A Practical Study of Big Data Technology in Computer Network Information Security Processing

In recent years,China has witnessed continuous development and progress in its scientific and technological landscape,with widespread utilization of computer networks.Concurrently,issues related to computer network information security,such as information leakage and virus invasions,have become increasingly prominent.Consequently,there is a pressing need for the implementation of effective network security measures.This paper aims to provide a comprehensive summary and analysis of the challenges associated with computer network information security processing.It delves into the core concepts and characteristics of big data technology,exploring its potential as a solution.The study further scrutinizes the application strategy of big data technology in addressing the aforementioned security issues within computer networks.The insights presented in this paper are intended to serve as a valuable reference for individuals involved in the relevant fields,offering guidance on effective approaches to enhance computer network information security through the application of big data technology.

Privacy Cost Analysis and Privacy Protection Based on Big Data

A comprehensive analysis of the impact privacy incidents on its market value is given.A broad set of instances of the exposure of personal information from a summary of some security mechanisms and the corresponding results are presented. The cumulative effect increases in magnitude over day following the breach announcement, but then decreases. Besides, a new privacy protection property, that is, p-sensitive k-anonymity is presented in this paper to protect against identity disclosure. We illustrated the inclusion of the two necessary conditions in the algorithm for computing a p-k-minimal generalization. Algorithms such as k-anonymity and l-diversity remain all sensitive attributes intact and apply generalization and suppression to the quasi-identifiers. This will keep the data "truthful" and provide good utility for data-mining applications, while achieving less perfect privacy. We aim to get the problem based on the prior analysis, and study the issue of privacy protection from the perspective of the model-benefit.

A distributed authentication and authorization scheme for in-network big data sharing

Big data has a strong demand for a network infrastructure with the capability to support data sharing and retrieval efficiently. Information-centric networking （ICN） is an emerging approach to satisfy this demand, where big data is cached ubiquitously in the network and retrieved using data names. However, existing authentication and authorization schemes rely mostly on centralized servers to provide certification and mediation services for data retrieval. This causes considerable traffic overhead for the secure distributed sharing of data. To solve this problem, we employ identity-based cryptography （IBC） to propose a Distributed Authentication and Authorization Scheme （DAAS）, where an identity-based signature （IBS） is used to achieve distributed verifications of the identities of publishers and users. Moreover, Ciphertext-Policy Attribnte-based encryption （CP-ABE） is used to enable the distributed and fine-grained authorization. DAAS consists of three phases： initialization, secure data publication, and secure data retrieval, which seamlessly integrate authentication and authorization with the in- terest/data communication paradigm in ICN. In particular, we propose trustworthy registration and Network Operator and Authority Manifest （NOAM） dissemination to provide initial secure registration and enable efficient authentication for global data retrieval. Meanwhile, Attribute Manifest （AM） distribution coupled with automatic attribute update is proposed to reduce the cost of attribute retrieval. We examine the performance of the proposed DAAS, which shows that it can achieve a lower bandwidth cost than existing schemes.

Research on the Association of Mobile Social Network Users Privacy Information Based on Big Data Analysis

The issue of privacy protection for mobile social networks is a frontier topic in the field of social network applications.The existing researches on user privacy protection in mobile social network mainly focus on privacy preserving data publishing and access control.There is little research on the association of user privacy information,so it is not easy to design personalized privacy protection strategy,but also increase the complexity of user privacy settings.Therefore,this paper concentrates on the association of user privacy information taking big data analysis tools,so as to provide data support for personalized privacy protection strategy design.

Cyber Resilience through Real-Time Threat Analysis in Information Security

This paper examines how cybersecurity is developing and how it relates to more conventional information security. Although information security and cyber security are sometimes used synonymously, this study contends that they are not the same. The concept of cyber security is explored, which goes beyond protecting information resources to include a wider variety of assets, including people [1]. Protecting information assets is the main goal of traditional information security, with consideration to the human element and how people fit into the security process. On the other hand, cyber security adds a new level of complexity, as people might unintentionally contribute to or become targets of cyberattacks. This aspect presents moral questions since it is becoming more widely accepted that society has a duty to protect weaker members of society, including children [1]. The study emphasizes how important cyber security is on a larger scale, with many countries creating plans and laws to counteract cyberattacks. Nevertheless, a lot of these sources frequently neglect to define the differences or the relationship between information security and cyber security [1]. The paper focus on differentiating between cybersecurity and information security on a larger scale. The study also highlights other areas of cybersecurity which includes defending people, social norms, and vital infrastructure from threats that arise from online in addition to information and technology protection. It contends that ethical issues and the human factor are becoming more and more important in protecting assets in the digital age, and that cyber security is a paradigm shift in this regard [1].

Cyber Security-Protecting Personal Data

Many organizations have datasets which contain a high volume of personal data on individuals,e.g.,health data.Even without a name or address,persons can be identified based on the details(variables)on the dataset.This is an important issue for big data holders such as public sector organizations(e.g.,Public Health Organizations)and social media companies.This paper looks at how individuals can be identified from big data using a mathematical approach and how to apply this mathematical solution to prevent accidental disclosure of a person’s details.The mathematical concept is known as the“Identity Correlation Approach”(ICA)and demonstrates how an individual can be identified without a name or address using a unique set of characteristics(variables).Secondly,having identified the individual person,it shows how a solution can be put in place to prevent accidental disclosure of the personal details.Thirdly,how to store data such that accidental leaks of the datasets do not lead to the disclosure of the personal details to unauthorized users.

Research on IPv6 Transition Evolvement and Security Architecture of Smart Distribution Grid Data Communication System

Smart distribution grid needs data communication systems as a support to complete their important functions. The smart distribution grid of the data and information are increasingly adopting internet protocol and Ethernet technology. The IP addresses are more and more important for the smart distribution grid equipment. The current IPv4 protocol occupies a dominant position; therefore, the challenges of the evolution to IPv6 and network security are faced by data communication systems of the smart distribution grid. The importance of data communications network and its main bearer of business were described. The data communications network from IPv4 to IPv6 evolution of the five processes and four stages of the transition were analyzed. The smart distribution grid data communications network security and types of their offensive and defensive were discussed. And the data communications network security architecture was established. It covers three dimensions, the security level, the communications network security engineering and the communications network security management. The security architecture safeguards the evolution to IPv6 for the smart distribution grid data communication systems.

新型电力系统数据跨域流通泛安全边界防护技术

新型电力系统建设涉及多业务系统、多部门、多方主体间进行海量、异构数据的交互和共享,电力数据的内外部网络环境与安全形势日趋复杂化,数据流通的脆弱性风险加剧。首先,分析新型电力系统下数据流的类型与特性,概括电力数据流通安全防护面临的新形势;其次,基于专用数据处理器(DPU)的高性能流量编排和多功能安全网关能力,构建面向电力数据跨域流通安全增强的泛安全边界,凭借数据面可编程技术沟通网络安全与数据安全双维度安全能力,提出基于DPU的数据跨域流通协同防护技术应用方案;最后,阐释DPU在不同电力通信网络层次的部署方式、价值与关键技术,分析现阶段DPU在电力领域应用存在的挑战。

基于大数据聚类的通信网络安全态势预测技术

传统通信网络安全态势预测技术缺乏大数据支撑,难以对发生的攻击进行详细分类和追踪,导致在进行长时间的态势预测中收敛过慢,准确度降低.提出一种基于大数据聚类的通信网络安全态势预测技术.分析通信网络的属性以及特点,选择安全态势描述一级指标,将数据标准化处理之后,细分出二级指标;优化大数据聚类算法,计算最优聚类数量、确定聚类中心,建立关联规则库并优化预测流程,完成基于大数据聚类的通信网络安全态势预测技术的设计.通过实验结果表明,与两种传统的安全态势预测技术相比,设计的技术收敛速度更快,全体数据点没有出现残差扩散的现象,并且数据完整度较高.

大数据时代计算机网络信息安全探讨

随着科技的不断发展,大数据时代已经到来,大数据技术广泛用于各行各业,为社会带来巨大的变革。然而,与大数据的快速发展相伴而生的是计算机网络信息安全问题的加剧。大数据时代网络安全问题的复杂性和严重性不容忽视,需要我们认真思考并采取有效措施应对。文章将探讨大数据时代对计算机网络信息安全的挑战,并提出一些关键策略以确保信息安全。

网络分析模式下低温锂电池储能系统功能安全保障策略

随着全球能源结构的转型和可再生能源的广泛应用,低温锂电池储能系统因其优异的性能在极端环境条件下得到了快速发展。然而,其储能安全问题也日益凸显。本文首先分析了当前低温锂电池储能系统的应用结构与研究进展,在此基础上重点探讨网络分析技术如何提高低温锂电池储能系统的功能安全。旨在为低温锂电池储能系统的安全性能提升提供有价值的参考。

构建安全可信网络新生态促进数字经济高质量发展

随着信息化进程不断推进,数字经济已成为经济增长新引擎,其面临的安全性、韧性及自主可控性挑战也日益凸显。本文旨在探讨如何构建安全可信的网络新生态以有效应对这些挑战,通过分析数字经济中大数据特性及对网络空间安全的重塑,强调构建安全可信的网络主动免疫体系的必要性,并探究如何通过安全可信技术促进数字经济的高质量发展。

计算机网络安全在大数据系统中的应用与研究

随着信息技术的快速发展,大数据系统在各行各业逐渐普及。然而,伴随着大规模数据的处理和传输,计算机网络安全问题逐渐显现。基于此,本文探讨了大数据系统中的网络安全挑战,分析计算机网络安全在大数据系统中的应用,提出大数据系统网络安全的未来发展方向。

基于大数据技术的网络安全态势感知平台设计

在网络安全威胁不断演变的背景下,构建一套基于大数据技术的网络安全态势感知平台至关重要。本文介绍了网络安全态势感知平台的设计框架,包括系统架构、数据采集与处理、安全事件检测与分析以及实时可视化等关键模块。通过应用案例分析,突显平台在实际环境中的应用效果。实时可视化与报告和自动化响应与持续改进两个章节详细探讨了用户界面设计、报告定制化和自动响应机制。最后,总结了平台设计的关键要点,并展望了未来网络安全领域的发展趋势。

大数据安全视域下高校网络思想政治教育的创新策略研究

随着网络技术的普及和发展,网络思想政治教育工作已经成为高校加强大学生思想政治教育的重要组成部分。伴随着大数据技术在互联网中的广泛应用,信息安全问题也给高校网络思想政治教育工作带来了新的挑战。通过阐述大数据安全在高校网络思想政治教育中的应用价值,探讨大数据安全视域下高校网络思想政治教育工作面临的问题,进一步寻求大数据安全视域下高校网络思想政治教育的创新策略,旨在为高校提升网络思想政治教育的质量和效益提供理论和实践支持。

数据安全防护体系在高校校园网中的应用

在高校网络的基本组成结构中,校园网具有保障高校数据信息得以安全稳定传输的重要作用,校园网目前已成为高校师生赖以实现沟通联系的基础设施支撑。目前在网络技术的快速转型以及发展趋势作用下,高校校园网日益存在更加突出的网络数据安全威胁,进而体现全面防范以及科学预测校园网数据安全隐患的必要性。文章主要探讨高校校园网构建数据安全防护体系的实践价值,合理改进校园网现有的数据传输安全保障机制。

大数据背景下网络安全与隐私保护技术研究

随着互联网和大数据技术的发展,网络安全和个人隐私面临着空前的威胁。文章主要介绍大数据、网络安全与个人隐私内容,分析大数据背景下网络安全与隐私保护问题,并探讨大数据背景下网络安全与隐私保护相关的技术,希望对维护网络安全和保护用户隐私有所帮助。

基于大数据技术的网络安全数据分析平台构建

信息技术的应用可以提高工作效率,但也存在一定的网络安全风险,保护网络安全成为众多企业、单位亟待解决的问题。网络安全数据管理过程中易存在较多隐患,漏洞扫描可以及时发现并解决数据安全隐患。事业单位产生了大量工作数据,且数据管理专职人员较少,需要管理人员花费大量时间梳理数据,存在扫描漏洞问题。基于此,文章利用大数据技术设计了网络安全数据分析平台。平台包括从数据入账到后续修复的全过程,能够有效地为单位提供更加精确的数据,提高网络安全分析效率。

大数据背景下网络安全问题及解决对策

大数据技术的快速发展应用,对于计算机网络发展意义重大,一方面,大数据给计算机网络发展带来重大机遇;另一方面,大数据也对计算机网络安全提出了更高的要求。文章就大数据时代的网络安全特征进行分析,阐述大数据背景下的主要网络安全问题,并分析大数据背景下维护网络安全的有效对策,以期为大数据技术在网络安全中的有效应用提供一些思路和参考。

大数据背景下通信网络安全管理策略探讨

在现代信息技术发展速度加快的背景下,以现代信息化技术为基础,开展通信网络安全管理工作具有至关重要的意义。文章主要分析大数据背景下通信网络安全问题,探讨在大数据背景下通信网络安全管理面临的困境。同时,从不同角度出发分析基于大数据技术的通信网络安全管理关键技术,通过采取有效策略加强通信网络安全管理,助力我国国家信息通信网络安全稳定地持续发展。