Lv, Jun Yang, Jingwen Dong, Hao Del Ser, Javier Xia, Jun Ren, Tiaojuan Wong, Stephen T. Yang, Guang College of Information Science and Technology Zhejiang Shuren University Hangzhou310015 China National Heart and Lung Institute Imperial College London London United Kingdom School of Information Science and Technology Nantong University Nantong226019 China School of Computer and Control Engineering Yantai University Yantai264005 China Department of Prosthodontics Peking University School Hospital of Stomatology Beijing China Center on Frontiers of Computing Studies Peking University Beijing China Derio48160 Spain Bilbao48013 Spain Department of Radiology Shenzhen Second People’s Hospital The First Affiliated Hospital of Shenzhen University Health Science Center Shenzhen China Systems Medicine and Bioengineering Department Houston Methodist Cancer Center HoustonTX77030 United States Department of Radiology Houston Methodist Hospital Weill Cornell Medicine HoustonTX77030 United States Cardiovascular Research Centre Royal Brompton Hospital London United Kingdom

In clinical medicine, magnetic resonance imaging (MRI) is one of the most important tools for diagnosis, triage, prognosis, and treatment planning. However, MRI suffers from an inherent slow data acquisition process because data is collected sequentially in k-space. In recent years, most MRI reconstruction methods proposed in the literature focus on holistic image reconstruction rather than enhancing the edge information. This work steps aside this general trend by elaborating on the enhancement of edge information. Specifically, we introduce a novel parallel imaging coupled dual discriminator generative adversarial network (PIDD-GAN) for fast multi-channel MRI reconstruction by incorporating multi-view information. The dual discriminator design aims to improve the edge information in MRI reconstruction. One discriminator is used for holistic image reconstruction, whereas the other one is responsible for enhancing edge information. An improved U-Net with local and global residual learning is proposed for the generator. Frequency channel attention blocks (FCA Blocks) are embedded in the generator for incorporating attention mechanisms. Content loss is introduced to train the generator for better reconstruction quality. We performed comprehensive experiments on Calgary-Campinas public brain MR dataset and compared our method with state-of-the-art MRI reconstruction methods. Ablation studies of residual learning were conducted on the MICCAI13 dataset to validate the proposed modules. Results show that our PIDD-GAN provides high-quality reconstructed MR images, with well-preserved edge information. The time of single-image reconstruction is below 5ms, which meets the demand of faster processing. © 2021, CC BY-NC-ND.

关键词： Generative adversarial networks

Petri Net control Method for Pipe-line Systems and Its Implementation via CIF3 ⁎

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IFAC-PapersOnLine 2019年第24期52卷 261-266页

作者： YuHao Fu JiLiang Luo Huifeng Wu Jianhong Ye Yi-sheng Huang College Information Science and Engineering Huaqiao University Xiamen 361021 China College Information Science and Engineering Huaqiao University Xiamen 361021 China and also with Fujian Engineering Research Center of Motor Control and System Optimal Schedule Xiamen 361021 China Institute of Intelligent and Software Technology Hangzhou Dianzi University Hangzhou 310018 China Computer Science and Technology Huaqiao University Xiamen 361021 China and also with Fujian Provincial Key Laboratory of Data Intensive Computing Quanzhou 362000 China Department of Electrical Engineering National Ilan University Taiwan

As for a pipe-line system subjected to complex operations, an approach is proposed to synthesize the controller via Petri nets (PNs) such that the plant is run as concurrently as possible and the loads of equipments are balanced. A P-timed and labeled PN is designed to model the whole process of a pipe-line system, where tasks, including transporting material from one tank to another and cleaning tank, are represented by operational places, and level sensors amounted in tanks are represented by labels assigned to transitions. Further, monitor places are designed to resolve the conflict relations among tasks due to the shared valves and pipes. An method is presented to translate an PN controller into a CIF3 (Compositional Interchange Format) model, which can be converted into a PLC program in the CIF3 tool. A beer filtration plant is taken as an example to illustrate the approach, and its simulation experiments are carried out to verify the theoretic results.

关键词： Chemical plant Valve control Petri net CIF3

Algebraic state space approach to model and control combined automata

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Frontiers of computer science 2017年第5期11卷 874-886页

作者： Yongyi YAN Zengqiang CHEN Jumei YUE College of Information Engineering Henan University of Science and Technology Luoyang 471023 China College of Computer and Control Engineering Nankai University Tianjin 300071 China College of Agricultural Engineering Henan University of Science and Technology Luoyang 471003 China

A new modeling tool, algebraic state space approach to logical dynamic systems, which is developed recently based on the theory of semi-tensor product of matrices （STP）, is applied to the automata field. Using the STE this paper investigates the modeling and controlling problems of combined automata constructed in the ways of parallel, serial and feedback. By representing the states, input and output symbols in vector forms, the transition and output functions are expressed as algebraic equations of the states and inputs. Based on such algebraic descriptions, the control problems of combined automata, including output control and state control, are considered, and two necessary and sufficient conditions are presented for the controllability, by which two algorithms are established to find out all the control strings that make a combined automaton go to a target state or produce a desired output. The results are quite different from existing methods and provide a new angle and means to understand and analyze the dynamics of combined automata.

关键词： automata composition controllability algebraic state space approach semi-tensor product

Background subtraction on depth videos with convolutional neural networks

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arXiv 2019年

作者： Wang, Xueying Liu, Lei Li, Guangli Dong, Xiao Zhao, Peng Feng, Xiaobing State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing100049 China College of Computer Science and Technology Jilin University ChangchunJilin130012 China

Background subtraction is a significant component of computer vision systems. It is widely used in video surveillance, object tracking, anomaly detection, etc. A new data source for background subtraction appeared as the emergence of low-cost depth sensors like Microsoft Kinect, Asus Xtion PRO, etc. In this paper, we propose a background subtraction approach on depth videos, which is based on convolutional neural networks (CNNs), called BGSNet-D (BackGround Subtraction neural Networks for Depth video). The method can be used in color unavailable scenarios like poor lighting situations, and can also be applied to combine with existing RGB background subtraction methods. A preprocessing strategy is designed to reduce the influences incurred by noise from depth sensors. The experimental results on the SBM-RGBD dataset show that the proposed method outperforms existing methods on depth data, and even reaches the performance of the methods that use RGB-D data. Copyright © 2019, The Authors. All rights reserved.

关键词： Anomaly detection

SysML Modeling Mistakes and Their Impacts on Requirements

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SysML Modeling Mistakes and Their Impacts on Requirements

IEEE International Requirements engineering Conference Workshops (REW)

作者： Mounifah Alenazi Nan Niu Juha Savolainen Department of Electrical Engineering and Computer Science University of Cincinnati USA College of Arts and Sciences University of Hafr Albatin Saudi Arabia Global Software and Control R&D Danfoss Drives A/S Denmark

ISBN: (纸本)9781728151663

The Systems Modeling Language (SysML) represents a significant and increasing segment of industrial support for building critical systems. Because modeling is a human-centric activity, mistakes are unavoidable. Although there exist several software defect classifications, little is known about the mistakes pertaining to SysML modeling and the implications of those mistakes in model-driven requirements engineering. In this paper, we report a systematic mapping through which 42 SysML modeling mistakes are identified from 19 primary studies. With an emphasis on the evidence of industrial relevance, we further uncover that, despite some mistakes hurt requirements satisfaction, others help make the requirements more complete and the specifications more precise. Our work sheds light on understanding the scope of the SysML mistakes and checking requirements fulfillment in the face of the mistakes.

关键词： Unified modeling language Modeling Software Systematics Systems Modeling Language Requirements engineering Software engineering

Mean-field transmission power control in dense networks part II - Social welfare evaluation

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arXiv 2019年

作者： Wu, Yuchi Wu, Junfeng Huang, Minyi Shi, Ling Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong College of Control Science and Engineering Zhejiang University Hangzhou310027 China School of Mathematics and Statistics Carleton University OttawaONK1S 5B6 Canada

We consider uplink power control in wireless communication when massive users compete over the channel resources. In Part I [1], we have formulated massive transmission power control contest in a mean-field game framework. In this part, our goal is to investigate whether the power-domain non-orthogonal multiple access (NOMA) protocol can regulate the non-cooperative channel access behaviors, i.e., steering the competition among the noncooperative users in a direction with improved efficiency and fairness. It is compared with the CDMA protocol, which drives each user to fiercely compete against the population, hence the efficiency of channel usage is sacrificed. The existence and uniqueness of an equilibrium strategy under CDMA and NOMA have already been characterized in Part I. In this paper, we adopt the social welfare of the population as the performance metric, which is defined as the expectation of utility over the distribution of different types of channel users. It is shown that under the corresponding equilibrium strategies, NOMA outperforms CDMA in the social welfare achieved, which is illustrated through simulation with different unit price for power consumption. Moreover, it can be observed from numerical results that NOMA can improve the fairness of the achieved data rates among different users. Copyright © 2019, The Authors. All rights reserved.

关键词： 5G mobile communication systems

The impact of generative artificial intelligence on socioeconomic inequalities and policy making

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arXiv 2023年

作者： Capraro, Valerio Lentsch, Austin Acemoglu, Daron Akgun, Selin Akhmedova, Aisel Bilancini, Ennio Bonnefon, Jean-François Brañas-Garza, Pablo Butera, Luigi Douglas, Karen M. Everett, Jim A.C. Gigerenzer, Gerd Greenhow, Christine Hashimoto, Daniel A. Holt-Lunstad, Julianne Jetten, Jolanda Johnson, Simon Kunz, Werner H. Longoni, Chiara Lunn, Pete Natale, Simone Paluch, Stefanie Rahwan, Iyad Selwyn, Neil Singh, Vivek Suri, Siddharth Sutcliffe, Jennifer Tomlinson, Joe van der Linden, Sander Van Lange, Paul A.M. Wall, Friederike Van Bavel, Jay J. Viale, Riccardo Department of Psychology University of Milan-Bicocca Italy Department of Economics MIT United States Institute Professor and Department of Economics MIT United States College of Education Michigan State University United States IMT School of Advanced Studies Lucca Italy Toulouse School of Economics France Department of Economics Loyola Andalucia University Spain Department of Economics Copenhagen Business School Denmark School of Psychology University of Kent United Kingdom Max Planck Institute for Human Development Berlin Germany Penn Computer Assisted Surgery and Outcomes Laboratory Department of Surgery Perelman School of Medicine University of Pennsylvania United States Department of Computer and Information Science School of Engineering and Applied Science University of Pennsylvania United States Department of Psychology and Neuroscience Brigham Young University United States School of Psychology University of Queensland Australia MIT Sloan School of Management United States Department of Marketing University of Massachusetts Boston United States Department of Marketing Bocconi University Italy Economic & Social Research Institute Dublin Ireland Department of Humanities University of Turin Italy Department of Service and Technology Marketing Aarhus University Denmark Center for Humans and Machines Max Planck Institute for Human Development Berlin Germany Faculty of Education Monash University Australia Microsoft Research United States York Law School United Kingdom Department of Psychology University of Cambridge United Kingdom Department of Experimental and Applied Psychology Vrije Universiteit Amsterdam Netherlands Department of Management Control and Strategic Management University of Klagenfurt Austria Department of Psychology Center for Neural Science New York University United States Norwegian School of Economics Bergen Norway Department of Economics University of Milan-Bicocca Italy

Generative artificial intelligence has the potential to both exacerbate and ameliorate existing socioeconomic inequalities. In this article, we provide a state-of-the-art interdisciplinary overview of the potential impacts of generative AI on (mis)information and three information-intensive domains: work, education, and healthcare. Our goal is to highlight how generative AI could worsen existing inequalities while illuminating how AI may help mitigate pervasive social problems. In the information domain, generative AI can democratize content creation and access, but may dramatically expand the production and proliferation of misinformation. In the workplace, it can boost productivity and create new jobs, but the benefits will likely be distributed unevenly. In education, it offers personalized learning, but may widen the digital divide. In healthcare, it might improve diagnostics and accessibility, but could deepen pre-existing inequalities. In each section we cover a specific topic, evaluate existing research, identify critical gaps, and recommend research directions, including explicit trade-offs that complicate the derivation of a priori hypotheses. We conclude with a section highlighting the role of policymaking to maximize generative AI’s potential to reduce inequalities while mitigating its harmful effects. We discuss strengths and weaknesses of existing policy frameworks in the European Union, the United States, and the United Kingdom, observing that each fails to fully confront the socioeconomic challenges we have identified. We propose several concrete policies that could promote shared prosperity through the advancement of generative AI. This article emphasizes the need for interdisciplinary collaborations to understand and address the complex challenges of generative AI. © 2023, CC BY.

关键词： Artificial intelligence

Mean-Field transmission power control in dense networks: Part I - Characterization of the equilibrium strategy

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arXiv 2019年

We consider uplink power control in wireless communication when massive users compete over the channel resources. The CDMA protocol, as a supporting technology of 3G networks accommodating signal from different sources over the code domain, represents the orthogonal multiple access techniques. With the development of 5G wireless networks, non-orthogonal multiple access (NOMA) is introduced to improve the efficiency of channel allocation. Our goal is to investigate whether the power-domain NOMA protocol can introduce a natural fair principle when the users interact with each other in a non-cooperative manner. It is compared with the CDMA protocol, where the fierce competition among users jeopardizes the efficiency of channel usage. The whole work is split into two parts. In this paper, (i.e., Part I), we conduct analysis with a mean-field game (MFG) model, and show the existence and uniqueness of an equilibrium strategy. To determine whether NOMA is a more efficient communication protocol for uplink communication, the social welfare comparison is conducted in Part II [1]. Copyright © 2019, The Authors. All rights reserved.

关键词： 5G mobile communication systems