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检索条件"任意字段=13th International Conference on Distributed Computing and Internet Technology, ICDCIT 2017"

共 228 条记录，以下是1-10 订阅

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13th international conference on distributed computing and internet technology, icdcit 2017

13th International Conference on Distributed Computing and I...

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13th international conference on distributed computing and internet technology, icdcit 2017

ISBN: (纸本)9783319504711

the proceedings contain 20 papers. the special focus in this conference is on distributed computing and internet technology. the topics include: Gathering multiple robots in a ring and an infinite grid;scalable IQRA_IG algorithm;an iterative mapreduce approach for reduct computation;simulation of mapreduce across geographically distributed datacentres using cloudsim;revamping the frequency and computational time of RTOS Task - power dissipation;analyzing protocol security through information-flow control;efficient image authentication scheme using genetic algorithms;privacy preserving signcryption scheme;a crawler for seeking and crawling malicious websites;innovative mobile number tracking system;a domain specific language for clustering and designing a secure data retrieval strategy using NoSQL database.

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distributed computing and internet technology: 13th international conference, icdcit 2017 Bhubaneswar, India, January 13–16, 2017 proceedings 13th

Distributed Computing and Internet Technology: 13th Internat...

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13th international conference on distributed computing and internet technology, icdcit 2017

作者： Krishnan, Padmanabhan Krishna, P. Radha Parida, Laxmi Oracle Labs BrisbaneQLD Australia Infosys Limited Hyderabad India IBM Thomas J. Watson Research Center Yorktown HeightsNY United States

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Attribute-based Encryption with Flexible Revocation for IoV 18

Attribute-based Encryption with Flexible Revocation for IoV

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18th international conference on Future Networks and Communications (FNC) / 20th international conference on Mobile Systems and Pervasive computing (MobiSPC) / 13th international conference on Sustainable Energy Information technology (SEIT)

作者： Chen, Ruoyu Li, Yuhong Rahmani, Rahim Beijing Univ Posts & Telecommun Sch Comp Sci Beijing 100876 Peoples R China Stockholm Univ Dept Comp & Syst Sci S-16407 Stockholm Sweden

Attribute-based encryption (ABE) has been used to provide data confidentiality and fine-grained access control in the internet of Vehicles (IoV). However, the attributes of vehicles in IoV might change frequently due to the movements of vehicles. thus, the invalid attributes need to be revoked in time and efficiently to ensure the security of the system. In this paper, we propose a data sharing scheme based on ABE for IoV. By using a binary tree and attribute version keys, flexible revocation can be achieved for IoV. Moreover, the ciphertext can be stored on clouds, and the distribution and of attribute keys can be realized by distributed attribute authorities. We performed the security analysis and proved the security of the proposed scheme. the results showed that the proposed scheme has lower average computing overhead in terms of attribute revocations compared with other schemes based on ABE, and can satisfy the performance requirement data sharing for IoV. (c) 2023 the Authors. Published by Elsevier B.V.

关键词： internet of vehicles attribute-based encryption revocation data sharing

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Enhanced DDoS Defense in SDN: Double-Layered Strategy with Blockchain Integration 13

Enhanced DDoS Defense in SDN: Double-Layered Strategy with B...

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13th IEEE international conference on Communications, Circuits and Systems (ICCCAS)

作者： Tian, Jialin Shu, Zhaogang Chen, Shuwu Xie, Haihui Liu, Xiaolong Qiu, Caiyu Fujian Agr & Forestry Univ Comp & Informat Coll Fuzhou Peoples R China

ISBN: (纸本)9798350386288;9798350386271

With the development of technologies such as cloud computing, big data, and the internet of things (IoT), Software-Defined Networking (SDN) has emerged as a novel network architecture in today's internet era. It can separate the control plane from the data plane, allowing rapid packet forwarding in the internet through a centralized controller. However, SDN environments are vulnerable to traditional distributed Denial of Service (DDoS) attacks. this paper proposes a new dual layer strategy to try to mitigate the question. First, by using blockchain technology and smart contract in the northbound interface to store the flow tables required for SDN networks, security is increased. then, we use the Token Bucket algorithm and Time Window algorithm to build the first-tier strategy to defend against obvious DDoS attacks. To detect unobvious DDoS attacks, we design the second-tier strategy that uses a composite data feature correlation coefficient calculation method and the Isolation Forest algorithm to perform binary classification on data, thereby identifying abnormal traffic. We use the currently publicly available DDoS dataset CIC-DDoS2019 for experimental verification. the results show that using this strategy in SDN networks results in an average deviation of data Round-Rip Time (RTT) approximately 38.86% lower than in the original SDN networks without this strategy. Additionally, the accuracy of DDoS attack identification reaches 91.29%. this means that with the implementation of this strategy, DDoS attacks can be effectively identified without compromising the stability of data transmission in SDN network environments.

关键词： Software Defined Networks distributed Denial of Service Blockchain Machine learning

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Big Data Framework Deployment and Solution Design of Agricultural internet of things 13

Big Data Framework Deployment and Solution Design of Agricul...

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13th international conference on Information technology in Medicine and Education, ITME 2023

作者： Kang, Lihui Xie, Dong Peng, Gang Yue, Kejuan Wang, Jiayue Wang, Mingming School of Information Hunan University of Humanities Science and Technology Loudi China School of Computer Science Hunan First Normal University Changsha China

ISBN: (纸本)9798350319156

this paper introduces the overall design scheme of agricultural internet of thing (IoT) system and the design framework of software functional modules. By analyzing the MapReduce computing framework of Hadoop, HDFS distributed file storage system, resource allocation and invocation principle of YARN, and the operation framework of Spark. We build the overall structure of the Hadoop-based Spark computing framework and deploy the Hadoop-based Spark cluster. © 2023 IEEE.

关键词： Big data

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Evaluating Indicator Weights for Satellite internet Security Assessment: an Approach to Combining Rough Set with Fuzzy Hierarchical Analysis 21

Evaluating Indicator Weights for Satellite Internet Security...

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21st IEEE international Symposium on Parallel and distributed Processing with Applications, 13th IEEE international conference on Big Data and Cloud computing, 16th IEEE international conference on Social computing and Networking and 13th international conference on Sustainable computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Lu, Yuming Li, Fenghua Wen, Yitong Fang, Liang Guo, Shoukun Li, Zifu Institute of Information Engineering Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences School of Cyber Security Beijing China

ISBN: (纸本)9798350329223

In order to reduce the impact of increasingly sophisticated cyberattacks on the satellite internet security, it is necessary to assess the satellite internet security. Most of existing assessment schemes for network security risk mainly rely on expert knowledge to subjectively weight assessment indicator and quantify security risks, thus leading to results of assessment which are not objective. To address this problem, combining rough set with fuzzy hierarchy analysis, we propose a combination scheme to evaluate the indicator weights for assessing the satellite internet security. First, from the perspective of IPDR model, we propose IPDR-based evaluation indicator system, and fuzzy hierarchy analysis is designed to fuse the indicator scores of more than one experts into one final value and obtain the subjective weight. Second, rough set theory is adopted to reduce indicators and correct the subjective weight obtained in the first step, thus obtaining the comprehensive weight. Finally, a series of experiments are carried out to validate our scheme. © 2023 IEEE.

关键词： Rough set theory

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Fog-enabled Intelligent Network Intrusion Detection Framework for internet of things Applications 13

Fog-enabled Intelligent Network Intrusion Detection Framewor...

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13th international conference on Cloud computing, Data Science and Engineering, Confluence 2023

作者： Bebortta, Sujit Das, Saneev Kumar Chakravarty, Sujata Ravenshaw University Department of Computer Science Cuttack India Centurion University of Technology and Management Department of Computer Science and Engineering Bhubaneswar India

ISBN: (纸本)9781665462631

With the continual growth in internet of things (IoT), several concerns regarding the security and privacy of the connected IoT devices arise. Attacks like distributed Denial of Service (DDoS) and probing attacks cause specific damage to the underlying network infrastructure. In this paper, we propose an Equilibrium Optimization-based Artificial Neural Network (EO-ANN) Framework for detection of network attacks pertaining to IoT systems. the proposed approach leverages the dynamic mass balance technique to obtain the optimal number of features for training the ANN algorithm. To evaluate the effectiveness of the proposed EO-ANN model, its performance is compared with several baseline prediction models. Experimental findings demonstrate that the suggested approach has precision and recall values of 0.9389 and 0.9248, respectively, and an F1-score of 0.9371, which results in an overall accuracy of 93.4731%. In addition to these performance requirements, the model was implemented over the Fog computing platform and the corresponding metrics viz., delay and energy consumption were obtained towards execution of different workloads. Hence, the experimentations offered in this study show that the suggested EO-ANN model is effective and that it can be successfully validated for classifying network intrusion in densely deployed IoT networks. © 2023 IEEE.

关键词： internet of things

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Partitioning-based Active Trust Mechanism in Cloud-Edge-Device Collaborative Data Collection 21

Partitioning-based Active Trust Mechanism in Cloud-Edge-Devi...

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作者： Xia, Zhuoqun Wang, Ziyu Liu, Xiao Changsha University of Science and Technology School of Computer and Communication Engineering Changsha China Guangxi University School of Computer Electronics and Information Nanning China

ISBN: (纸本)9798350329223

Since the open character of the internet of things (IoT), IoT devices are vulnerable to various attacks. Compromised devices may maliciously provide unreliable data to the cloud. Furthermore, existing trust evaluation models struggle to balance data security needs across different regions. To address this issue, the paper proposes a partition-based active trust mechanism (PATM). this PATM scheme mainly includes the following parts: First, the region is divided into subregions, and evaluations are conducted for the indicators of each subregion. Mechanism modeling and fuzzy analytic hierarchy process are used to analyze the impact of each indicator on the sensitivity of subregions. Second, the direct estimation method is utilized to estimate the demand for active detection routing based on the sensitivity of subregions. then, the number of operations of malicious nodes is increased through the high-frequency transmission of detection routes required by each subregion. Additionally, a trust calculation method based on node operations is proposed to evaluate the reliability of the device. the experimental results show that the PATM scheme proposed in this article can quickly identify the trust degree of nodes while balancing the needs of different regions, ensuring the credibility of data collection. © 2023 IEEE.

关键词： internet of things

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Ant: An Efficient Lossless Compression Algorithm for IoT Time Series Data 21

Ant: An Efficient Lossless Compression Algorithm for IoT Tim...

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作者： Li, Junhui Xu, Guangping Yang, Hongzhang Wu, Yulei Tianjin University of Technology School of Computer Science and Engineering Tianjin China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin China Key Laboratory of Computer Vision and System Ministry of Education China University of Bristol Faculty of Science and Engineering Bristol United Kingdom

ISBN: (纸本)9798350329223

In various applications in internet of things like industrial monitoring, large amounts of floating-point time series data are generated at an unprecedented rate. Efficient compression algorithms can effectively reduce the size of data, enhance transmission performance and storage efficiency, and simultaneously lower storage costs. therefore, there is a need for lightweight and efficient stream compression algorithms. In this paper, we propose a novel lossless floating-point data compression algorithm called Ant. the main idea is to encode double-precision floating-point numbers into integer form, calculate the delta between adjacent values, and then convert the delta into unsigned integers. this encoding method effectively reduces storage costs and improves data compression efficiency. Extensive experiments on real-world datasets demonstrate that our algorithm achieves compression speeds at least as fast as state-of-the-art streaming methods, and a 63% relative improvement in average compression rate. © 2023 IEEE.

关键词： Storage efficiency

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Application Research of Vertical Federated Learning technology in Banking Risk Control Model Strategy 21

Application Research of Vertical Federated Learning Technolo...

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作者： Luo, Yong Lu, Zhi Yin, Xiaofei Lu, Songfeng Weng, Yiting Huazhong University of Science and Technology Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Wuhan China China Minsheng Banking Corp. Ltd. Beijing China Shenzhen Huazhong University of Science and Technology Research Institute Wuhan China Shu Lun Pan Beijing China

ISBN: (纸本)9798350329223

this study centers on the application of vertical federated learning technology in the context of internet banking loans, with a particular focus on innovations in data privacy protection, risk control model algorithms, and secure multi-party computation. Currently, banking risk control strategies mainly rely on traditional data processing technologies, which often fall short in protecting user privacy and ensuring data usage efficiency. We adopt vertical federated learning technology, offering an innovative solution for the internet banking loan scenario. Firstly, regarding data privacy protection, we propose a differential privacy mechanism to safeguard user-sensitive data. Secondly, we innovatively apply risk control model algorithms, facilitating collaborative modeling across multiple internet loan platforms through federated learning. Furthermore, we introduce secure multi-party computation technology to ensure the secure transmission of data and confidentiality of computation processes during federated learning. through empirical experiments on real internet loan datasets, we validate the effectiveness and feasibility of our proposed methods. After implementing our risk control model, the credit approval rate increased from 3.44% to 18.2%, with a single-day high reaching 25.53%. the average loan amount increased by 7,700 yuan, and the average interest rate slightly declined by 0.48%, marking a significant improvement and breakthrough compared to traditional risk control models. this study offers innovative solutions for data privacy protection and risk control in the internet loan scenario, providing safer and more reliable services for financial institutions and users. Moreover, our methods possess high practicality and promotional value. the potential widespread impact on the industry is profound. © 2023 IEEE.

关键词： Risk management

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