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Countering DNS Amplification Attacks Based on Analysis of Outgoing Traffic

Journal of Communications and Information Networks 2023年第2期8卷 111-121页

作者： Evgeny Sagatov Samara Mayhoub Andrei Sukhov prasad calyam Sevastopol State University(SevSU) Universitetskaya ul.33Sevastopol 99026Russia Samara National Research University Moskovskoe sh.34Samara 443086Russia University of Missouri-Columbia 221 Naka HallColumbia MO 65211USA

Domain name system(DNS)amplification distributed denial of service(DDoS)attacks are one of the popular types of intrusions that involve accessing DNS servers on behalf of the *** this case,the size of the response is many times greater than the size of the request,in which the source of the request is substituted for the address of the *** paper presents an original method for countering DNS amplification DDoS *** novelty of our approach lies in the analysis of outgoing traffic from the victim’s *** servers used for amplification attacks are easily detected in Internet control message protocol(ICMP)packet headers(type 3,code 3)in outgoing *** packets of this type are generated when accessing closed user datagram protocol(UDP)ports of the victim,which are randomly assigned by the Saddam attack *** prevent such attacks,we used a Linux utility and a software-defined network(SDN)module that we previously developed to protect against port *** Linux utility showed the highest efficiency of 99.8%,i.e.,only two attack packets out of a thousand reached the victim server.

关键词： DNS amplification attacks outgoing traffic analysis port scanning attack network intrusion qualification attributes

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Predicting carbon nanotube forest attributes and mechanical properties using simulated images and deep learning

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npj Computational Materials 2021年第1期7卷 1214-1224页

作者： Taher Hajilounezhad Rina Bao Kannappan Palaniappan Filiz Bunyak prasad calyam Matthew R.Maschmann Mechanical&Aerospace Engineering University of MissouriColumbiaMOUSA Electrical Engineering and Computer Science University of MissouriColumbiaMOUSA

Understanding and controlling the self-assembly of vertically oriented carbon nanotube(CNT)forests is essential for realizing their potential in myriad *** governing process–structure–property mechanisms are poorly understood,and the processing parameter space is far too vast to exhaustively explore *** overcome these limitations by using a physics-based simulation as a high-throughput virtual laboratory and image-based machine learning to relate CNT forest synthesis attributes to their mechanical *** CNTNet,our image-based deep learning classifier module trained with synthetic imagery,combinations of CNT diameter,density,and population growth rate classes were labeled with an accuracy of>91%.The CNTNet regression module predicted CNT forest stiffness and buckling load properties with a lower root-mean-square error than that of a regression predictor based on CNT physical *** results demonstrate that image-based machine learning trained using only simulated imagery can distinguish subtle CNT forest morphological features to predict physical material properties with high *** paves the way to incorporate scanning electron microscope imagery for high-throughput material discovery.

关键词： carbon properties overcome

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Human-Centric Composite-Quality Modeling and Assessment for Virtual Desktop Clouds

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ZTE Communications 2013年第1期11卷 27-36页

作者： Yingxiao Xu prasad calyam David Welling Saravanan Mohan Alex Berryman Rajiv Ramnath Fudan University University of Missouri MO 65201USA Ohio Supercomputer Center/OARnet OH 43212USA The Ohio State University OH 43210USA

There are several motivations, such as mobility, cost, and secu- rity, that are behind the trend of traditional desktop users transi- tioning to thin-client-based virtual desktop clouds （VDCs）. Such a trend has led to the rising importance of human-centric performance modeling and assessment within user communities that are increasingly making use of desktop virtualization. In this paper, we present a novel reference architecture and its eas- ily deployable implementation for modeling and assessing objec- tive user quality of experience （QoE） in VDCs. This architec- ture eliminates the need for expensive, time-consuming subjec- tive testing and incorporates finite-state machine representa- tions for user workload generation. It also incorporates slow-mo- tion benchmarking with deep-packet inspection of application task performance affected by QoS variations. In this way, a ＂composite-quality＂ metric model of user QoE can be derived. We show how this metric can be customized to a particular user group profile with different application sets and can be used to a） identify dominant performance indicators and troubleshoot bottlenecks and b） obtain both absolute and relative objective user QoE measurements needed for pertinent selection of thin-client encoding configurations in VDCs. We validate our composite-quality modeling and assessment methodology by us- ing subjective and objective user QoE measurements in a re- al-world VDC called VDPilot, which uses RDP and PCoIP thin-client protocols. In our case study, actual users are pres- ent in virtual classrooms within a regional federated university system.

关键词： virtual desktops quality modeling and assessment performancebenchmarking thin-client protocol adaptation objective QoEmetrics

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