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Flow-based benchmark data sets for intrusion detection 16

Flow-based benchmark data sets for intrusion detection

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16th European conference on Cyber Warfare and Security, ECCWS 2017

作者： Ring, Markus Wunderlich, Sarah Grüdl, Dominik Landes, Dieter Hotho, Andreas Coburg University of Applied Sciences Germany University of Würzburg Germany

ISBN: (纸本)9781911218432

Anomaly based intrusion detection systems suffer from a lack of appropriate evaluation data sets. Often, existing data sets may not be published due to privacy concerns or do not reflect actual and current attack scenarios. In order to overcome these problems, we identify characteristics of good data sets and develop an appropriate concept for the generation of labelled flow-based data sets that satisfy these criteria. the concept is implemented based on OpenStack, thus demonstrating the suitability of virtual environments. Virtual environments offer advantages compared to static data sets by easily creating up-to-date data sets with recent trends in user behaviour and new attack scenarios. In particular, we emulate a small business environment which includes several clients and typical servers. Network traffic is generated by scripts which emulate typical user activities like surfing the web, writing emails, or printing documents on the clients. these scripts follow some guidelines to ensure that the user behaviour is as realistic as possible, also with respect to working hours and lunch breaks. the generated network traffic is recorded in unidirectional NetFlow format. For generating malicious traffic, attacks like Denial of Service, Brute Force, and Port Scans are executed within the network. Since origins, targets, and timestamps of executed attacks are known, labelling of recorded NetFlow data is easily possible. For inclusion of actual traffic, which has its origin outside the OpenStack environment, an external server with two services is deployed. this server has a public IP address and is exposed to real and up-to-date attacks from the internet. We captured approximately 32 million flows over a period of four weeks and categorized them into five classes. Further, the chronological sequence of the flows is analysed and the distribution of normal and malicious traffic is discussed in detail. the main contribution of this paper is the demonstration of a novel a

关键词： Intrusion detection

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Multi-Resolution data Fusion for Super-Resolution Electron Microscopy 30

Multi-Resolution Data Fusion for Super-Resolution Electron M...

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30th IEEE/CVF conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Sreehari, Suhas Venkatakrishnan, S. V. Bouman, Katherine L. Simmons, Jeff P. Drummy, Larry F. Bouman, Charles A. Purdue Univ W Lafayette IN 47907 USA Oak Ridge Natl Lab Oak Ridge TN 37830 USA MIT 77 Massachusetts Ave Cambridge MA 02139 USA US Air Force Res Lab Wright Patterson AFB OH 45433 USA

ISBN: (纸本)9781538607336

Perhaps surprisingly, all electron microscopy (EM) data collected to date is less than a cubic millimeter - presenting a huge demand in the materials and biological sciences to image at greater speed and lower dosage, while maintaining resolution. Traditional EM imaging based on homogeneous raster scanning severely limits the volume of high-resolution data that can be collected, and presents a fundamental limitation to understanding physical processes such as material deformation and crack propagation. We introduce a multi-resolution data fusion (MDF) method for super-resolution computational EM. Our method combines innovative data acquisition with novel algorithmic techniques to dramatically improve the resolution/volume/ speed trade-off. the key to our approach is to collect the entire sample at low resolution, while simultaneously collecting a small fraction of data at high resolution. the high-resolution measurements are then used to create a material-specific model that is used within the "plug-and-play" framework to dramatically improve resolution of the low-resolution data. We present results using FEI electron microscope data that demonstrate super-resolution factors of 4x-16x, while substantially maintaining high image quality and reducing dosage.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks signal processing algorithms

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PCA-aided Fully Convolutional Networks for Semantic Segmentation of Multi-channel fMRI 18

PCA-aided Fully Convolutional Networks for Semantic Segmenta...

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18th International conference on Advanced Robotics (ICAR)

作者： Tai, Lei Ye, Haoyang Ye, Qiong Liu, Ming City Univ Hong Kong MBE Hong Kong Hong Kong Peoples R China Wenzhou Med Univ Affiliated Hosp 1 Dept Radiol Wenzhou Zhejiang Peoples R China Hong Kong Univ Sci & Technol Dept ECE Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9781538631577

Semantic segmentation of functional magnetic resonance imaging (fMRI) makes great sense for pathology diagnosis and decision system of medical robots. the multi-channel fMRI provides more information of the pathological features. But the increased amount of data causes complexity in feature detections. this paper proposes a principal component analysis (PCA)-aided fully convolutional network to particularly deal with multi-channel fMRI. We transfer the learned weights of contemporary classification networks to the segmentation task by fine-tuning. the results of the convolutional network are compared with various methods e.g. k-NN. A new labeling strategy is proposed to solve the semantic segmentation problem with unclear boundaries. Even with a small-sized training dataset, the test results demonstrate that our model outperforms other pathological feature detection methods. Besides, its forward inference only takes 90 milliseconds for a single set of fMRI data. To our knowledge, this is the first time to realize pixel-wise labeling of multi-channel magnetic resonance image using FCN.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks signal processing algorithms

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signal processing Techniques for Accurate Screening of Wrist Fractures 8th

Signal Processing Techniques for Accurate Screening of Wrist...

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8th IFIP WG 5.5/SOCOLNET Advanced Doctoral conference on Computing, Electrical and Industrial Systems (DoCEIS)

作者： Ali, Ridita Alboul, Lyuba Offiah, Amaka Sheffield Hallam Univ Ctr Automat & Robot Res Sheffield S Yorkshire England Sheffield Childrens NHS Fdn Trust Sheffield S Yorkshire England

ISBN: (纸本)9783319560779

the common way for doctors to differentiate wrist injury in to a sprain or a fracture, is to take radiographs (X-ray), which expose patients to radiation. the purpose of this study is to explore a non-invasive method to screen for potential fractures. A small, computer run, hand-held system has been developed which consists of a vibration induction mechanism and a piezoelectric sensor for capturing the vibration signals. Two analyzing techniques were considered. the first involves extraction of wavelet coefficients from decomposition of data and the second applies Fast Fourier Transform to the data. Results of both techniques were then cluster analyzed to partition between fracture and sprain. the data were acquired from both the injured and uninjured wrists of six adult patients. this study is currently being evaluated on children's wrists.

关键词： Vibration analysis Fast fourier transform Wavelet decomposition Fracture screening

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A Hybrid Model Towards Moving Route Prediction Under data Sparsity 20

A Hybrid Model Towards Moving Route Prediction Under Data Sp...

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20th International conference on Information Fusion (Fusion)

作者： Wang, Liang Wang, Mei Ku, Tao Cheng, Yong Guo, Xinying Xian Univ Sci & Technol Xian 710054 Shaanxi Peoples R China Chinese Acad Sci Shenyang Inst Automat Shenyang 110016 Liaoning Peoples R China Xian Univ Technol Xian 710048 Shaanxi Peoples R China

ISBN: (纸本)9780996452700

Moving route prediction offers important benefits for many emerging location-aware applications such as target advertising and urban traffic management. A common approach to route prediction is to match similar trace recordings from a larger volume of historical trajectories, and return the targeted recorded path as desired answer. However, due to privacy concerns, incentive mechanism and other reasons, especially in small business environment, a limited dataset with sparse trajectories is only available. Actually, the existing sparse dataset cannot cover sufficient query routes, and then the match-based approach may return no results at all. Moreover, the existing sparse dataset may fail many trajectory mining approaches that work well on general environment. In this paper, we investigate moving route prediction from sparse trajectory dataset, and propose a novel hybrid model, namely HMRP, to address the above problem. To avoid sparse distribution over spatial semantic layer, a road network map reconstruction methods are proposed to accommodate the sparse trajectories in semantic transformation. And then, by training historical trajectories, the implicit mobility patterns and Markov transition model are constructed to support route prediction. When a query trajectory arrives, towards its derived potential destination, our proposed HMRP model integrates pattern matching strategy and Markov probability distribution to predict its future route gradually in a complementary way. Experiments on real-life taxicab GPS recorded dataset demonstrate that HMRP method can improve movement prediction precision significantly, comparing with the baseline prediction algorithms. And the response time for each query trajectory is acceptable for most application cases.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks signal processing algorithms

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3D GPR Imaging of Shallow Plastic Pipes, Tree Roots, and small Objects 16

3D GPR Imaging of Shallow Plastic Pipes, Tree Roots, and Sma...

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16th International conference on Ground Penetrating Radar (GPR)

作者： Grasmueck, M. Novo, A. RSMAS Univ Miami Dept Marine Geosci Miami FL 33149 USA IDS North Amer Inc Geosyst Business Unit Georadar Div Golden CO USA

ISBN: (纸本)9781509051816

Obtaining high quality and easy to interpret horizontal slices of the shallow subsurface depends on how a 3D ground penetrating radar (GPR) survey is acquired and processed. A field site containing three basic target geometries of linear pipes, curvilinear roots, and small objects serves as a testbed. High-density 250 and 500 MHz single channel GPR surveys covering 250m(2) were acquired to evaluate 3D GPR imaging parameters. the results show: 1) a uniform trace density of a quarter wavelength is necessary to image all three target geometries;2) positioning precision has to be better than half the trace spacing to avoid horizontal jitter;3) 500 MHz offers a good compromise between dense trace spacing and image resolution;and 4) 3D migration processing focuses diffractions in exact target locations. Sparse 3D GPR only images linear targets parallel to the antenna polarization. Curvilinear and point targets are missed. the findings also apply to multichannel array systems for high quality and efficient 3D GPR imaging of large field sites.

关键词： Ground penetrating radar data acquisition processing slice image quality full-resolution 3D pseudo 3D

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Noise Suppressing and Direct Wave Removal in GPR data Based on Shearlet Transform 16

Noise Suppressing and Direct Wave Removal in GPR Data Based ...

引用

16th International conference on Ground Penetrating Radar (GPR)

作者： Wang, X. N. Liu, S. X. Jilin Univ Coll Geoexplorat Sci & Technol Changchun 130026 Peoples R China

ISBN: (纸本)9781509051816

Ground penetrating radar (GPR) is often used to detect buried objects and evaluate structural condition. However, the direct wave and random noise often influence the arrival-time detection and the target-position location. We present a new application of Shearlet transform (ShT) to GPR data processing for direct wave removal and random noise suppression. ShT is a non-adaptive geometric-analysis technique, which has the properties of multi-directions and multi-scale, so it can show the optimal representations of signals in higher dimensions. the original GPR data is transformed to the ShT domain. the direct wave and the remaining GPR signal are effectively separated. While we eliminate the direct wave, the GPR signal is not damaged. the Shearlet coefficients of the GPR signal are relatively large, whereas random noises are relatively small. So we can use the threshold algorithm depending on different scales and directions in the ShT domain to suppress random noise. the GPR signal can be preserved very well and SNR is enhanced.

关键词： GPR Direct wave Random Noise Shearlet transform Suppression

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Localization and Backscattering Density Estimation from GPR data with Neural Network 16

Localization and Backscattering Density Estimation from GPR ...

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16th International conference on Ground Penetrating Radar (GPR)

作者： Liu, T. Huang, C. L. Su, Y. Xii, W. Natl Univ Def Technol Sch Elect Sci & Engn Changsha 410073 Hunan Peoples R China Acad Xuzhou Engn Xuzhou 221004 Peoples R China

ISBN: (纸本)9781509051816

Anadaptive linear neuron network is employed for reversing the location and back scattering density of objects from ground penetrating radar data. the processing avoids the disadvantage of unknown electromagnetic velocity in a medium for the specific rebar detecting application. Based on the common-offset reflection GPR survey model, the network was derived by reconstructing and compressing the reflected signal matrix. the location and scattering density of the targets under investigation are extracted by fitting the output of the network to the measured data. Finally, experiments with high-resolution configurations confirmed the reliability of the proposed method, and further developments are discussed.

关键词： Ground penetrating radar Neural network Adaptive linear neuron Back scattering density

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Indoor Detection and Tracking of Human targets with UWB Radar Sensor Networks 16

Indoor Detection and Tracking of Human Targets with UWB Rada...

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16th IEEE International conference on Ubiquitous Wireless Broadband (ICUWB)

作者： Valmori, Filippo Giorgetti, Andrea Mazzotti, Matteo Paolini, Enrico Chiani, Marco Univ Bologna CNIT DEI I-47521 Cesena FC Italy OCEM Airfield Technol I-40056 Crespellano BO Italy

ISBN: (纸本)9781509013173

In this paper, the whole signal processing chain for an ultra-wideband (UWB) radar sensor network (RSN) is presented, starting from real measurements collected by sensor devices, and ending with the estimation of the target trajectory. the RSN is composed by one transmitter and six receivers, and monitors an indoor area of about 70 m(2) performing tracking of a human target. the proposed processing chain consists of: clutter removal, a novel detection scheme, one-dimensional clustering, trilateration, two-dimensional clustering, particle-based probability hypothesis density filter tracking, and data association. Numerical results show the remarkable performance of the system, resulting in a root mean square localization error of 36 cm, a value smaller than the target size. the presented experimental study show that it is possible to accurately track human targets using a UWB RSN in a densely cluttered environment.

关键词： Ultra-wideband (UWB)

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An Envelope Alignment Method for Terahertz Radar ISAR Imaging of Maneuvering targets 1

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4th International conference on Communications, signal processing, and Systems (CSPS)

作者： Liu, Tong Cao, Zongjie Min, Rui Univ Elect Sci & Technol China Sch Elect Engn Chengdu Peoples R China

ISBN: (数字)9783662498316

ISBN: (纸本)9783662498316;9783662498293

A novel envelope alignment technique for terahertz radar ISAR imaging of maneuvering targets is presented in this paper. this method selects a single pulse echo as the envelope alignment benchmark through the correlation coefficient of adjacent range profiles, which solves the problems of jump error and drift error in the conventional adjacent amplitude correlation method. the imaging results of measured terahertz data demonstrate the effectiveness of this improved envelope alignment technique based on the adjacent amplitude correlation method.

关键词： Terahertz radar Maneuvering targets Envelope alignment ISAR imaging

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