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A survey on cryptographic techniques for protecting big data security: present and forthcoming

Science China(Information Sciences) 2022年第10期65卷 73-106页

作者： Siqi LU Jianhua ZHENG Zhenfu CAO Yongjuan WANG Chunxiang GU School of Cyberspace security Information Engineering University Henan Key Laboratory of Network Cryptography Technology Institute of security Technology Shanghai Key Laboratory of Trustworthy Computing East China Normal University Cyberspace security Research Center Peng Cheng Laboratory Shanghai Institute of Intelligent Science and Technology Tongji University

big data drive multidimensional convergence and profound innovations among industries and provide novel ways of exploring the world. As they significantly create economic and social value, big data meaningfully impact the implementation and management of information security and privacy protection.Cryptographic technologies are used to protect the security and entire life cycle of big data. The demand for this technology is multiplied when the data are stored in the cloud. They are stored in the cloud in the form of ciphertext, and the driving requirement for data retrieval, sharing, and manipulation places the security of data at risk. The all-or-nothing approach of traditional cryptography systems cannot realize the release and processing of data information with flexible and increasingly fine granularity. Consequently, dealing with the relationship between privacy protection and data utilization, as well as navigating the blurry boundaries between subverting either plaintext or ciphertext, has become a research focus of the current cryptographic trend for protecting big data security. Presently, there are many studies designed to solve these limitations.First, security requirements and source encryption mode for future big data systems and applications are elaborated. Then, focusing on the practical security and functionality of the big data life cycle, including storage, retrieval, sharing, calculation, statistical analysis, and utilization, the research being conducted based on those functions is reviewed. For each cryptographic technology that meets the requirement of each type of big data security or application, security and efficiency comments and sufficient comparison analyses of cryptography schemes or protocols are provided; moreover, the current general problems and development trends are expounded. Because the current innovative research on cryptographic technology was primarily based on the development or improvement of a single solution, the study on the security of the entire big data life cycle

关键词： big data security cryptographic techniques ciphertext-based data sharing and computing authenticated encryption functional encryption homomorphic encryption secure multi-party computing

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Hadoop-based secure storage solution for big data in cloud computingg environment

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Digital Communications and Networks 2024年第1期10卷 227-236页

作者： Shaopeng Guan Conghui Zhang Yilin Wang Wenqing Liu School of Information and Electronic Engineering Shandong Technology and Business UniversityYantai264003China

In order to address the problems of the single encryption algorithm,such as low encryption efficiency and unreliable metadata for static data storage of big data platforms in the cloud computing environment,we propose a Hadoop based big data secure storage scheme.Firstly,in order to disperse the NameNode service from a single server to multiple servers,we combine HDFS federation and HDFS high-availability mechanisms,and use the Zookeeper distributed coordination mechanism to coordinate each node to achieve dual-channel storage.Then,we improve the ECC encryption algorithm for the encryption of ordinary data,and adopt a homomorphic encryption algorithm to encrypt data that needs to be calculated.To accelerate the encryption,we adopt the dualthread encryption mode.Finally,the HDFS control module is designed to combine the encryption algorithm with the storage model.Experimental results show that the proposed solution solves the problem of a single point of failure of metadata,performs well in terms of metadata reliability,and can realize the fault tolerance of the server.The improved encryption algorithm integrates the dual-channel storage mode,and the encryption storage efficiency improves by 27.6% on average.

关键词： big data security data encryption Hadoop Parallel encrypted storage Zookeeper

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Classification of big data security Based on Ontology Web Language

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Journal of Information security 2023年第1期14卷 76-91页

作者： Alsadig Mohammed Adam Abdallah Amir Mohamed Talib College of Computer and Information Sciences (CCIS) Riyadh Kingdom of Saudi Arabia (KSA) Imam Mohammad Ibn Saud Islamic University (IMSIU) Riyadh Kingdom of Saudi Arabia (KSA)

A vast amount of data (known as big data) may now be collected and stored from a variety of data sources, including event logs, the internet, smartphones, databases, sensors, cloud computing, and Internet of Things (IoT) devices. The term “big data security” refers to all the safeguards and instruments used to protect both the data and analytics processes against intrusions, theft, and other hostile actions that could endanger or adversely influence them. Beyond being a high-value and desirable target, protecting big data has particular difficulties. big data security does not fundamentally differ from conventional data security. big data security issues are caused by extraneous distinctions rather than fundamental ones. This study meticulously outlines the numerous security difficulties Large data analytics now faces and encourages additional joint research for reducing both big data security challenges utilizing Ontology Web Language (OWL). Although we focus on the security Challenges of big data in this essay, we will also briefly cover the broader Challenges of big data. The proposed classification of big data security based on ontology web language resulting from the protégé software has 32 classes and 45 subclasses.

关键词： big data big data security Information security data security Ontology Web Language Protégé

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Research on Medical big data Application Model Based on data Separation

Research on Medical Big Data Application Model Based on Data...

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作者： Hai-feng LI Hong-rui SUN Dalian Jiaotong University

data attributed data, privacy attributed privacy. At present, big data development now going all walks of life, in order to better carry out medical research and so on, the medical industry select development of healthcare big data, but the data are still some big problems in terms of security: user privacy information disclosure and other. This paper proposes a new way of thinking: data separation storage method, by the user’s information data into information data block medical data and personal information data blocks, try a way to solve the existing problem of private data leakage, and study the practical application ability of medical big data based on this data separation storage method.

关键词： Medical big data big data security data separation

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