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检索条件"任意字段=3rd International Conference on Soft Computing in Data Science, SCDS 2017"

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Analysis of User's Abnormal Behavior Based on Behavior Sequence in Enterprise Network 3rd

Analysis of User's Abnormal Behavior Based on Behavior Seque...

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3rd international conference on Cloud computing and Security (ICCCS)

作者： Guan, Haichao Li, Huakang Sun, Guozi Nanjing Univ Posts & Telecommun Jiangsu Key Lab Big Data & Secur & Intelligent Pr Sch Comp Sci & Technol Sch Software Nanjing 210003 Jiangsu Peoples R China

ISBN: (纸本)9783319685052;9783319685045

There are many abnormal user behavior in the enterprise network environment, how to monitor it effectively is a hot research hotspot. At present, the analysis of abnormal behavior is mainly through the means of traffic monitoring, but there is no precise definition and related research on the behavior of enterprise network users. Therefore, the paper propose a model to analyze the abnormal behavior of enterprise network users. First, the data from the monitoring log of enterprise network should be pre-processing and the user behavior are serializing;then, for each user behavior sequence in sequence databases, calculating the user behavior similarity and correlation coefficient in a week by the improved algorithm;finally, comparing the similarity and the correlation coefficient between users and finding the user abnormal behavior. In this paper, we use the model to verify the feasibility of the internal network of the company, and find out the user's abnormal behavior.

关键词： Behavior sequence Abnormal behavior analysis Behavior similarity

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Coverless Text Information Hiding Method Using the Frequent Words Distance 3rd

Coverless Text Information Hiding Method Using the Frequent ...

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3rd international conference on Cloud computing and Security (ICCCS)

作者： Zhang, Jianjun Xie, Yicheng Wang, Lucai Lin, Haijun Hunan Univ Coll Comp Sci & Elect Engn Changsha 410080 Hunan Peoples R China Hunan Normal Univ Coll Engn & Design Changsha 410081 Hunan Peoples R China

ISBN: (纸本)9783319685052;9783319685045

The attackers may discover the existence of the secret information or even get it by analyzing the cover's statistical characteristics, changes of which often occur due to the embedding. In this paper, a novel coverless text information hiding method was proposed. By using the words rank map and the frequent words distance, normal texts containing the secret information could be retrieved from the text database, and will be sent to the receiver without any modification. Because the embedding is not needed, the proposed method could be able to escape from almost all state-of-the-art steganalysis methods.

关键词： Coverless information hiding The rank map The frequent words distance The big data

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Supporting data communications in IoT-enabled waste management 17th

Supporting data communications in IoT-enabled waste manageme...

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17th international conference on Next Generation Teletraffic and Wired/Wireless Advanced Networks and Systems, NEW2AN 2017, 10th conference on Internet of Things and Smart Spaces, ruSMART 2017 and 3rd international Workshop on Nano-scale computing and Communications, NsCC 2017

作者： Fedchenkov, Petr Zaslavsky, Arkady Medvedev, Alexey Anagnostopoulos, Theodoros Sosunova, Inna Sadov, Oleg Department of Infocommunication Technologies ITMO University Saint Petersburg197101 Russia CSIRO Computational Informatics CSIRO Box 312 Clayton SouthVIC3169 Australia Faculty of Information Technology Monash University Melbourne Australia Research and Education Ordnance Survey SouthamptonSO16 0AS United Kingdom

ISBN: (纸本)9783319673790

The Internet of Things (IoT) enables Smart Cities with novel services. Such services demand low power, high throughput and low-cost sensor data collection technologies. The number of devices, their variety, the breadth of their distribution, and the number of standards are continuously increasing. In this paper, we explore and critically analyze emerging IoT communication technologies. LoRaWAN has been selected for deployment in the smart waste management system (SWM) for collecting data from smart garbage bins. The paper proposes an architecture for SWM data collection and delivery as part of St. Petersburg pilot of Horizon-2020 bIoTope project. Extensive experiments with actual sensors and smart garbage bins were conducted for stress-testing the LoRaWAN technology, analyzing data rates and power consumption. The paper concludes with lessons learned and LoRaWAN wider deployment feasibility and improvements discussion. © 2017, Springer international Publishing AG.

关键词： Internet of things

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Design of a certificateless designated server based searchable public key encryption scheme 3rd

Design of a certificateless designated server based searchab...

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3rd international conference on Mathematics and computing, ICMC 2017

作者： Hafizul Islam, S.K. Obaidat, Mohammad S. Rajeev, Varun Amin, Ruhul Indian Institute of Information Technology KalyaniWest Bengal741235 India University of Jordan Amman Jordan Fordham University BronxNY United States EdgeVerve Systems Limited BengaluruKarnataka560100 India Thapar University PatialaPunjab147004 India

ISBN: (纸本)9789811046414

In the present day, applications of cloud computing is growing exponentially and clients are inclined to use the cloud server to store sensitive data, which is indexed by important or related keyword(s) available in the data. Once the data is stored, the client supplies some keywords to the cloud server and requests the corresponding data. If the data is stored in plaintext form, data privacy will be violated. Thus the client encrypts the data along with the realted keywords, and then stores the ciphertext in the cloud server. Encryption of data maintains the confidentiality, but this makes keyword search difficult. To solve this issue, designated server based public key encryption with keyword search (dPEKS) scheme is used. In dPEKS scheme, to get the encrypted data, the client computes a trapdoor related to a relevant keyword, and sends it to the cloud server, which then gives the ciphertext to the client provided that the trapdoor is verified. Hence, the client gets the data from the ciphertext. However, an adversary will not get any information on the data or the keywords. A certificatelessdPEKS (CL-dPEKS) scheme is proposed in this paper. It provides indistinguishability to the ciphertext and trapdoor, and resilience to off-line keyword guessing attack. The Computational Diffie-Hellman (CDH) problem and Bilinear DiffieHellman (BDH) problem keep the proposed scheme secure. © Springer Nature Singapore Pte Ltd. 2017.

关键词： Sensitive data

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About crawling scheduling problems 3

About crawling scheduling problems

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3rd international conference BOINC-Based High Performance computing: Fundamental Research and Development, BOINC:FAST 2017

作者： Pechnikov, Andrey A. Chernobrovkin, Denis I. Nwohiri, Anthony M. Institute of Applied Mathematical Research of Karelian Research Centre of the Russian Academy of Sciences Petrozavodsk Russia DataArt Inc St. Petersburg Russia Department of Computer Science Faculty of Science University of Lagos Nigeria

This paper investigates the task of scheduling jobs across several servers in a software system similar to the Enterprise Desktop Grid. One of the features of this system is that it has a specific area of action – collects outbound hyperlinks for a given set of websites. The target set is scanned continuously (and regularly) at certain time intervals. data obtained from previous scans are used to construct the next scanning task for the purpose of enhancing efficiency (shortening the scanning time in this case). A mathematical model for minimizing the scanning time for a batch mode is constructed;an approximate algorithm for the solution of the model is proposed. A series of experiments are carried out in a real software system. The results obtained from the experiments enabled to compare the proposed batch mode with the known round robin mode. This revealed the advantages and disadvantages of the batch mode. Copyright © by the paper's authors. Copying permitted for private and academic purposes.

关键词： Scanning

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Transfer of multimedia data via LoRa 17th

Transfer of multimedia data via LoRa

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作者： Kirichek, Ruslan Pham, Van-Dai Kolechkin, Aleksey Al-Bahri, Mahmood Paramonov, Alexander State University of Telecommunication St. Petersburg Russia 6 Miklukho-Maklaya St. Moscow Russia

ISBN: (纸本)9783319673790

This article provides the results of the multimedia data transmission parameters research by LoRa using, in particular the results of images and voice transmission using the fragment of the model network in the Internet of Things Laboratory SPbSUT. During the series of experiments there was noticed the LoRa radio modules performance variation of different parameters (Bandwidth, Spreading Factor and Coding Rate), which have affected on the time and quality of image transmission. For image compression were used JPEG and JPEG 2000 methods, which have allowed to achieve an acceptable compression and image reconstruction while transmitting in the low-speed network. In the course of the experiment, the images were transferred from a camera mounted on a quadrocopter at distance of several kilometers. We considered such parameters as the time of data transfer, packet loss, estimation of the images quality obtained on the basis of subjective and objective methods. For voice compression, the A-law method was used, which allowed to compress the frame size by 4 times. Experiments of real-time speech transmission were conducted in different languages and evaluated by the experts. During the results analyzing there were defined the lower subjective score for Arabic, and the higher scores for English and Vietnamese. In conclusion, this article provides the results of the quantitative and qualitative dimensions evaluation and presents directions for the further research. © 2017, Springer international Publishing AG.

关键词： Internet of things

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An improved harmony search algorithm for protein structure prediction using 3D off-lattice model 3rd

An improved harmony search algorithm for protein structure p...

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Proceedings of the 3rd international conference on Harmony Search Algorithm, ICHSA 2017

作者： Jana, Nanda Dulal Sil, Jaya Das, Swagatam Department of IT National Institute of Technology Durgapur713209 India Department of CST Indian Institute of Engineering Science and Technology Shibpur711103 India ECS Unit Indian Statistical Institute Kolkata700108 India

ISBN: (纸本)9789811037276

Protein structure prediction (PSP) is an important research area in bio-informatics for its immense scope of application in drug design, disease prediction, name a few. Structure prediction of protein based on sequence of amino acids is a NP-hard and multi-modal optimization problem. This paper presents an improved harmony search (ImHS) algorithm to solve the PSP problem based on 3D off lattice model. In the proposed method, the basic harmony search (HS) algorithm combined with dimensional mean based perturbation strategy to avoid premature convergence and enhance the capability of jumping out from the local optima. The experiments are carried out on a set of real protein sequences with different length collected from the Protein data Bank (PDB) to validate the efficiency of the proposed method. Numerical results show that the ImHS algorithm significantly outperforms compared to other algorithms on protein energy minimization. © Springer Nature Singapore Pte Ltd. 2017.

关键词： Forecasting

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Detect incorrect triples in knowledge base based on triple confidence evaluation 17

Detect incorrect triples in knowledge base based on triple c...

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3rd international conference on Industrial and Business Engineering, ICIBE 2017

作者： Xie, Haihua Lu, Xiaoqing Tang, Zhi Huang, Xiaojun Institute of Computer Science and Technology Peking University Beijing China State Key Laboratory of Digital Publishing Technology Peking University Founder Group Co. LTD. Beijing China Postdoctoral Workstation of the Zhongguancun Haidian Science Park North Main Street Zhongguancun Haidian District Beijing100871 China Institute of Computer Science and Technology Peking University North Main Street Zhongguancun Haidian District Beijing100871 China State Key Laboratory of Digital Publishing Technology Peking University Founder Group Co. LTD. North Main Street Zhongguancun Haidian District Beijing100871 China

ISBN: (纸本)9781450353519

The knowledge base is an important form of data storage and organization in the fields of knowledge service, and it is the basis of knowledge representation learning. The accuracy of the contents in the knowledge base determines the effectiveness of knowledge service applications. This study proposes a generic computational methodology to evaluate the confidence level of triples in knowledge bases and detect potentially incorrect ones for further verification. In our methodology, the confidence of a triple is evaluated based on weighted feature words that are able to characterize the subject-object relation embedded in the triple, and the feature words are extracted from a corpus of natural language sentences using statistical and natural language processing techniques. Based on the calculated confidence values of triples, incorrect triples are detected using machine-learning-based classification. An experiment on a data set of industry applications has been conducted to demonstrate the workflow of evaluating triple confidence and detecting in-correct triples using our methodology. © 2017 Association for computing Machinery.

关键词： Knowledge representation

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An Improved Artificial Immune Network Based on the Secondary Immune Mechanism for data Clustering 3rd

An Improved Artificial Immune Network Based on the Secondary...

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3rd international conference on Cloud computing and Security (ICCCS)

作者： Li, Yangyang Hou, Xiaoju Jiao, Licheng Xue, Yu Xidian Univ Key Lab Intelligent Percept & Image Understanding Int Res Ctr Intelligent Percept & Computat Minist EducJoint Int Res Lab Intelligent Percept Xian 710071 Shanxi Peoples R China NUIST Nanjing Jiangsu Peoples R China

ISBN: (纸本)9783319685052;9783319685045

data clustering is a typical method in data mining. As a effective algorithm for clustering, the Artificial Immune Network is inspired by natural immune system can reflect the structure of the given dataset, filter redundancy and cluster datasets without the number of clusters, so far it is widely used. However, it can't effectively identify the noise nodes, the running time is long and too much parameters are set in improved algorithms. In order to shorten running time and reduce the impact of parameters, this paper proposes an improved artificial immune network based on the secondary immune mechanism. The Clone operator and Mutation operator are replaced by Competition Selection operator and Competition Selection strategy, which are inspired by the resource limited artificial immune system. Because the algorithm can reach a stable convergence only through two times, so it greatly reduce the running time;and can effectively identify the noise nodes due to the introduction of stimulation level. A number of datasets including artificial datasets and real-world datasets are used to evaluate the performance of the proposed algorithm and the other existing clustering algorithms, such as K-means, FCM, SC, aiNet and FCAIN. The simulation results indicate that the proposed artificial immune network algorithm is an effective and efficient method in data clustering.

关键词： Artificial immune network data clustering Competition selection operator Secondary immune mechanism

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SWM-PnR: ontology-based context-driven knowledge representation for IoT-enabled waste management 17th

SWM-PnR: ontology-based context-driven knowledge representat...

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作者： Sosunova, Inna Zaslavsky, Arkady Anagnostopoulos, Theodoros Fedchenkov, Petr Sadov, Oleg Medvedev, Alexey Department of Infocommunication Technologies ITMO University Kronverkskiy pr. 49 St. Petersburg Russia Digital Data61 CSIRO Box 312 Clayton SouthVIC3169 Australia Research and Education Ordnance Survey SouthamptonSO16 0AS United Kingdom Caulfield School of Information Technology Monash University Melbourne Australia

ISBN: (纸本)9783319673790

Using knowledge-based and semantic technologies in IoT is a very active research and promising area. This paper proposes a method of ontology-based context-driven knowledge representation for IoT-enabled hard waste management as part of a wider international project that aims at building IoT ecosystems for smart cities. The paper presents the development of the waste management ontology, rules, and proposes a multistage data processing method that allows extracting knowledge about specific nontrivial situations on its basis. The paper describes implementation of the proposed system as a web application, where the content types are based on ontology, and data processing occurs according to the proposed algorithm. Benefits of the proposed knowledge-based system are discussed and demonstrated. The proposed approach will significantly improve monitoring and management of waste collection, route planning, and problem reporting. © 2017, Springer international Publishing AG.

关键词： Ontology

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