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检索条件"任意字段=2023 International Conference on Data, Information and Computing Science, CDICS 2023"

共 46657 条记录，以下是11-20 订阅

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Secure Sharing of university data Using Hyperledger Fabric and IPFS system 18

Secure Sharing of university Data Using Hyperledger Fabric a...

引用

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： Marhane, Khaoula Taif, Fatima Namir, Abdelouahed Univ Hassan 2 Fac Sci Ben Msik Bd Commandant Driss Al Harti Casablanca 20670 Morocco

the university often sharing the data with the her providers the services and the projects. While the general rule from education records cannot be disclosed a anyone. In this paper we proposed hyperledger fabric in same university for connected all faculty and knowledge sharing with we use the InterPlanetary File System (IPFS) for the storage of tendering document. (c) 2023 The Authors. Published by Elsevier B.V.

关键词： Blockchain Hyperledger Fabric Secure Sharing data IPFS

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A High Capacity Combined Carrier Steganography Without Embedding Image

A High Capacity Combined Carrier Steganography Without Embed...

引用

2023 IEEE international conference on Dependable, Autonomic and Secure computing, 2023 international conference on Pervasive Intelligence and computing, 2023 international conference on Cloud and Big data computing, 2023 international conference on Cyber science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2023

作者： Zhang, Yangwen Chen, Yuling Dou, Hui Luo, Yun Tan, Chaoyue Xiong, Maolin College of Computer Science and Technology Guizhou University State Key Laboratory of Public Big Data Guiyang China

ISBN: (纸本)9798350304602

The technique of image steganography is the embedding of secret information into the carrier image by means of algorithms that are widely used in the field of information transmission, but steganalysis tools built with traditional steganographic algorithms can easily identify them. The technique of steganography without embedding (SWE) is the mapping of the secret information onto the noise and the generation of an image by mapping the noise of the secret information. This SWE technique is difficult to find without directly using secret information. But the capacity of secret information is less and the extraction accuracy is low when the SWE is currently hidden. Therefore, a steganography without embedding technique for carrier secret information is proposed in this paper based on the above problems. Initially, the secret information is mapped into the carrier noise, which can increase the secret information capacity of steganography and improve the accuracy of extracting information. Finally, the effectiveness and generality of the design method will be verified by experiments. © 2023 IEEE.

关键词： Embeddings

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Recommendation Algorithm Based on Social information and Global Average Matrix Decomposition

Recommendation Algorithm Based on Social Information and Glo...

引用

作者： Wang, Wanliang Jiang, Jiulei Li, Shengqing School of Computer Science and Engineering North Minzu University Yinchuan China School of Computer Science and Engineering Changshu Institute of Technology Suzhou China

ISBN: (纸本)9798350304602

Traditional recommendation systems typically rely solely on user content information to predict product ratings while ignoring the impact of other factors on recommendation effectiveness. Proposes a recommendation algorithm based on product attributes and social attributes that leverages product attribute information to obtain user preferences and product features, thereby reducing rating data sparsity. The algorithm also considers the effect of social attributes on the recommendation system and uses linear weighting with global rating average, item rating average, user rating average, and matrix decomposition to predict user ratings, thus improving prediction accuracy. The algorithm was tested on three public datasets, and the results indicate that it improves recommendation performance to a certain extent. © 2023 IEEE.

关键词： Recommender systems

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Fault-Tolerant data Aggregation with Error-Checking for Smart Grids

Fault-Tolerant Data Aggregation with Error-Checking for Smar...

引用

作者： Wang, Congcong Wang, Chen Shen, Jian Vijayakumar, Pandi Bhuiyan, Zakirul Alam School of Software Nanjing University of Information Science & Technology Nanjing210044 China School of Information Science and Engineering Zhejiang Sci-Tech University Hangzhou310018 China University College of Engineering Tindivanam Department of Computer Science and Engineering Tamilnadu 604001 India Fordham University Department of Computer and Information Sciences NY10458 United States

ISBN: (纸本)9798350304602

With the rapid development of smart grid technology, a new challenge has been brought about by the massive data generated from distributed devices. data aggregation technology plays a crucial role in smart grid schemes, in terms of energy data statistics and resource allocation. However, achieving fast error-checking and improving device fault-tolerance are still open issues in the smart grid data aggregation. To address these issues, this paper proposes an error-tolerant data aggregation scheme integrated with error-checking mechanisms. The scheme proposes a tree-based aggregation structure, facilitating swift error-checking of data. We combine masking values with user anonymity in the ElGamal cryptographic scheme to ensure the security of sensitive data and resist collusion attacks. Both theoretical and experimental analyses demonstrate that this scheme enables a lightweight, secure data aggregation, ensuring enhanced reliability and error-checking. © 2023 IEEE.

关键词： Fault tolerance

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The Involvement of Quantum computing in the Realm of Cybersecurity

The Involvement of Quantum Computing in the Realm of Cyberse...

引用

international conference on Computational science and Computational Intelligence (CSCI)

作者： Mahmoud, Mohammed Univ Jamestown Dept Comp Sci Jamestown ND 58405 USA

ISBN: (数字)9798350361513

ISBN: (纸本)9798350361513;9798350372304

In this paper, I will be discussing quantum computing in cybersecurity. Quantum computing is in development and will be released to the public sooner rather than later. With how quickly technology evolves, it will get here faster than we know it. However, this opens the door for cyberattacks with strength never seen before, possibly breaching the privacy of millions of individuals and organizations around the world. I have gathered information and data surrounding the involvement of cybersecurity within the quantum computing world. This research involves how this type of computing is being utilized with cybersecurity today, possible risks of both the security and the introduction of computers with exponential computing power compared to current devices, along with what encryption methods are strong enough to hold firm against quantum powered attacks. Technology is the future humanity has made for themselves, and understanding the security risks and benefits are critical to remaining safe and ethical while new techniques emerge.

关键词： Quantum computing cybersecurity security technology cyberattacks cyberthreats breaches privacy information data risks computing power encryption decryption algorithms

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Analysis of the role of computer big data and cloud computing in information security

Analysis of the role of computer big data and cloud computin...

引用

2023 international conference on Networking, Informatics and computing, ICNETIC 2023

作者： Wei, Qian Tianjin University of Technology Tianjin China

ISBN: (纸本)9798350313314

With the rapid development of social economy, science and technology, e-commerce and network, computer extends more and more content, in the era of big data, cloud computing has become an emerging field, multi-tenant, distributed computing, distributed storage and virtualization concepts onto the stage. This paper mainly discusses the factors affecting information security in the era of big data, and analyzes the role of big data and cloud computing in information security. © 2023 IEEE.

关键词： Economic and social effects

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Some Classes of Cryptographic Power Functions and Permutation Polynomials with Low (-1)-Differential Uniformity in Cyber Security

Some Classes of Cryptographic Power Functions and Permutatio...

引用

作者： Liu, Qian Dong, Xiaobei Chen, Zhixiong Liu, Ximeng Xu, Li College of Computer and Data Science Fuzhou University Fuzhou China Putian University Fujian Key Laboratory of Financial Information Processing Putian China College of Computer and Data Science Fuzhou University Key Laboratory of Information Security of Network Systems Fuzhou China College of Computer and Cyber Security Fujian Normal University Fuzhou China

ISBN: (纸本)9798350304602

Cryptographic functions with low differential uniformity have wide applications in cryptography and cyber security. In this paper, we further investigate c-differential uniformity proposed by Ellingsen et al. (IEEE Transactions on information Theory. 2020, 66(9): 5781-5789). Specifically, two classes of power functions with low (1)-differential uniformity over finite fields with odd characteristic are obtained. In addition, a class of permutation polynomials and P1N or AP1N functions over F3n are proposed. These functions with low c-differential uniformity are utilized to resist against c-differential attacks in cyberspace from those with the usual low differential uniformity. © 2023 IEEE.

关键词： Cybersecurity

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Differential Privacy Frequent Closed Itemset Mining over data Stream 22

Differential Privacy Frequent Closed Itemset Mining over Dat...

引用

IEEE 22nd international conference on Trust, Security and Privacy in computing and Communications (TrustCom) / BigdataSE conference / CSE conference / EUC conference / ISCI conference

作者： Ma, Xuebin Guan, Shengyi Lang, Yanan Inner Mongolia Univ Inner Mongolia Key Lab Wireless Networking & Mobi Hohhot Peoples R China

ISBN: (纸本)9798350381993;9798350382006

As the most common technique for mining and analyzing massive data, frequent itemset mining is widely used in various scenarios. However, when the data contains sensitive information, it will bring serious privacy leakage risks to mining and publishing it directly. Therefore, how to efficiently mine frequent itemset without privacy disclosure is a hot issue at present. In data stream, because the data between adjacent timestamps possess certain correlation, which makes it easier to leak privacy for frequent itemset mining in the data stream, and considering that frequent itemset will have combinatorial explosion problem in data stream, frequent closed itemset mining in the data stream will be a better choice. In this paper, we propose a differential privacy algorithm for mining frequent closed itemset in data stream, which is referred to as DPES. The algorithm uses a vertical mining method in each sliding window, which can quickly obtain the frequent closed itemset contained in the current window. Besides, to improve the data utility, we also design an adaptive privacy budget allocation strategy by computing the difference to decide whether the current timestamp should publish a low-noise statistic or an approximate statistic. Finally, we demonstrate that the DPES algorithm satisfies e-difference privacy by privacy analysis, and the experimental results on several real datasets also show the effectiveness of the DPES algorithm.

关键词： Frequent closed itemset mining Differential privacy data stream

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Ensemble Methods for Spatial data Stream Classification 18

Ensemble Methods for Spatial Data Stream Classification

引用

作者： King, Liam Osborn, Wendy Univ Lethbridge Dept Math & Comp Sci 4401 Univ Dr West Lethbridge AB T1K 3M4 Canada

In this paper, we study the problem of classification of data in a spatial data stream. The classification of spatial objects in a static data set has been well studied. However, classifying objects in a spatial data stream has received very little attention. We propose an iterative ensemble approach for deep learning of a spatial data stream. Using several deep neural networks, our strategy iteratively performs training and testing of the classifier, with the goal of reaching a desired accuracy, and the same accuracy that would be achieved as a classifier that is trained and tested with the entire dataset. An experimental evaluation and comparison of the ensemble approach shows improvement over a previously proposed iterative deep learning strategy. (c) 2023 The Authors. Published by Elsevier B.V.

关键词： spatial data streams classification neural networks ensemble methods

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IoT data Confidentiality Self-Management

IoT Data Confidentiality Self-Management

引用

作者： Garah, Abdelhamid Mbarek, Nader Kirgizov, Sergey University of Burgundy Lib Laboratory Dijon21000 France

ISBN: (纸本)9798350304602

As the number of connected devices increases, protecting sensitive information transmitted by IoT devices is critical. One of the most effective ways to ensure data confidentiality while accommodating the limited resources of constrained devices is to use lightweight cryptographic algorithms. However, managing these algorithms in IoT ecosystems is a significant challenge. To overcome this problem, we propose a new IoT framework that enables self-management of IoT data confidentiality based on the use of lightweight cryptography and the Autonomic computing paradigm. Our approach implements the MAPE-K closed control loop, which uses a decision tree algorithm to predict the most appropriate lightweight encryption algorithm based on the state of the IoT object, thus ensuring data confidentiality, improving system performance, and extending the lifetime of IoT devices. © 2023 IEEE.

关键词： Decision trees

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