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Research on Integrated Detection of SQL Injection Behavior Based on Text Features and Traffic Features 10th

Research on Integrated Detection of SQL Injection Behavior B...

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10th International conference on Computer Engineering and Networks, CENet 2020

作者： Li, Ming Liu, Bo Xing, Guangsheng Wang, Xiaodong Wang, Zhihui College of Intelligence Science and Technology National University of Defence Technology Changsha410073 China National Key Laboratory of Parallel and Distributed Processing College of Computer Science and Technology National University of Defence Technology Changsha410073 China

ISBN: (纸本)9789811584619

With the rapid development of Internet technology, various network attack methods come out one after the other. SQL injection has become one of the most severe threats to Web applications and seriously threatens various Web application services and users data security. There are both traditional detection methods and emerging methods based on deep learning technology with higher detection accuracy for the detection of SQL injection. However, they are all for detecting a single statement and cannot determine the stage of the attack. To further improve the effect of SQL injection detection, this paper proposes an integrated detection framework for SQL injection behavior based on both text features and traffic features. We propose a SQL-LSTM model based on deep learning technology as the detection model at the text features level. Meanwhile, the features of the data traffic are merged. By this integrated method, the detection effect of SQL injection is further improved. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Long short-term memory

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RPL: A Domain-Specific Language for Designing and Implementing parallel C++ Applications

RPL: A Domain-Specific Language for Designing and Implementi...

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Euromicro conference on parallel, distributed and Network-Based processing

作者： V. Janjic C. Brown K. Mackenzie K. Hammond M. Danelutto M. Aldinucci J. Daniel Garcia Uni. of St Andrews UK Uni. of Pisa Italy Uni. of Torino Italy Uni. Carlos III Madrid Spain

parallelising sequential applications is usually a very hard job, due to many different ways in which an application can be parallelised and a large number of programming models (each with its own advantages and disadvantages) that can be used. In this paper, we describe a method to semi-automatically generate and evaluate different parallelisations of the same application, allowing programmers to find the best parallelisation without significant manual reengineering of the code. We describe a novel, high-level domain-specific language, Refactoring Pattern Language (RPL), that is used to represent the parallel structure of an application and to capture its extra-functional properties (such as service time). We then describe a set of RPL rewrite rules that can be used to generate alternative, but semantically equivalent, parallel structures (parallelisations) of the same application. We also describe the RPL Shell that can be used to evaluate these parallelisations, in terms of the desired extra-functional properties. Finally, we describe a set of C++ refactorings, targeting OpenMP, Intel TBB and FastFlow parallel programming models, that semi-automatically apply the desired parallelisation to the application's source code, therefore giving a parallel version of the code. We demonstrate how the RPL and the refactoring rules can be used to derive efficient parallelisations of two realistic C++ use cases (image Convolution and Ant Colony Optimisation).

关键词： Skeleton Libraries parallel processing Pipelines parallel programming Writing

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parallel processing improvements for full-wave electromagnetic solvers

Parallel processing improvements for full-wave electromagnet...

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IEEE Topical Meeting on Electrical Performance of Electronic Packaging (EPEPS)

作者： Seung-Cheol Lee Sergey Polstyanko Denis Soldo Matthew Commens Prakash Vennam Steven G. Pytel ANSYS Inc. Canonsburg PA

As computing resources become increasingly parallel for both shared and distributed memory systems, computational electromagnetic methods need to take full advantage of new architectures in order to reduce simulation times. Several different aspects of the solution process make it difficult for traditional finite element field solvers to effectively utilize distributed and shared memory resources. This paper will provide insight into recent advancements made in the finite element method matrix solve (shared memory) and frequency sweep (distributed memory) that drastically reduce simulation times for signal and power integrity applications.

关键词： Finite element analysis Transmission line matrix methods Random access memory Sparse matrices Three-dimensional displays parallel processing Geometry

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Discrete wavelet transform IPcore design for image compression

Discrete wavelet transform IPcore design for image compressi...

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International conference on Signal processing Proceedings (ICSP)

作者： Weihuang Fu Limin Meng Xiaoyuan Wang Zhejiang Provincial Key Laboratory of Optic Fiber Communication Technology Zhejiang University of Technology China Eastern Communications Company Limited China

Discrete wavelet transform (DWT), which is recently used by some international standard organizations in image compression protocols, has an excellent performance on multiresolution representation. Because of DWT's computation-intensive nature, however, it seldom meets the application of real-time video system. Field programmable gate array (FPGA) has the advantages as parallel, high-speed, and easy-modification. These merits make FPGA the appropriate choice for the DWT implementations. This paper describes an IPcore design based on hardware description language (HDL), and implemented on an FPGA device. The core uses distributed arithmetic, parallel operation, and pipelining design. In addition, the IPcore technology protects and encapsulates the design of the image compression core.

关键词： Discrete wavelet transforms image coding Field programmable gate arrays Hardware design languages Protocols image resolution Real time systems Video compression Arithmetic Pipeline processing

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parallel implementations of AOS schemes: a fast way of nonlinear diffusion filtering

Parallel implementations of AOS schemes: a fast way of nonli...

引用

IEEE International conference on image processing

作者： J. Weickert K.J. Zuiderveld B.M. ter Haar Romeny W.J. Niessen Image Sciences Institute Utrecht University Hospital Utrecht Netherlands DIKU Universitetsparken Copenhagen Denmark

In most cases nonlinear diffusion filtering is implemented by means of explicit finite difference schemes. These algorithms are not very efficient, since they are only stable for small time steps. We address this problem by presenting unconditionally stable semi-implicit schemes which are based on an additive operator splitting (AOS). They are very efficient since they can be implemented by recursive filtering, and their separability allows a straightforward implementation in any dimension. We analyse their behaviour on a parallel computer and demonstrate that parallel AOS schemes on a modern shared-memory multiprocessor system with 8 processors allow a speed-up of two orders of magnitude in comparison to the widely-used explicit scheme on a single processor.

关键词： Filters Smoothing methods Filtering image edge detection Ultrasonic imaging Hospitals Concurrent computing Time sharing computer systems Multiprocessing systems parallel processing

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GPU-Accelerated FDTD Solver for Electromagnetic Differential Equations 24th

GPU-Accelerated FDTD Solver for Electromagnetic Differential...

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24th International conference on Computational Science (ICCS)

作者： HoseinyFarahabady, MohammadReza Zomaya, Albert Y. Univ Sydney Ctr Distributed & High Performance Comp Sch Comp Sci Sydney NSW Australia

ISBN: (纸本)9783031637537;9783031637513

Computational electromagnetics plays a crucial role across diverse domains, notably in fields such as antenna design and radar signature prediction, owing to the omnipresence of electromagnetic phenomena. Numerical methods have replaced traditional experimental approaches, expediting design iterations and scenario characterization. The emergence of GPU accelerators offers an efficient implementation of numerical methods that can significantly enhance the computational capabilities of partial differential equations (PDE) solvers with specific boundary-value conditions. This paper explores parallelization strategies for implementing a Finite-Difference Time-Domain (FDTD) solver on GPUs, leveraging shared memory and optimizing memory access patterns to achieve performance gains. One notable innovation presented in this research involves utilizing strategies such as exploiting temporal locality and avoiding misaligned global memory accesses to enhance data processing efficiency. Additionally, we break down the computation process into multiple kernels, each focusing on computing different electromagnetic (EM) field components, to enhance shared memory utilization and GPU cache efficiency. We implement crucial design optimizations to exploit GPU's parallel processing capabilities fully. These include maintaining consistent block sizes, analyzing optimal configurations for field-updating kernels, and optimizing memory access patterns for CUDA threads within warps. Our experimental analysis verifies the effectiveness of these strategies, resulting in improvements in both reducing execution time and enhancing the GPU's effective memory bandwidth. Throughput evaluation demonstrates performance gains, with our CUDA implementation achieving up to 17 times higher throughput than CPU-based methods. Speedup gains and throughput comparisons illustrate the scalability and efficiency of our approach, showcasing its potential for developing large-scale electromagnetic simulations on

关键词： Numerical Computational Electromagnetics GPU Accelerators Finite-Difference Time-Domain Solver Partial Differential Equations Geometric Discretization

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Wi-FLIP: A wireless smart camera based on a focal-plane low-power image processor

Wi-FLIP: A wireless smart camera based on a focal-plane low-...

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ACM/IEEE International conference on distributed Smart Cameras, ICDSC

作者： Jorge Fernández-Berni Ricardo Carmona-Galán Gustavo Liñán-Cembrano Ákos Zarándy Ángel Rodríguez-Vázquez Institute of Microelectronics of Seville (IMSE-CNM) Sevilla Spain Computer and Automation Research Institute (MTA-SZTAKI) Budapest Hungary

This paper presents Wi-FLIP, a vision-enabled WSN node resulting from the integration of FLIP-Q, a prototype vision chip, and Imotel, a commercial WSN platform. In Wi-FLIP, image processing is not only constrained to the digital domain like in conventional architectures. Instead, its image sensor - the FLIP-Q prototype - incorporates pixel-level processing elements (PEs) implemented by analog circuitry. These PEs are interconnected, rendering a massively parallel SIMD-based focal-plane array. Low-level image processing tasks fit very well into this processing scheme. They feature a heavy computational load composed of pixel-wise repetitive operations which can be realized in parallel with moderate accuracy. In such circumstances, analog circuitry, not very precise but faster and more area- and power-efficient than its digital counterpart, has been extensively reported to achieve better performance. The Wi-FLIP's image sensor does not therefore output raw but pre-processed images that make the subsequent digital processing much lighter. The energy cost of such pre-processing is really low - 5.6mW for the worst-case scenario. As a result, for the configuration where the Imote2's processor works at minimum clock frequency, the maximum power consumed by our prototype represents only the 5.2% of the whole system power consumption. This percentage gets even lower as the clock frequency increases. We report experimental results for different algorithms, image resolutions and clock frequencies. The main drawback of this first version of Wi-FLIP is the low frame rate reachable due to the non-standard GPIO-based FLIPQ-to-Imote2 interface.

关键词： Clocks Wireless sensor networks Power demand image resolution Prototypes Arrays

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Detecting Arithmetic of Passenger's Location Based on image processing

Detecting Arithmetic of Passenger's Location Based on Image ...

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ACIS International conference on Software Engineering, Artificial Intelligence, Networking, and parallel/distributed Computing (SNPD)

作者： Ying Yang Jing Sheng Wei Zhou School of Mechanical Engineering and Automation Northeastern University Shenyang China

Airbag deployments during automobile accidents can cause injury and even death if the occupant is an improper size or in an improper position. Because of this, steps have been taken to make airbag deployment safer by adding adaptive deployment decision capabilities. This paper presents a new method to obtain occupants' pose and location by using a CCD camera fixed in a cabin. The face location is the target of our initial focus, as it provides a good estimate of the occupant's head position and is the most critical part of the body in airbag deployment. The occupants' head locations are detected through obtaining their face position. First, establish criterion templates to represent different size of occupants, that is, children, the 5th percentage of female, the 50th percentage of male and the 90"' percentage of male. Then compare the occupants' stature with the criterion templates. The airbag can be fully deployed, partially deployed or nor deployed at all according to occupants' size and location. This arithmetic has the advantage of simple, accuracy, real time and less sensitive to illumination. Experimental results show that the recognition accuracy of the proposed approach is better. The total correct classification rate is 96.5%. It has great significance to maximum protect occupants' lives according to occupants' stature to control the deployment of airbag.

关键词： Arithmetic image processing Face detection Head Automobiles Accidents Injuries Charge coupled devices Charge-coupled image sensors Focusing

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image Preprocessing and Trajectory Feature Extraction based on Hidden Markov Models for Sign Language Recognition

Image Preprocessing and Trajectory Feature Extraction based ...

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ACIS International conference on Software Engineering, Artificial Intelligence, Networking, and parallel/distributed Computing (SNPD)

作者： Duong Van Hieu Supot Nitsuwat Fac. of Inf. Technol. King Mongkut's Univ. of Technol. Bangkok Faculty of Information Technology King Mongkut''s University of Technology Bangkok Thailand Faculty of Information Technology King Mongkut's University of Technology North Bangkok

ISBN: (纸本)9780769532636

This paper presents a new image preprocessing and revised feature extraction methods for sign language recognition (SLR) based on Hidden Markov Models (HMMs). Multi-layer Neural Network is used for building an approximate skin model by using Cb and Cr color components of sample pixels. Gesture videos are spitted into image sequences and converted into YCbCr color space. In order to get only hand area in each image, unexpected skin areas such as face of actor and noises are identified and eliminated. After obtaining hand areas from image sequence of each gesture, features such as direction, center of gravity, length, and so on will be taken out for learning and testing phases. The features will be normalized before used as inputs of HMMs for learning models and recognizing gesture activities.

关键词： Hidden Markov models Feature extraction image color analysis Trajectory Skin Pixel image sequences

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Terrain Change Monitoring and Computer image processing Algorithms in Building Site Monitoring

Terrain Change Monitoring and Computer Image Processing Algo...

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distributed Computing and Optimization Techniques (ICDCOT), International conference on

作者： Juanjuan Wang Shandong Huayu University of Technology Dezhou Shandong China

With the continuous development of the construction industry, monitoring terrain changes on site has become increasingly important. Traditional monitoring methods are not efficient, while computer image processing algorithms have the advantage of fast and accurate processing of monitoring images. So this article studies a terrain change monitoring model based on computer image processing algorithms in construction site monitoring. Based on the VisDrone dataset, the first step is to preprocess the image, use histogram equalization to process light interference, and use median filtering to process electromagnetic interference. This article uses a grayscale co-occurrence matrix to identify building features, and uses the slope of observation points to represent surface changes. Subsequently, the features are input into the Convolutional Recurrent Neural Network (CRNN) for training, and the results are classified using a support vector machine (SVM). The experimental results show that the precision rate of the model in identifying terrain changes reaches 96.3%, and the processing time of a single image is 3.7s. The model has good speed and accuracy in monitoring terrain changes, providing a reference for monitoring terrain changes in construction sites.

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