Data Integrity and Risk

Data Integrity is a critical component of Data lifecycle management. Its importance increases even more in a complex and dynamic landscape. Actions like unauthorized access, unauthorized modifications, data manipulations, audit tampering, data backdating, data falsification, phishing and spoofing are no longer restricted to rogue individuals but in fact also prevalent in systematic organizations and states as well. Therefore, data security requires strong data integrity measures and associated technical controls in place. Without proper customized framework in place, organizations are prone to high risk of financial, reputational, revenue losses, bankruptcies, and legal penalties which we shall discuss further throughout this paper. We will also explore some of the improvised and innovative techniques in product development to better tackle the challenges and requirements of data security and integrity.

Quality control of marine big data——a case study of real-time observation station data in Qingdao

Offshore waters provide resources for human beings,while on the other hand,threaten them because of marine disasters.Ocean stations are part of offshore observation networks,and the quality of their data is of great significance for exploiting and protecting the ocean.We used hourly mean wave height,temperature,and pressure real-time observation data taken in the Xiaomaidao station(in Qingdao,China)from June 1,2017,to May 31,2018,to explore the data quality using eight quality control methods,and to discriminate the most effective method for Xiaomaidao station.After using the eight quality control methods,the percentages of the mean wave height,temperature,and pressure data that passed the tests were 89.6%,88.3%,and 98.6%,respectively.With the marine disaster(wave alarm report)data,the values failed in the test mainly due to the influence of aging observation equipment and missing data transmissions.The mean wave height is often affected by dynamic marine disasters,so the continuity test method is not effective.The correlation test with other related parameters would be more useful for the mean wave height.

Enhancing Patients Outcomes and Infection Control through Smart Indoor Air Quality Monitoring Systems

Air pollution poses a critical threat to public health and environmental sustainability globally, and Nigeria is no exception. Despite significant economic growth and urban development, Nigeria faces substantial air quality challenges, particularly in urban centers. While outdoor air pollution has received considerable attention, the issue of indoor air quality remains underexplored yet equally critical. This study aims to develop a reliable, cost-effective, and user-friendly solution for continuous monitoring and reporting of indoor air quality, accessible from anywhere via a web interface. Addressing the urgent need for effective indoor air quality monitoring in urban hospitals, the research focuses on designing and implementing a smart indoor air quality monitoring system using Arduino technology. Employing an Arduino Uno, ESP8266 Wi-Fi module, and MQ135 gas sensor, the system collects real-time air quality data, transmits it to the ThingSpeak cloud platform, and visualizes it through a user-friendly web interface. This project offers a cost-effective, portable, and reliable solution for monitoring indoor air quality, aiming to mitigate health risks and promote a healthier living environment.

A Virtual Router Cluster System Based on the Separation of the Control Plane and the Data Plane

This paper proposes a virtual router cluster system based on the separation of the control plane and the data plane from multiple perspectives,such as architecture,key technologies,scenarios and standardization.To some extent,the virtual cluster simplifies network topology and management,achieves automatic conFig.uration and saves the IP address.It is a kind of low-cost expansion method of aggregation equipment port density.

Ensuring Security, Confidentiality and Fine-Grained Data Access Control of Cloud Data Storage Implementation Environment

With the development of cloud computing, the mutual understandability among distributed data access control has become an important issue in the security field of cloud computing. To ensure security, confidentiality and fine-grained data access control of Cloud Data Storage (CDS) environment, we proposed Multi-Agent System (MAS) architecture. This architecture consists of two agents: Cloud Service Provider Agent (CSPA) and Cloud Data Confidentiality Agent (CDConA). CSPA provides a graphical interface to the cloud user that facilitates the access to the services offered by the system. CDConA provides each cloud user by definition and enforcement expressive and flexible access structure as a logic formula over cloud data file attributes. This new access control is named as Formula-Based Cloud Data Access Control (FCDAC). Our proposed FCDAC based on MAS architecture consists of four layers: interface layer, existing access control layer, proposed FCDAC layer and CDS layer as well as four types of entities of Cloud Service Provider (CSP), cloud users, knowledge base and confidentiality policy roles. FCDAC, it’s an access policy determined by our MAS architecture, not by the CSPs. A prototype of our proposed FCDAC scheme is implemented using the Java Agent Development Framework Security (JADE-S). Our results in the practical scenario defined formally in this paper, show the Round Trip Time (RTT) for an agent to travel in our system and measured by the times required for an agent to travel around different number of cloud users before and after implementing FCDAC.

多普勒雷达DATA文件安全模型的设计

从计算机DATA文件安全的内涵出发,针对目前DATA文件面临的安全威胁,分析了影响DATA文件的安全因素,提出了DATA文件安全体系层次结构。重点论述DATA文件层次的安全控制所采取的技术手段和应急措施,在此基础上设计了一种新型DATA文件安全防护模型,使之能够控制DATA文件多层安全,保证DATA文件的安全运行。

基于ADOData控件实现数据库连接及其简单应用

VB具有强大的数据操纵功能,不仅能创建数据库文件,还能利用ADO Data控件实现与数据库的连接,通过一些绑定控件来显示数据库中的有关内容,并能开发出实用的数据管理系统。该文详细介绍了VB数据控件的属性,实现与数据库连接的方法、步骤,列举一些简单应用的编程代码。

Data Hiding and Security for XMLDatabase: A TRBAC-Based Approach

In order to cope with varying protection granularity levels of XML(extensible Markup Language) documents, we propose a TXAC (Two-level XML. Access Control) framework,in which an extended TRBAC ( Temporal Role-Based Access Control) approach is proposed to deal withthe dynamic XML data With different system components, LXAC algorithm evaluates access requestsefficiently by appropriate access control policy in dynamic web environment. The method is aflexible and powerful security system offering amulti-level access control solution.

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.

Development of Geological Data Warehouse

Data warehouse (DW), a new technology invented in 1990s, is more useful for integrating and analyzing massive data than traditional database. Its application in geology field can be divided into 3 phrases: 1992-1996, commercial data warehouse (CDW) appeared; 1996-1999, geological data warehouse (GDW) appeared and the geologists or geographers realized the importance of DW and began the studies on it, but the practical DW still followed the framework of DB; 2000 to present, geological data warehouse grows, and the theory of geo-spatial data warehouse (GSDW) has been developed but the research in geological area is still deficient except that in geography. Although some developments of GDW have been made, its core still follows the CDW-organizing data by time and brings about 3 problems: difficult to integrate the geological data, for the data feature more space than time; hard to store the massive data in different levels due to the same reason; hardly support the spatial analysis if the data are organized by time as CDW does. So the GDW should be redesigned by organizing data by scale in order to store mass data in different levels and synthesize the data in different granularities, and choosing space control points to replace the former time control points so as to integrate different types of data by the method of storing one type data as one layer and then to superpose the layers. In addition, data cube, a wide used technology in CDW, will be no use in GDW, for the causality among the geological data is not so obvious as commercial data, as the data are the mixed result of many complex rules, and their analysis always needs the special geological methods and software; on the other hand, data cube for mass and complex geo-data will devour too much store space to be practical. On this point, the main purpose of GDW may be fit for data integration unlike CDW for data analysis.

An Adaptive Data Aggregation Algorithm in Wireless Sensor Network with Bursty Source

The Wireless Sensor network is distributed event based systems that differ from conventional communica-tion network. Sensor network has severe energy constraints, redundant low data rate, and many-to-one flows. Aggregation is a technique to avoid redundant information to save energy and other resources. There are two types of aggregations. In one of the aggregation many sensor data are embedded into single packet, thus avoiding the unnecessary packet headers, this is called lossless aggregation. In the second case the sensor data goes under statistical process (average, maximum, minimum) and results are communicated to the base station, this is called lossy aggregation, because we cannot recover the original sensor data from the received aggregated packet. The number of sensor data to be aggregated in a single packet is known as degree of ag-gregation. The main contribution of this paper is to propose an algorithm which is adaptive to choose one of the aggregations based on scenarios and degree of aggregation based on traffic. We are also suggesting a suitable buffer management to offer best Quality of Service. Our initial experiment with NS-2 implementa-tion shows significant energy savings by reducing the number of packets optimally at any given moment of time.

一种全生命周期可控的公共数据共享方案

公共数据作为数据要素将极大赋能政府公共服务和社会治理,然而,频繁爆发的数据泄露事件严重阻碍了公共数据共享的进程。虽然现有的属性基加密方案能够实现公共数据的安全访问,但存在授权管理低效、共享后难以管控等问题,不适合现有的公共数据共享模式。为此,文章提出了一种全生命周期可控的公共数据共享方案。该方案设计了一种数据胶囊封装方法,将共享的公共数据与访问授权策略进行深度绑定,并构建了共享数据多方参与的分层授权、全生命周期感知的访问管控方式。安全性分析以及实验仿真表明,该方案实现了公共数据共享的全生命周期可控,开销较小,符合现实需求。

基于MEC边缘云的智慧商城数据更新控制算法

针对智慧商城中数据量较大的问题,提出基于MEC边缘云的智慧商城数据更新控制算法。在MEC边缘云环境中将数据信息经过整合分类处理后直接推送至用户端,将万有引力搜索算法和布谷鸟搜索算法融合构建CS-GSA算法,用于MEC边缘云智慧商城数据库数据清洗。在差分数据更新方法中引入游程编码和哈夫曼编码,采用游程编码将连续重复的数据压缩处理,降低数据规模,然后通过哈夫曼编码再次压缩,降低传输过程中的通信开销,实现MEC边缘云智慧商城数据更新。实验结果表明,所提方法的解编码时间、数据更新时间更短、通信开销较小,说明其能够提高数据更新质量。

人工智能囊胚形态评估数据集构建与质控专家共识

囊胚形态人工智能(AI)评估是AI医疗器械发展的新兴方向,也是AI在辅助生殖领域的重要应用。AI在新领域应用的起步阶段,数据集的构建与质控对产品质量有重要影响。目前,囊胚形态学AI评估在数据采集、标注、质控等方面尚未形成统一的规范。在参考AI医疗器械、辅助生殖医疗器械现有国家行业标准的基础上,本文以囊胚形态AI评估数据集为主题,对数据集构建与质控要求进行了探讨,对数据集质量特性进行了解析,旨在指导数据集制造责任方加强数据集全生命周期管理,更好地为产品研发、测试、临床试验等环节提供质量保障,助力产业发展。

图书馆智慧管理平台书目数据融合若干问题分析——以河海大学图书馆为例

文章通过分析河海大学图书馆智慧管理平台下的书目数据融合项目的实践,总结了数据库中书目数据存在的问题及原因,从编目人员、编目外包公司、图书馆自身3个维度提出优化策略,以提升图书馆的编目业务的质量,促进图书馆编目事业稳定健康的发展。

企业数据跨境流动的风险防控研究

随着大数据经济的发展,数据已经成为各国竞相争夺的数字资源。通过分析企业数据的内涵及特征,根据我国企业数据跨境流动现状,探讨了企业面临的内部数据合规管理体系不完善、数据监管机构不明确等难题。目前许多国家就数据跨境流动提出了解决方案,在此基础上通过建立系统性跨境数据流动法律规范体系、加强国际合作等方式、设置独立的数据监管机构,提升我国数字企业核心竞争力,降低开拓境外市场的合规风险。

政府大数据思维下宏观调控的理论分析

宏观调控是政府为解决信息不完全导致市场失灵问题所采取的政策措施。信息通信技术、互联网技术、大数据分析和人工智能等可以在一定程度上改善信息不完全的问题,这些技术正在驱动着政府运用大数据思维进行宏观调控。我们分析政府大数据思维及大数据思维下的宏观调控,首先要在理论上解读信息和大数据的关系,其次是说明政府大数据思维的形成过程,再次是解说政府宏观调控的操作程序和过程,最后对政府大数据思维下的宏观调控效用进行评价。大数据思维的本质仍然是因果思维,但大数据时代的因果逻辑思维模式与工业化时代的因果逻辑思维模式不是一回事。政府作为宏观调控的行为主体,从大数据思维进入大数据分析这一过程,包含着极其丰富的内容,可考虑从信息通信技术、大数据、互联网和人工智能等相互融合的角度对其逻辑分析框架展开探讨。有了这样的逻辑分析框架,我们可以描绘出政府对未来数字经济运行进行宏观调控有可能展现的一般图景。

党“管”数据:基于政企数据权力演化的治理逻辑

数据是治国理政的重要资源,党“管”数据则是推动国家治理体系和治理能力现代化的关键路径。而在数据资源的流动下发生着数据权力的动态演化,存在政企主体数据发展优势表现不同,且需平衡少数大型企业依托政府数据资源优势异化形成数据权力的利弊影响,呈现出党“管”数据的需求。基于此,本文将从静态视角和动态视角分析政企主体间数据权力的形成和异化,从理论与实践的角度分别阐释党“管”数据的必要逻辑,进而探讨中国特色治理模式下党“管”数据的实现路径。研究认为,党“管”数据是制度优势、组织架构和安全发展的必然要求,是规制政企数据权力动态异化的必然选择,并凝练出“1+4”治理路径,推进实现善治目标与国家治理体系和治理能力现代化。

铁路房建工程数据管控系统软件研发

针对铁路房建工程中存在人工汇总效率低、标准不统一、易出错等问题,开发一套铁路房建工程数据管控系统软件。该系统通过制定房建标准化分类命名及标准化的提资模板,实现数据的批量导入;同时通过输入相关参数,可以自动配置全线房屋并汇总房屋相关需求数据,各专业可以通过该系统开展具体的设计并将设计数据汇总至系统中,形成房建数据湖,并利用数据湖生成各专业的数据统计表格。该系统解决了日常工作中专业间提资数据不完整、不可信、获取慢等问题,并实现设计数据的即时共享,大幅提高设计效率及质量,促进铁路房建工程的数字化转型,有力支持以铁路全专业为主体的协同设计系统的研发。