In this paper,the application of agricultural big data in agricultural economic management is deeply explored,and its potential in promoting profit growth and innovation is analyzed.However,challenges persist in data ...In this paper,the application of agricultural big data in agricultural economic management is deeply explored,and its potential in promoting profit growth and innovation is analyzed.However,challenges persist in data collection and integration,limitations of analytical technologies,talent development,team building,and policy support when applying agricultural big data.Effective application strategies are proposed,including data-driven precision agriculture practices,construction of data integration and management platforms,data security and privacy protection strategies,as well as long-term planning and development strategies for agricultural big data,to maximize its impact on agricultural economic management.Future advancements require collaborative efforts in technological innovation,talent cultivation,and policy support,to realize the extensive application of agricultural big data in agricultural economic management and ensure sustainable industrial development.展开更多
Big data has been taken as a Chinese national strategy in order to satisfy the developments of the social and economic requirements and the development of new information technology. The prosperity of big data brings ...Big data has been taken as a Chinese national strategy in order to satisfy the developments of the social and economic requirements and the development of new information technology. The prosperity of big data brings not only convenience to people's daily life and more opportunities to enterprises, but more challenges with information security as well. This paper has a research on new types and features of information security issues in the age of big data, and puts forward the solutions for the above issues: build up the big data security management platform, set up the establishment of information security system and implement relevant laws and regulations.展开更多
The landscape of cybersecurity is rapidly evolving due to the advancement and integration of Artificial Intelligence (AI) and Machine Learning (ML). This paper explores the crucial role of AI and ML in enhancing cyber...The landscape of cybersecurity is rapidly evolving due to the advancement and integration of Artificial Intelligence (AI) and Machine Learning (ML). This paper explores the crucial role of AI and ML in enhancing cybersecurity defenses against increasingly sophisticated cyber threats, while also highlighting the new vulnerabilities introduced by these technologies. Through a comprehensive analysis that includes historical trends, technological evaluations, and predictive modeling, the dual-edged nature of AI and ML in cybersecurity is examined. Significant challenges such as data privacy, continuous training of AI models, manipulation risks, and ethical concerns are addressed. The paper emphasizes a balanced approach that leverages technological innovation alongside rigorous ethical standards and robust cybersecurity practices. This approach facilitates collaboration among various stakeholders to develop guidelines that ensure responsible and effective use of AI in cybersecurity, aiming to enhance system integrity and privacy without compromising security.展开更多
In a database-as-a-service(DaaS)model,a data owner stores data in a database server of a service provider,and the DaaS adopts the encryption for data privacy and indexing for data query.However,an attacker can obtain ...In a database-as-a-service(DaaS)model,a data owner stores data in a database server of a service provider,and the DaaS adopts the encryption for data privacy and indexing for data query.However,an attacker can obtain original data’s statistical information and distribution via the indexing distribution from the database of the service provider.In this work,a novel indexing schema is proposed to satisfy privacy-preserved data management requirements,in which an attacker cannot obtain data source distribution or statistic information from the index.The approach includes 2 parts:the Hash-based indexing for encrypted data and correctness verification for range queries.The evaluation results demonstrate that the approach can hide statistical information of encrypted data distribution while can also obtain correct answers for range queries.Meanwhile,the approach can achieve nearly 10 times and 35 times improvement on encrypted data publishing and indexing respectively,compared with the start-of-the-art method order-preserving Hash-based function(OPHF).展开更多
基金Supported by Research and Application of Soil Collection Software and Soil Ecological Big Data Platform in Guangxi Woodland(GUILINKEYAN[2022ZC]44)Construction of Soil Information Database and Visualization System for Artificial Forests in Central Guangxi(2023GXZCLK62).
文摘In this paper,the application of agricultural big data in agricultural economic management is deeply explored,and its potential in promoting profit growth and innovation is analyzed.However,challenges persist in data collection and integration,limitations of analytical technologies,talent development,team building,and policy support when applying agricultural big data.Effective application strategies are proposed,including data-driven precision agriculture practices,construction of data integration and management platforms,data security and privacy protection strategies,as well as long-term planning and development strategies for agricultural big data,to maximize its impact on agricultural economic management.Future advancements require collaborative efforts in technological innovation,talent cultivation,and policy support,to realize the extensive application of agricultural big data in agricultural economic management and ensure sustainable industrial development.
基金supported by National Key Technology Support Program(No.2013BAD17B06)Major Program of National Social Science Fund(No.15ZDB154)
文摘Big data has been taken as a Chinese national strategy in order to satisfy the developments of the social and economic requirements and the development of new information technology. The prosperity of big data brings not only convenience to people's daily life and more opportunities to enterprises, but more challenges with information security as well. This paper has a research on new types and features of information security issues in the age of big data, and puts forward the solutions for the above issues: build up the big data security management platform, set up the establishment of information security system and implement relevant laws and regulations.
文摘The landscape of cybersecurity is rapidly evolving due to the advancement and integration of Artificial Intelligence (AI) and Machine Learning (ML). This paper explores the crucial role of AI and ML in enhancing cybersecurity defenses against increasingly sophisticated cyber threats, while also highlighting the new vulnerabilities introduced by these technologies. Through a comprehensive analysis that includes historical trends, technological evaluations, and predictive modeling, the dual-edged nature of AI and ML in cybersecurity is examined. Significant challenges such as data privacy, continuous training of AI models, manipulation risks, and ethical concerns are addressed. The paper emphasizes a balanced approach that leverages technological innovation alongside rigorous ethical standards and robust cybersecurity practices. This approach facilitates collaboration among various stakeholders to develop guidelines that ensure responsible and effective use of AI in cybersecurity, aiming to enhance system integrity and privacy without compromising security.
基金the National Natural Science Foundation of China(No.61931019).
文摘In a database-as-a-service(DaaS)model,a data owner stores data in a database server of a service provider,and the DaaS adopts the encryption for data privacy and indexing for data query.However,an attacker can obtain original data’s statistical information and distribution via the indexing distribution from the database of the service provider.In this work,a novel indexing schema is proposed to satisfy privacy-preserved data management requirements,in which an attacker cannot obtain data source distribution or statistic information from the index.The approach includes 2 parts:the Hash-based indexing for encrypted data and correctness verification for range queries.The evaluation results demonstrate that the approach can hide statistical information of encrypted data distribution while can also obtain correct answers for range queries.Meanwhile,the approach can achieve nearly 10 times and 35 times improvement on encrypted data publishing and indexing respectively,compared with the start-of-the-art method order-preserving Hash-based function(OPHF).
