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4th IEEE International Conference on Cloud Computing and Intelligence Systems (IEEE CCIS)

作者： Yu, Hewei Hu, Yangyu Gao, Yang Xu, Juan Zhang, Miao Natl Comp Network Emergency Response Tech Team Coordinat Ctr China Beijing 100029 Peoples R China Beijing Univ Posts & Telecommun Informat Secur Ctr Beijing 100876 Peoples R China

ISBN: (纸本)9781509012565

With the explosive growth of mobile application, more and more threats migrate from traditional PC platform to mobile device. Mobile Internet platform, especially Android platform, is becoming a hotbed of malicious application. The security monitoring of massive applications in application stores is a focus in the field of information security. The study of related topics of security detection and defense of malicious application is badly needed. This paper puts forward a processing method of massive data based on security detection of Android application which intends to improve the efficiency of security detection engine in the face of a large number of concurrent detection task. By parallel extracting characteristic properties of APKs and building local signature database, the detection process can be simplified so as to achieve a good treatment effect.

关键词： Android platform mobile malware detection APK feature extraction massive data processing

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Research and Application of massive data processing in Oil Services

Research and Application of Massive Data Processing in Oil S...

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2012 3rd International Conference on Information Technology for Manufacturing Systems(ITMS 2012)

作者： LI Baoan Computer School Beijing Information Science and Technology University

Big data problem has caused widespread concern from industry to academia in recent years. As the amount of data produced by various industries and sectors of rapid growth, increasing demands on data processing and analysis capabilities, how to face the challenges of data, discover new opportunities, the issue has received wide attention. As a traditional industry, the oil drilling or refinery enterprise is facing the operational status of the system to produce large amounts of data. This text introduced an approach to massive data processing for oil enterprise based on cloud computing and Internet of Things.

关键词： massive data processing Oil Services Cloud Computing IOT(Internet of Things)

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Visual animal biometrics: survey

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IET BIOMETRICS 2017年第3期6卷 139-156页

作者： Kumar, Santosh Singh, Sanjay Kumar Banaras Hindu Univ Indian Inst Technol Dept Comp Sci & Engn Varanasi 221005 Uttar Pradesh India

Visual animal biometrics is an emerging research discipline in computer vision, pattern recognition and cognitive science. It is a promising research field that encourages new development of quantified algorithms and methodologies for representing, detection of visible features, phenotypic appearances of species, individuals and recognition of morphological and animal biometric characteristics. Furthermore, it also assists the study of animal trajectory and behaviours analysis of species. Currently, real-world applications of visual animal biometric systems are gaining more proliferation due to a variety of applications and use, enhancement of quantity and quality of the collection of extensive ecological data and processing. However, to advance visual animal biometrics will require integration of methodologies among the scientific disciplines involved. Such valuable efforts will be worthwhile due to the enormous perspective of this approach rests with the formal abstraction of phenomics, to build well-developed interfaces between different organisational levels of life. This study provides a comprehensive survey of visual animal biometric systems and recognition approaches for various species and individual animal based on their morphological image pattern and biometric characteristics. This comprehensive review paper encourages the multidisciplinary researchers, scientists, biologists and different research communities to design the better platforms for the development of efficient algorithms and learning models to solve the massive data processing, classification and identification of different species related problems.

关键词： biology computing zoology feature extraction biometrics (access control) image classification species phenotypic appearances species visible features animal biometric characteristics species behaviours analysis species animal trajectory visual animal biometric systems formal abstraction morphological image pattern characteristics morphological image biometric characteristics massive data processing

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RESEARCH on THE TECHNOLOGY of massive ANDROID APPLICATION data processing

RESEARCH on THE TECHNOLOGY of MASSIVE ANDROID APPLICATION DA...

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2016 4th IEEE International Conference on Cloud Computing and Intelligence Systems（IEEE CCIS2016）

作者： Hewei Yu Yangyu Hu Yang Gao Juan Xu Miao Zhang National Computer network Emergency Response technical Team/Coordination Center of China Information Security Center Beijing University of Posts and Telecommunications

ISBN: (纸本)9781509012572

关键词： Android platform mobile malware detection APK feature extraction massive data processing

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massive Collaborative Wireless Sensor Network Structure Based on Cloud Computing

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INTERNATIONAL JOURNAL OF ONLINE ENGINEERING 2018年第11期14卷 4-15页

作者： Ren, Qiong Jianghan Univ Sch Math & Comp Sci Wuhan 430056 Hubei Peoples R China

To explore the wireless sensor network (WSN) structure, the cooperative WSN architecture of mass data processing based on cloud computing is studied. The technology of WSN and cloud computing is deeply discussed. The system and node structure of WSN are studied by theoretical analysis method, and the performance of the WSN is studied by using the numerical simulation method. The mass data processing technology based on Map Reduce and its application in WSN are discussed. The numerical simulation method is used to experiment on the architecture of SVC4WSN and MD4LWSN. The relationship between the optimal network number and the node communication radius at different node density is verified. Moreover, the energy and time delay Reduce path is compared with three protocols of LEACH, PEGASIS and PEDAP. The results show that the two Reduce paths have better performance in both network survival time and the total time slot of data acquisition.

关键词： WSN massive data processing cloud computing

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Task scheduling of massive spatial data processing across distributed data centers: what's new?

Task scheduling of massive spatial data processing across di...

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17th IEEE International Conference on Parallel and Distributed Systems (ICPADS)

作者： Song, Weijing Yue, Shasha Wang, Lizhe Zhang, Wanfeng Liu, Dingsheng Chinese Acad Sci Ctr Earth Observat & Digital Earth Beijing 100864 Peoples R China

ISBN: (纸本)9780769545769

Spatial data processing in general involves large-scale distributed computing resources across multiple data centers and distributed massive data sets. Task scheduling of spatial data processing across distributed data centers brings new research issues and calls for novel scheduling mechanisms and frameworks. This paper analyzes the features of spatial data processing, identifies the research issues of task scheduling in massive spatial data processing, and proposes task model & scheduling mechanisms for task scheduling in spatial data processing.

关键词： massive data processing spatial data infrastructure task scheduling

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Research of Demand Recognition Based on Template Matching 11

Research of Demand Recognition Based on Template Matching

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11th International Conference on Computer Science & Education (ICCSE)

作者： Liu, Weiqiang Wang, Beizhan Chen, Lingyu Chen, Kang Wang, Jiajun Xiamen Univ Software Sch Xiamen Peoples R China

ISBN: (纸本)9781509022182

The search way of traditional search engines is the full-text retrieval based on inverted index, which is also the retrieval way used to query the index database based on the search statement, and this doesn't make good use of the meaning expressed by the search statements, thereby failing to accurately identify the specific demand of users, and this is bound to give users greater search costs. The introduction of vertical search is a solution to this problem of traditional search engines, while the first is to identify the meaning of users' search statements in order to achieve vertical search, which is the problem needs to be solved in natural language processing. This paper designs the demand recognition algorithm based on the template matching, and introducesspecific design ideas, and algorithms. The experimental results show that the demand recognition algorithm designed in this paper may well be used to identify the specific demand of the users' search statements.

关键词： Demand Recognition Natural Language processing massive data processing

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Research of Demand Recognition Based on Template Matching

Research of Demand Recognition Based on Template Matching

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International Conference on Computer Science and Education

作者： Weiqiang Liu Beizhan Wang Lingyu Chen Kang Chen Jiajun Wang Software School of Xiamen University

ISBN: (纸本)9781509022199

关键词： Demand Recognition Natural Language processing massive data processing

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A Software Chain Approach to Big data Stream processing and Analytics 9

A Software Chain Approach to Big Data Stream Processing and ...

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9th International Conference on Complex, Intelligent and Software Intensive Systems (CISIS)

作者： Xhafa, Fatos Naranjo, Victor Caballe, Santi Barolli, Leonard Univ Politecn Cataluna Barcelona Spain Open Univ Catalonia Barcelona Spain Fukuoka Inst Technol Fukuoka Japan

ISBN: (纸本)9781479988709

Big data Stream processing is among the most important computing trends nowadays. The growing interest on Big data Stream processing comes from the need of many Internet-based applications that generate huge data streams, whose processing can serve to extract useful analytics and inform for decision making systems. For instance, an IoT-based monitoring systems for a supply-chain, can provide real time data analytics for the business delivery performance. The challenges of processing Big data Streams reside on coping with real-time processing of an unbounded stream of data, that is, the computing system should be able to compute at high throughput to accommodate the high data stream rate generation in input. Clearly, the higher the data stream rate, the higher should be the throughput to achieve consistency of the processing results (e.g. preserving the order of events in the data stream). In this paper we show how to map the data stream processing phases (from data generation to final results) to a software chain architecture, which comprises five main components: sensor, extractor, parser, formatter and outputter. We exemplify the approach using the Yahoo!S4 for processing the Big data Stream from FlightRadar24 global flight monitoring system.

关键词： Big data Stream Real-time Analytics Software Chain Architecture massive data processing Generic Log Adapter Yahoo!S4 Global Flight Monitoring System FlightRadar24

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The Improved CF Model Analysis With massive data processing

The Improved CF Model Analysis With Massive Data Processing

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2010 IEEE International Conference on Intelligent Computing and Intelligent Systems(2010 IEEE 智能计算与智能系统国际会议 ICIS 2010)

作者： Beizhan Wang Zhenpeng Zhan Huiqun Chen Software School of Xiamen University Xiamen China

in the uncertain reasoning domain, there are many methods to process uncertain reasoning. One of them is CF model analysis;it has achieved a good applying from the MYCIN system. But there are also some problems in the using of this theory, for example, It's susceptible to negative evidence and even it may fully negate the effect taken by core evidence due to unimportant negative evidence. So in this paper, we put forward the improved CF model to fix some problem, in the other way, we take with massive data processing for improving the accuracy rate. The decision analysis list is reasoned by both the improved CF model and massive data processing. And this model has been applied by a business system.

关键词： CF model uncertainly reasoning massive data processing weight matrix algorisim

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