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Accurate Click Fraud Rapid Detection of AD Requests for Smartphone Platforms

Accurate Click Fraud Rapid Detection of AD Requests for Smar...

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Applied Artificial Intelligence and computing (ICAAIC), international conference on

作者： I Justin Sophia. R. Meganathan B. Dhanasakkaravarthi S. Satheesh Kumar Abhishek Mishra Department of Computer Science Loyola College Chennai Tamil Nadu India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India Department of Mechanical Engineering Agni College of Technology Chennai Tamil Nadu India Department of Master of Business Administration Panimalar Engineering College Chennai Tamil Nadu India Department of Management Studies Graphic Era Deemed to be University Dehradun Uttarakhand India

The main objective of this work is to develop a system for detecting fraudulent clicks in the context of EyeSee activity. EyeSee is characterized by being a provider of innovative advertising formats and digital solutions. There are several reasons why ad networks and advertisers want new ways to analyze the traffic produced by ad clicks: advertisers are scammed, incorrect statistics, lost customers and boosting a parallel economy. The most common way that ad clicks are analyzed is through cookies and IP addresses. Cookies are related to authentication, unfortunately they are susceptible to attacks such as Session hijacking. Through the IP address it also becomes complicated, since there are distributed attacks in which several machines are used (botnet) to produce the click fraud attack. Even if an IP is blocked from a distributed attack, the other machines continue to reproduce the attack. In order to apply a solution, a click fraud detection system capable of identifying the veracity of a click was created. This system will be able to test the browser and validate user behavior.

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Deployment of Batch Mode Scientific Workflow on a Computation-as-a-Service Private cloud

Deployment of Batch Mode Scientific Workflow on a Computatio...

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international conference on Soft computing and Machine Intelligence (ISCMI)

作者： Yiyi Xu Pengfei Liu Irene Penesis Guanghua He Australia and Department of Computer Science & Engineering Guangxi University of Science and Technology Liuzhou China

ISBN: (纸本)9781728113029;9781728113012

cloud computing is usually to address business problems of costly computing infrastructures but nowadays it is considered as a possible alternative to scientific workflow deployment. Therefore, there are only limited cases for scientific and engineering computing in which there are task parallelism closely coupled with high concurrent I/O requirements. To address this issue, this paper developed a new resource management methodology to maximize overall machine utilization levels while minimizing application run time. The key strategy and algorithm in this methodology consist of: (i) a bottom-up architecture that utilizes resources for both servers and clients. (ii) a maximum utilization resource coloration algorithm based on node ability. A prototype system was implemented by incorporating the policies and algorithms mentioned above in cloud computing and distributed Systems (cloudS) Laboratory. Initial results were obtained by two different cases, by Rotorysics (formerly Propella), a special marine hydrodynamics code for propellers and turbines and by DF_OSFBEM, a panel method code for unsteady 3D multiple-foil hydrodynamics. Results showed that new solution has speeded up total run time up to 50% at the 2nd level - the higher service ability level. By using the developed methodology and exploration of Computation-as-a-Service (CaaS), the objective was achieved to accelerate scientific workflow efficiency in private cloud computing platform.

关键词： cloud computing Task analysis Resource management Peer-to-peer computing Computational modeling Data centers Computer architecture

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Accelerating MatLab code using GPU: A review of tools and strategies

Accelerating MatLab code using GPU: A review of tools and st...

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international conference on Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC)

作者： Baida Zhang Shuai Xu Feng Zhang Yuan Bi Linqi Huang National laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha China Department of Information Engineering Academy of Armored Forces Engineering Beijing China Inspur (Beijing) Electronic Information Industry Company Limited Beijing China Naval Academy of Armament Beijing China School of Resources and Safety Engineering Central South University Changsha China

Lots of toolboxes of accelerating MatLab using GPU are available now[1], but, users are confused by which toolbox is best suitable for a particular task. Three toolboxes-Jacket, GPUmat, and parallel computing Toolbox of MatLab are selected. For each toolbox, its advantages and pitfalls are reviewed, with an aim to allow the reader to identify which toolbox is appropriate for a given task. Strategies of whether a function should execute on GPU are given after a formula analysis. The analysis is also a framework for program automatically decides which function is cost-efficient to execute on GPU. A series of benchmark of different types of computing, including data transfer between GPU and CPU, data matrix Generation, matrix operation and GPU functions were tested in all three toolboxes. And the results show that Jacket is the best one. Some advices to improve the performance of toolboxes are given in the end.

关键词： Graphics processing unit Acceleration parallel processing Computer architecture conferences Licenses MATLAB

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Game Theoretic Modeling to Enforce Security Information Sharing among Firms

Game Theoretic Modeling to Enforce Security Information Shar...

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IEEE international conference on Cyber Security and cloud computing (CScloud)

作者： Deepak K. Tosh Shamik Sengupta Sankar Mukhopadhyay Charles A. Kamhoua Kevin A. Kwiat Dept of Computer Science and Engineering Dept of Economics University of Nevada Reno Cyber Assurance Branch Air Force Research Laboratory Rome NY

ISBN: (纸本)9781467393010

Robust CYBersecurity information EXchange (CYBEX) infrastructure is envisioned to protect the firms from future cyber attacks via collaborative threat intelligence sharing, which might be difficult to achieve via sole effort. The executive order from the U. S. federal government clearly encourages the firms to share their cybersecurity breach and patch related information among other federal and private firms for strengthening their as well as nation's security infrastructure. In this paper, we present a game theoretic framework to investigate the economic benefits of cyber-threat information sharing and analyze the impacts and consequences of not participating in the game of information exchange. We model the information exchange framework as distributed non-cooperative game among the firms and investigate the implications of information sharing and security investments. The proposed incentive model ensures and self-enforces the firms to share their breach information truthfully for maximization of its gross utility. Theoretical analysis of the incentive framework has been conducted to find the conditions under which firms' net benefit for sharing security information and investment can be maximized. Numerical results verify that the proposed model promotes such sharing, which helps to relieve their total security technology investment too.

关键词： Investment Information management Games Information exchange Computer security Numerical models

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Secure Routing for Mobile Ad Hoc Networks

Secure Routing for Mobile Ad Hoc Networks

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ACIS international conference on Software engineering, Artificial Intelligence, Networking, and parallel/distributed computing (SNPD)

作者： Jing Liu Fei Fu Junmo Xiao Yang Lu People''s Liberation Army University of Science and Technology China

Buttyan found out a security flaw in Ariadne (Y.C. Hu, A. Perrig, andD. B. Johnson, "Ariadne: a secure on-demand routing protocol for ad hoc networks," in Proc. of the Eighth ACM hitl Conf. on Mobile computing and Networking (*** 2002), pp.23-28. Atlanta, GA.2002.) and proposed a secure routing protocol, EndairA (L. Buttyan, and I. Vajda, "Towards provable security for ad hoc routing protocols", in Proc. of the 2nd ACM Workshop on Security of ad hoc and Sensor Networks, 2005 and G. Acs, L. Buttyan, and I. Vajda, "Provably secure on-demand source routing in mobile ad hoc networks," IEEE Transactions on Mobile computing, Vol. 5, No. 11, November 2006.), with the ability to resist active-1-1 attacks. But unfortunately we discover an as yet unknown active-0- 1 attack which we call man-in-the-middle attack and EndairA couldn 't resist. Accordingly we propose a new secure routing protocol, EndairALoc. Analysis shows that EndairALoc can resist not only active-1-1 attacks but also the wormhole attack. Furthermore EndairALoc uses pairwise secret keys instead of public keys used in EndairA. Compared with EndairA, EndairALoc can save more energy in the routing establishment.

关键词： Mobile ad hoc networks Routing protocols Resists Security Public key Cryptography Software engineering Artificial intelligence distributed computing Programmable logic arrays

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Efficient Resource Allocation with Score for Reliable Task Scheduling in cloud computing Systems

Efficient Resource Allocation with Score for Reliable Task S...

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international conference on Innovative Mechanisms for Industry Applications (ICIMIA)

作者： Vijayalakshmi A. Lepakshi C S R Prashanth Maharani Lakshmi Ammanni College for Women Bangalore India New Horizon College of Engineering Bangalore India

ISBN: (数字)9781728141671

ISBN: (纸本)9781728141688

parallel task execution in a heterogeneous cloud computing system emerges as NP-complete problem and in the literature, many heuristics behave differently when deployed in various environments. Efficient resource allocation improves reliability and leads to the completion of jobs and minimization of delays. In general, static task scheduling algorithms consider the earliest finish time (EFT) of the task to minimize the makespan. In this work, we propose a new heuristic called Efficient Resource Allocation with Score (ERAS) for reliable task scheduling in cloud computing systems, which considers temporal operational availability of Virtual Machines (VM) by considering various types of delays and EFT to assign a normalized score to the processor for scheduling tasks. Here, the allocation of VMs to tasks is based on a score given to each VM, by considering multiple criteria. The results show that ERAS algorithm gives better performance with increased reliability when compared to existing algorithms that consider only EFT for allocation.

关键词： Task analysis cloud computing Virtual machining Reliability Scheduling algorithms Resource management

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Empirical cloud computing Remote Human Resource Work Efficiency System Based on Data Mining

Empirical Cloud Computing Remote Human Resource Work Efficie...

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Sensors, Electronics and Computer engineering (ICSECE), IEEE international conference on

作者： Linfang Wu Guangzhou Huashang Vocational College Guangzhou China

ISBN: (数字)9798350373646

ISBN: (纸本)9798350373653

In order to improve the dynamic monitoring ability of power grid human resource management system, fuzzy information cluster analysis technology is used to study the dynamic monitoring technology of power grid human resources. This paper establishes a modern HR management system based on cloud computing. The virtual architecture layer mainly collects entities and virtual computing resources in multiple Spaces, and integrates these resources into a dynamically adjustable database to realize the physical storage and transmission of data. The row and column decisions of the situation are obtained through multiple objective situation decisions. Using multiple target situation decision matrix, the optimal situation is selected for personnel allocation and fed back to the display layer. The distribution structure model of power consumption human resources is established and the distribution cluster center of power consumption human resources is obtained. In this paper, the multi-dimensional time scale features of personnel data are examined by clustering method, and the automatic identification and fuzzy extraction of personnel data are realized. The state equation of the model is obtained by simulating the model. The accuracy and rapidity of this algorithm in human resource data monitoring are verified by statistical analysis of power grid human resource data. The research results of this paper provide an effective means for the effective utilization of power grid human resources.

关键词： Power demand Power system dynamics Feature extraction Dynamic scheduling Power grids Mathematical models Personnel Resource management Data mining Monitoring

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PCPSVM: A parallel Cutting Plane Algorithm for Training SVMs

PCPSVM: A Parallel Cutting Plane Algorithm for Training SVMs

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2010 2nd international conference on Computer engineering and Technology(2010年第二届计算机工程与技术国际会议 ICCET 2010)

作者： Ganzhao Yuan School of Computer Science and Engineering South China University of Technology Guangzhou 510006 P. R. China

ISBN: (纸本)9781424463473

The cutting plane algorithm provides fast training for classification SVMs,but it still suffers from the problem of memory restriction,because the algorithm requires to load all the data to the memory. To overcome this bottleneck,we propose and implement a parallel Cutting Plane algorithm for training Support Vector Machines (PCPSVM) on distributed computers. The Algorithm uses a row-based storage method to reduce memory requirement and finally can parallelize both data loading and computation. Let l denote the number of training instances,d the dimension of each instance,m the number of machines. We divide the data to m parts,and loads only essential data to each machine to perform parallel computation. The memory requirement can be reduced from O(ld) to O(ld/m). We implement our PCPSVM algorithm in the MPICH platform. Experiments show that the algorithm is effective,memory requirement is reduced and great speed-up is achieved when many processors are used. PCPSVM Open Source is available at .

关键词： Cutting Plane parallel computing Row-based SVMs Machine Learning Large-Scale Problem

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Towards a smart selection of resources for low-energy multimedia processing

Towards a smart selection of resources for low-energy multim...

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international conference on cloud Technologies and Applications (cloudTech)

作者： Sidi Ahmed Mahmoudi Faculty of Engineering University of Mons Belgium

ISBN: (纸本)9781467388955

Today, one can find images and videos everywhere, they can come from cameras, mobile phones or from other devices. These images and videos are used to illustrate different objects in a large number of situations (airports, hospitals, public areas, sport events, etc.). This makes the task of processing images and videos a necessary tool that can be used for various domains related to computer vision. The performance of these algorithms have been so reduced due to their high intensive computation and energy consumption. In this work, we propose a new framework that allows users to select in a smart and efficient way the computing units (CPU or/and GPU) in case of processing single image, multiple images, multiple videos or single video in real time. This framework enables to affect the CPU or/and GPU units for calculation depending on the type of media to process and the algorithm complexity. The framework provides several image and video functions on GPU, such as silhouette extraction, points of interest extraction, edges detection, sparse and dense optical flow estimation. These functions are exploited in different applications such as vertebra segmentation in X-ray and MR images, gaze estimation, event detection and localization in real time. Experimental results have been obtained by applying the framework for different use case applications showing a speedup ranging from 5 to 116×, by comparison with sequential CPU implementations. In addition to these performance, the parallel and heterogeneous implementation offered lower power consumption as a result for the fast treatment.

关键词： Biomedical imaging Performance evaluation Estimation Cameras Image edge detection Hardware Graphics processing units

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Application of parallel computing Thought in Training Model for Computer Talents

Application of Parallel Computing Thought in Training Model ...

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Information Science and Education (ICISE-IE), international conference on

作者： Qirui Li Delong Cui Qiuli Fu Jieguang He College of Computer Guangdong University of Petrochemical Technology Maoming China College of Electronic Information Engineering Guangdong University of Petrochemical Technology Maoming China

ISBN: (纸本)9781665438308

Compared with serial computing, parallel computing can execute multiple instructions at a time, which can increase computing speed and expand the scale of solutions, thereby solving large and complex computing problems. The training of computer talents is also a complex system engineering. Therefore, we propose a parallel dual-system training model for computer talents with industry-education integration and quality-development. Different from general parallel computing, the model we proposed has both temporal and spatial parallelism. The temporal parallelism is reflected in the two system lines being carried out at the same time in the training process, while the spatial parallelism is reflected in the staggering of the two system lines in the same course. In industry-education integration system, we establish the cooperation between schools and enterprises in building a series of curriculums, including mobile application (MA), artificial intelligence (Al), cloud computing (CC), big data (BD), innovation and entrepreneurship (IES), internships at enterprises (IE), to effectively improve students’ technological foresight and mastery. Moreover, the quality-development system consists of the compulsory projects integrated with theoretical courses and the elective projects integrated with extracurricular practice, so as to improve students’ comprehensive quality. In this model, the credits of courses in industry-education system accounts for 37.5%, quality-development system accounts for 32.7%, and other courses account for 29.8%. Practical results show that by applying this talent training model, the counterpart employment rate of computer science graduates in 2021 has increased by 10%, and the number of postgraduate admissions has increased by 80%, compared with graduates in 2020, the number of professional competition awards has increased by 15%, compared with students in 2020.

关键词： Training Analytical models Technological innovation Information science Philosophical considerations Computational modeling Entrepreneurship

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