E-government Data Research Articles

A blockchain-enabled decentralized access control scheme using multi-authority attribute-based encryption for edge-assisted Internet of Things

More edge users opt to use Internet of Things (IoT) devices to collect their data (e.g., health data, social data, e-governance data, etc.), which are stored in central cloud service providers (CSPs). However, this compromises data privacy and creates issues with collusion attacks. Current ciphertext-policy attribute-based encryption (CP-ABE) schemes with and without blockchain have only partially addressed these issues. Ongoing challenges remain to be resolved, including large-universe attribute management, secret key verification, and malicious attribute authorities (AAs) tracking. Therefore, we propose a decentralized access control scheme (namely BLUMA-CPABE) integrating blockchain with multi-authority ciphertext-policy attribute-based encryption (MA-CP-ABE). The scheme not only supports large-universe, policy hiding, and AAs tracking, but it also utilizes on- and off-chain mechanisms to alleviate the computation burden of the blockchain. In addition, we develop a verifiable key distribution approach in which AAs are configured as blockchain consensus nodes capable of issuing, signing, validating, and disseminating secret keys as transactions on-chain. It guarantees the keys’ security and reliability. To incentivize authorities to control newly added attributes proactively for large-universe, we enhance the Proof-of-Authority (called PoA＋) consensus mechanism in multi-authority scenarios. It allows authorities to take turns proposing and confirming new blocks based on three contribution indicators: attribute management contribution, data decryption contribution, and block validation gain. The proposed scheme is proven statically secure while resisting collusion attacks. The experimental results demonstrate the feasibility and efficiency of our scheme.

Covid-19 Pandemic and Digital Public Awareness Platforms: Strategies, Solutions, and Tools of Communication and e-Government Data Management

Abstract The global outbreak of the Covid-19 pandemic has forced governments around the world to launch various digital information campaigns in an attempt to boost public awareness about the virus and increase public information on effective measures to prevent its diffusion in local communities. Different public relations and data preservation, data retention, and data distribution strategies have been applied by healthcare policymakers to initiate, implement, and promote a wide range of public information campaigns, unique open data-driven platforms, and related digital solutions and tools to achieve the goal. Likewise, they were driven by different motivations and priorities as well as demands and political signals that they received from both top government leadership and civil society. In this regard, it is interesting to analyze how these different public relations and data management strategies were manifested in real administrative and technological practices, what priorities policymakers put in promoting such digital platforms, what communication and data management tools they used, and how effective they were in raising public awareness about the pandemic via such digital information platforms and related data-driven projects, startups, and initiatives.

A novel approach for E-Government services with artificial intelligence using CNN

Artificial Intelligence (AI) is a domain that works on various complex applications, such as E-government services. In order to provide government services to the people, an online AI-based Deep Learning (DL) model has been developed to check the availability of government schemes. However, several E-government services are not available to the citizens based on their usage. Many challenges have been identified while using E-Government services. This paper introduces the DL model, Convolutional Neural Networks (CNN), to solve the issues in E-Government services. The system focuses on maintaining E-government data resources, and CNN is primarily used to automate E-Government services. Finally, CNN has developed an innovative E-Government environment to support the design, development, and implementation of applications.

Study on Evaluation of Development of Guilin E-Government Based on E-Government Development Index

E-government has become an important direction for the development of our government. Measuring national and regional e-government development indicators can help government agencies better understand the actual situation of e-government. This paper is based on E-government Development Index, including the Online Services Index (OSI), Telecommunications Infrastructure Index (TII) and Human Capital Index (HCI). The development of e-government in Guilin is evaluated by using the methods of index change analysis and comparative analysis. The relevant data of this paper come from Guangxi Statistical Yearbook, Guilin Economic and Social Statistical Yearbook and the official website of Guilin Bureau of Statistics. From the study of Guilin e-government data, we judged that Guilin e-government is in the trend of rapid development and comprehensive and coordinated development. Through its development trend, we can judge that in the future, Guilin e-government will continue to develop, but at the same time, if we do not deal with the relationship between development speed and development content, it will also bring great trouble to Guilin e-government. Therefore, we put forward the following development suggestions: (1) Guilin e-government should strengthen technological innovation and development, and create an intelligent e-government platform. (2) Guilin e-government will make government services more targeted and build a service platform for special groups. (3) Guilin e-government should formulate e-government policies and improve institutional innovation.

Fully Homomorphic Encryption for Cloud Based E-Government Data

Cloud computing is a way of providing services, networks, hardware, storage, and interfaces for the construction of E-Government infrastructure that enables the delivery of services efficiently and achieves cost savings. Cloud services enable individuals and organizations to utilize cloud providers’ software and hardware resources stored remotely. The span between the client and the actual location of his data provides a barrier because this data can be obtained by a third party, risking the citizen’s data privacy. We examine a method based on the Fully Homomorphic Encryption (FHE) scheme in order to facilitate the processing of sensitive information pertaining to the E-Government that does not involve the disclosure of the original data. In this paper, we consider some general data operations to evaluate the feasibility of the FHE method and show that the accuracy are similar when data operations are applied to homomorphically encrypted data. The results of the experiment highlight the potential of the various privacy-preserving data operations that can be performed under FHE approach. These methods provide results that are equivalent to those achieved by unencrypted data and models within a decent amount of time.

Big Data in E-government: Classification and Prediction using Machine Learning Algorithms

Many countries have used big data to develop their institutions, such as Estonia in policing, India in health care, and the development of agriculture in the United Kingdom, etc. Data is very important as it is no longer oil that is the most valuable resource in the world, but data. This research examines ways to develop the Iraqi state institutions by using the big data of one of its institutions (electronic civil registry) (ECR) using the mining and analysis of this data. The pre-processing and analysis of this data are carried out depending on the needs of each institution and then using Machine Learning (ML) techniques. Its use has shown remarkable results in many areas, especially in data analysis, classification and forecasting. We applied five ML algorithms that are Support Vector Machine (SVM), Decision Tree (DT), K-Nearest Neighbor (KNN), Random Forest (RF), and Naive Bayes (NB) carried out in the Orange Data Mining tool. According to the simulation results of the proposed system, the accuracy of the classifications was around 100%, 99%, and 100% for the military department by the SVM classifier, the social welfare department by the RF classifier, and the statistics-planning department by the SVM classifier, respectively.

Fuzzy based Security Risk Assessment of e-Government Data Centre in Indian Context

Fuzzy based Security Risk Assessment of e-Government Data Centre in Indian Context

Fuzzy based security risk assessment of e-government data centre in Indian context

Fuzzy based security risk assessment of e-government data centre in Indian context

A review of effectiveness of Saudi E-government data security management

Security of data has always been a contested issue since the internet became the way of life. The internet and Web 2.0 followed by Web 3.0 have enabled many applications for the use of the citizens. E-government is one of them. Questions have always been raised about the security of data in E-government applications and services. Saudi Arabia is one of the developing countries when it comes to the internet-based services. This paper attempts to review the effectiveness of security policies when dealing with threats and vulnerabilities. We shall study these aspects in the context of Saudi Arabian E-government. E-government, anywhere in the world is a very sensitive area when it comes to ensuring security of the users as well as the corporate data. Breach in security of user data may have catastrophic implications in some cases.

Construction of E-government Data Sharing Framework Based on Big Data Technology

With the continuous development of Internet technology, more and more fields are beginning to use Internet technology to improve their business construction. Moreover, in terms of e-government construction, introducing the Internet technology into e-government work at all levels is also an important content, and the Party Central Committee has proposed a series of major decisions such as network power and “Internet +” to accelerate the process of e-government informatization. Meanwhile, big data virtualization technology and access control technology are used to break through e-government data sharing barriers to realize virtual integration and trusted sharing across e-government data and support multi-departmental, crosslevel, and cross-network data security interactive processing for e-government business collaboration. Besides, the multi-source circulation and on-demand access of cross-departmental e-government data are realized to break data barriers, form data transmission links, and create a model for exchanging and sharing e-government data. Through the exchange and sharing of e-government data, the barrier-free flow of information can be achieved and the efficiency of e-government business handling can be improved as well.

Documenting Context-Based Quality Assessment of Controlled Vocabularies

Access to e-Government data is challenging due to the heterogeneity and complexity of the public information ecosystem. Controlled Vocabularies (CVs) provide a key to disclosing the potential of Open Government data, by supplying common terms for marking up metadata and data in a consistent and coherent way. However, quality information is needed to help public institutions decide whether to adopt an existing or newly created CV. The paper discusses how to evaluate and document CV quality thus facilitating a comparison of different controlled vocabularies based on contextual information. The Analytical Hierarchy Process (AHP) is adopted to assess the overall quality and rank of a controlled vocabulary, by integrating various quality dimensions according to the decision maker's needs. A set of e-Government controlled vocabularies that facilitate the semantic interoperability of e-Government data are selected as a testbed, and updated quality values are made available as Linked Data. Multi-step guidelines are also defined promoting and complementing the adoption of W3C recommendations to provide machine-readable quality metadata. This fosters reliability and re-usability by providing consumers with information on the assessment process carried out and the outcomes achieved. We illustrate the application of these guidelines by focusing on provenance and quality documentation.

Role of E-Government and Open Data to Enhance Transparency Practices

E-government involves the use of latest skills by the government while providing the services and other information management systems to its citizens. Open data refers to the openness of all the data related to government to its citizens so that the government becomes more and more transparent and to decrease negative activities. Transparency refers to the clear and clean image of a government towards its people, which increases the trust of people on their government. The motive of this study is to analyze the impact of e-government adoption and open government data on transparency in ASEAN countries. Two control variables i.e. literacy rate and corruption have also been used in the study. The past literature has also been discussed in literature review section of this study. In order to conduct research, data about the concerned variables of the study has been collected from ASEAN countries consisting of 29 years. After applying several tests and approaches for research purpose, the two major hypotheses of this study are accepted along with the impact of a control variable, corruption. However, the impact of other control variable i.e. literacy rate has been rejected. There are various theoretical, practical and policy making benefits that will increase the transparency.

Security knowledge representation of e-government data centre through ontology

Security knowledge representation of e-government data centre through ontology

Security Knowledge Representation of e-Government Data Centre Through Ontology

Security knowledge is the heart of an e-government data centre. The knowledge refers to information gained through learning and experience. It is well known that security requirements of a community data centre are changing rapidly which are mostly formless and lack formal representation yet. It is therefore, felt essential to have a model for a community data centre that can support knowledge sharing and reuse in an explicit and mutually agreed manner. We have developed a security knowledge-based, ontology-centric framework for e-government data centre. Our framework that demonstrates correlation between high-level policy statements based on information system security standards and deployable security controls which are implementable and the objectives are achievable. This framework may support security expert activities with respect to security requirements, application and management of respective security controls and their countermeasures. We have tried to implement our model in a neutral manner.

Using microdata for international e-Government data exchange: The case of social security domain

Semantic interoperability issues of international e-Government data exchanges have not been solved up until now. In the case of social security institutions, the data exchange operations have some particularities that make that the non-ambiguous definition of core concepts used in the institutions has a key impact on the success and quality of system interconnections. In this article, we present the result of a research to implement a new metadata specification based in Dublin Core elements for international social security exchanges, named Exchange Social Security Information Metadata (ESSIM). This proposal is based in a semantic approach using Linked Data for Interoperability, with technologies, such as RDF(S), SPARQL, Microdata and JSON-LD, in order to ensure interoperability between social security institutions from different countries. This will help to strengthen the protection of the social security rights of mobile workers by automating the application of international agreements on social security and to improve cross border communication between social security institutions of different countries. For the near future, the goal is to include this specification as part of information and communication technology Guidelines under development by International Social Security Association with the participation of authors of this article. This will facilitate a future adoption of the specification as an international standard.

Research and Application of Big Data in E-government

The wide use of modern electronic information technology, represented by big data technology, has brought people into the era of big data. Big data is affecting our work, life, even economy and the development of the society. Nowadays, the application of big data technology in e-government speeds up the development of e-government, which is important for the overall construction of e-government. This paper summarizes the application of the big data, introduces the application of big data technology in e-government. Then this paper analyzes the current situation and problems of e-government development. Finally this paper proposes the solutions of big data platform in e-government.

Big data driven e-government framework in Nigeria

Many nations of the world are employing the use of big data in e-government for integrated policy making. However, in Nigeria, data-driven decision making is still a challenge due to lack of a centralized framework that can integrate different silo data centers for insightful and evidence- based governance. The paper proposes a big data-driven e-government framework for e- governance operations. The framework was designed in the Nigerian context using big data mechanisms. It was tested with an experiment that performed a sentiment analysis to uncover the opinion of the masses on selected agencies in order to help policy making. This was done with datasets collected from the social media handles of two (2) government agencies – the Nigerian police force and the Nigerian army. The results uncovered the actual opinions of the populace concerning both agencies as it regards national security. The framework promises a host of benefits such as centralized data entry point for governance, data harvesting system, seamless integration and collaboration of government operations and an easy application of open data policy. The paper concludes with four (4) recommendations which the government of any developing nation can imbibe for results-oriented e-governance and increase the quality of service to citizens and businesses. Keywords: big data, data, e-government, e-governance, framework, hadoop, sentiment analysis

Empirical analysis of Birth Registration E-governance data using Naïve Bayes Data Mining

Empirical analysis of Birth Registration E-governance data using Naïve Bayes Data Mining

IMPLEMENTATION OF NAÏVE BAYESIAN DATA MINING ALGORITHM ON DECEASED REGISTRATION DATA

The use of data mining algorithm in different domains like marketing, finance, retail, cyber security, fraud detection, medical science, etc… is well known. In recent times, the data mining is also implemented for e-governance data. Normally, e-governance data are only used for Online Transaction Processing System (OLTP). However, one can use data mining algorithm to uncover hidden and new trends from e-governance data. In this paper, Naive Bayes data mining algorithm is applied on Deceased Registration data to find hidden trends.

IMPLEMENTATION OF ARTIFICIAL NEURAL NETWORK ALGORITHM ON VEHICLE REGISTRATION DATA

An Artificial Neural Network can be implemented to solve variety of problems. An Artificial Neural Network has been used in different domains like Finances, Marketing, Healthcare, Image Processing, Crime Detection, Weather Forecasting, Economics, Voice Recognition etc…In last few years, Government institutions around the world also started using an Artificial Neural Network on e-governance data. In this paper, an Artificial Neural Network is applied on Vehicle Registration Data to uncover interesting relationship among various attributes.