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Application of Ensemble Learning in DDoS Detection

Application of Ensemble Learning in DDoS Detection

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2019 7th international conference on Machinery,Materials and computing technology(ICMMCT 2019)

作者： Yun Feng Fu Kun Jiangnan University Department of Internet of Things Engineering

A growing number of internet of things(IoT) devices are appearing on the *** these devices are facing more and more security risks,such as distributed denial of service(DDoS) *** recent years,the scale of DDoS attacks is getting larger and larger,and each DDoS attack will cause huge *** motivates the development of new techniques to automatically detect attack traffic and improve detection accuracy as much as possible,so as to reduce *** paper demonstrates several ensemble learning methods which show a higher accuracy DDoS detection in IoT network traffic than using a single machine learning *** results show that ensemble learning can complement the limitations of using a single machine learning method to improve the DDoS detection accuracy.

关键词： internet of things Anomaly Detection DDoS Machine Learning Feature Engineering Ensemble Learning

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A Preemptive Hybrid Approach to Minimum Spanning Tree Restoration in Large Mesh SDN Networks

A Preemptive Hybrid Approach to Minimum Spanning Tree Restor...

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IEEE international conference on Future internet of things and Cloud Workshops (FiCloudW)

作者： Wayne Collymore School of Computing and Digital Technology Birmingham City University Birmingham UK

ISBN: (数字)9781728144115

ISBN: (纸本)9781728144122

Achieving high levels of network resiliency has long been a major objective for data centre and service providers. Recently, Software Defined Networking (SDN) has arrived with the ability to extend centralised programmability, control and management to all aspects of networking. For traditional TCP/IP networks, due to the close coupling of the control and data plane on network devices, protocols that provide recovery and restoration operate effectively in a distributed manner. In practice a programmed SDN controller is at the heart of any SDN deployment. SDN controllers offers opportunities for algorithms to operate at a logically global or centralised level. Shifting distributed protocols away from localised switches or routers to a centralised controller effectively creates a level playing field for algorithms. A global view of the entire network is now available not only to the network programmer or manager, but also to all the algorithms programmed at the controller. Although a central view may be an advantage, little is known about the behaviour of different restoration algorithms and their recovery in a centralised controller when operating under a worst case environment such a scaled wired mesh SDN topology. this paper presents the SDN implementation and analysis of a range of Minimum Spanning Tree (MST) algorithms, their key performance metrics are evaluated and based on these results a preemptive approach to path restoration is proposed. Initial results of the approach show considerable time savings in the initial stages of building an MST.

关键词： centralised control computer centres computer network management IP networks software defined networking telecommunication network routing telecommunication network topology telecommunication switching telecommunication traffic transport protocols trees ( INTEGRATED SHIP CONTROL telecommunication switching telecommunication network topology Computer Network Management telecommunication network routing transport protocols internet Protocol networks telecommunication traffic Controllers algorithms restoration Performance metrics Spanning tree trees Preemptive

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CLOSER 2017 - Proceedings of the 7th international conference on Cloud computing and Services Science

CLOSER 2017 - Proceedings of the 7th International Conferenc...

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7th international conference on Cloud computing and Services Science, CLOSER 2017

ISBN: (纸本)9789897582431

the proceedings contain 84 papers. the topics discussed include: a CKAN plugin for data harvesting to the Hadoop distributed file system;a computation- and network-aware energy optimization model for virtual machines allocation;cost optimization on public cloud provider for big geospatial data;reconfigurable and adaptive spark applications;managing and unifying heterogeneous resources in cloud environments;an ontological template for context expressions in attribute-based access control policies;highly reconfigurable computing platform for high performance computing infrastructure as a service: Hi-IaaS;combining TOSCA and BPMN to enable automated cloud service provisioning;anything to topology - a method and system architecture to topologize technology-specific application deployment artifacts;ROP defense in the cloud through live text page-level re-ordering - the LITPR system;a framework for certification of large-scale component-based parallel computing systems in a cloud computing platform for HPC services;recovery-oriented resource management in hybrid cloud environments;component-wise application migration in bidimensional cross-cloud environments;uncertainty-aware optimization of resource provisioning, a cloud end-user perspective;DISCO: a dynamic self-configuring discovery service for semantic web services;and internet of things out of the box: using TOSCA for automating the deployment of IoT environments.

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A review of cloud computing simulation platforms & related environments 7

A review of cloud computing simulation platforms & related e...

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7th international conference on Cloud computing and Services Science, CLOSER 2017

作者： Byrne, James Svorobej, Sergej Giannoutakis, Konstantinos M. Tzovaras, Dimitrios Byrne, P.J. Östberg, Per-Olov Gourinovitch, Anna Lynn, theo Irish Centre for Cloud Computing and Commerce Dublin City University Glasnevin Dublin 9 Ireland Centre for Research and Technology Hellas Information Technologies Institute 6th km Xarilaou-Thermi Thessaloniki57001 Greece Dept. Computing Science and HPC2N Umeå University UmeaSE-901 87 Sweden

ISBN: (纸本)9789897582431

Recent years have seen an increasing trend towards the development of Discrete Event Simulation (DES) platforms to support cloud computing related decision making and research. the complexity of cloud environments is increasing with scale and heterogeneity posing a challenge for the efficient management of cloud applications and data centre resources. the increasing ubiquity of social media, mobile and cloud computing combined with the internet of things and emerging paradigms such as Edge and Fog computing is exacerbating this complexity. Given the scale, complexity and commercial sensitivity of hyperscale computing environments, the opportunity for experimentation is limited and requires substantial investment of resources both in terms of time and effort. DES provides a low risk technique for providing decision support for complex hyperscale computing scenarios. In recent years, there has been a significant increase in the development and extension of tools to support DES for cloud computing resulting in a wide range of tools which vary in terms of their utility and features. through a review and analysis of available literature, this paper provides an overview and multi-level feature analysis of 33 DES tools for cloud computing environments. this review updates and extends existing reviews to include not only autonomous simulation platforms, but also on plugins and extensions for specific cloud computing use cases. this review identifies the emergence of CloudSim as a de facto base platform for simulation research and shows a lack of tool support for distributed execution (parallel execution on distributed memory systems). ©2017 by SCITEPRESS - Science and technology Publications, Lda. All rights reserved.

关键词： Fog computing

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Adapting enterprise security approaches for evolving cloud processing and networking models 7th

Adapting enterprise security approaches for evolving cloud p...

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7th international conference on Mathematical Methods, Models and Architectures for Computer Network Security, MMM-ACNS 2017

作者： Hutchison, Andrew Department of Computer Science University of Cape Town Cape Town7700 South Africa

ISBN: (纸本)9783319651262

With the advent of public cloud services, enterprise are moving to adopt the lower cost, more flexible, scalable public cloud offerings like OTC, AWS and Azure. Simultaneously they are adapting their network models to move away from centralized enterprise QoS networks (with internet break out from a single or few large enterprise gateways) in favor of lower cost, direct offloading of corporate traffic from company locations via local and distributed internet service providers. Using this model enterprises are also accessing cloud services from multiple entry points, and this completely changes the enterprise security deployment landscape. As an additional ongoing trend, the networking of physical devices is bringing a whole new ‘operational technology’ domain to the enterprise space, and a new approach to enterprise security is therefore required. In this paper the drivers of change in approaches to security for public cloud computing are presented, considering also the responsibilities of the customer and of the cloud service provider and the component which enterprises still need to focus on. In addition, the network model for security is explained and considered, with the new distributed deployment zone for security as described. Cyber physical/IoT type systems are also then discussed as an additional security landscape over which enterprises increasingly need to take special care. © Springer international Publishing AG 2017.

关键词： internet service providers

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the Research and Application of the Power Big Data 7

The Research and Application of the Power Big Data

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7th international conference on Electronics and Information Engineering (ICEIE)

作者： Zhang, Suxiang Zhang, Dong Zhang, Yaping Cao, Jinping Xu, Huiming State Grid Informat & Telecommun Branch Beijing 100761 Peoples R China State Power Econ Res Inst Beijing 102209 Peoples R China State Grid Corp China Beijing 100031 Peoples R China

ISBN: (数字)9781510610811

ISBN: (纸本)9781510610811

Facing the increasing environment crisis, how to improve energy efficiency is the important problem. Power big data is main support tool to realize demand side management and response. With the promotion of smart power consumption, distributed clean energy and electric vehicles etc get wide application;meanwhile, the continuous development of the internet of things technology, more applications access the endings in the grid power link, which leads to that a large number of electric terminal equipment, new energy access smart grid, and it will produce massive heterogeneous and multi-state electricity data. these data produce the power grid enterprise's precious wealth, as the power big data. How to transform it into valuable knowledge and effective operation becomes an important problem, it needs to interoperate in the smart grid. In this paper, we had researched the various applications of power big data and integrate the cloud computing and big data technology, which include electricity consumption online monitoring, the short-term power load forecasting and the analysis of the energy efficiency. Based on Hadoop, HBase and Hive etc., we realize the ETL and OLAP functions;and we also adopt the parallel computing framework to achieve the power load forecasting algorithms and propose a parallel locally weighted linear regression model;we study on energy efficiency rating model to comprehensive evaluate the level of energy consumption of electricity users, which allows users to understand their real-time energy consumption situation, adjust their electricity behavior to reduce energy consumption, it provides decision-making basis for the user. With an intelligent industrial park as example, this paper complete electricity management. therefore, in the future, power big data will provide decision-making support tools for energy conservation and emissions reduction.

关键词： energy efficiency cloud computing big data smart power consumption

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the Implementation of Air Pollution Monitoring Service Using Hybrid Database Converter 7

The Implementation of Air Pollution Monitoring Service Using...

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7th international conference on Cloud computing and Big Data (CCBD)

作者： Sun, Pei-Lun Weng, Jia-Yow Yang, Chao-Tung Chen, Shuo-Tsung Liu, Jung-Chun Tunghai Univ Dept Comp Sci Taichung 40704 Taiwan

ISBN: (纸本)9781509035557

In this work, the proposed Intelligent Indoor Environment Monitoring System in Cloud (iDEMS) combines environmental sensors with ZigBee wireless sensor network technology to store and process environmental data in HBase. the environmental data collected by sensors will be stored and processed in the cloud using HBase, which supports storing large amounts of data, free to easily increase storage space. the iDEMS also can compute through Hadoop MapReduce for the HBase database to do distributed computing or cloud computing to process environmental records. In this part, we particularly Take great effort to improve the performance of read and write in big data and provide functions, including information searching, data filtering, and basic statistics. In addition, iDEMS integrated with an intelligent control socket to effectively improve the air quality of indoor environment and reduce the concentration of pollutants in the environment to keep people far from pollutants. Finally, IDEMS presents the environmental information by a web-based monitoring platform so that users can use the internet to monitor the environment and adjust the indoor environment at any time, any place as wanted.

关键词： iDEMS Environmental Sensors Cloud computing Big Data HBase

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distributed multi-user, multi-key searchable encryptions resilient fault tolerance 7th

Distributed multi-user, multi-key searchable encryptions res...

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7th international conference on the theory, Technologies and Applications of Trusted Systems, INTRUST 2015

作者： Zhu, Huafei School of Computer and Computing Science Zhejaing University City College Hangzhou310015 China

ISBN: (纸本)9783319315492

In this paper, a construction of distributed multi-user, multi-key searchable encryptions is proposed and analyzed. Our scheme leverages a combination of the Shamir’s threshold secret key sharing, the Pohlig-Hellman function and the ElGamal encryption scheme to provide high reliability with limited storage overhead. It achieves the semantic security in the context of the keyword hiding, the search token hiding and the data hiding under the joint assumptions that the decisional Diffie-Hellman problem is hard and the pseudo-random number generator deployed is cryptographically strong. © Springer international Publishing Switzerland 2016.

关键词： Fault tolerance

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7th international conference on Trusted Systems, INTRUST 2015

7th International Conference on Trusted Systems, INTRUST 201...

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7th international conference on the theory, Technologies and Applications of Trusted Systems, INTRUST 2015

ISBN: (纸本)9783319315492

the proceedings contain 15 papers. the special focus in this conference is on Encryptions, Signatures and Encryptions and Signatures. the topics include: Privacy-preserving anomaly detection across multi-domain for software defined networks;distributed multi-user, multi-key searchable encryptions resilient fault tolerance;another look at aggregate signatures;universally composable oblivious database in the presence of malicious adversaries;public key encryption with distributed keyword search;a signature generation approach based on clustering for polymorphic worm;computational soundness of uniformity properties for multi-party computation based on LSSS;attribute-based signatures with controllable linkability;a causality-based model for describing the trustworthiness of a computing device;an application-oriented efficient encapsulation system for trusted software development;research on trusted bootstrap based on the universal smart card;efficient implementation of AND, OR and NOT operators for ABCs;application of NTRU using group rings to partial decryption technique;a RBAC-based method for intercepting and processing malicious applications in android platform;an audit log protection mechanism based on security chip.

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Public key encryption with distributed keyword search 7th

Public key encryption with distributed keyword search

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7th international conference on the theory, Technologies and Applications of Trusted Systems, INTRUST 2015

作者： Kuchta, Veronika Manulis, Mark Department of Computing University of Surrey Guildford United Kingdom

ISBN: (纸本)9783319315492

In this paper we introduce threshold Public Key Encryption with Keyword Search (TPEKS), a variant of PEKS where the search procedure for encrypted keywords is distributed across multiple servers in a threshold manner. TPEKS schemes offer stronger privacy protection for keywords in comparison to traditional PEKS schemes. In particularly, they prevent keyword guessing attacks by malicious servers. this protection is not achievable in a single-server PEKS setting. We show how TPEKS can be built generically from any anonymous Identity-Based threshold Decryption (IBTD), assuming the latter is indistinguishable, anonymous and robust. In order to instantiate our TPEKS construction we describe an efficient IBTD variant of the Boneh-Franklin IBE scheme. We provide an appropriate security model for such IBTD schemes and give an efficient construction in the random oracle model. TPEKS constructions are particularly useful in distributed cloud storage systems where none of the servers alone is sufficiently trusted to perform the search procedure and where there is a need to split this functionality across multiple servers to enhance security and reliability. © Springer international Publishing Switzerland 2016.

关键词： distributed cloud

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