Towards Data Privacy and Security Framework in Big Data Governance

N.Maniam, Jacentha; Singh, Dalbir

doi:10.15282/ijsecs.6.1.2020.5.0068

Cited by 23 publications

(9 citation statements)

References 17 publications

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“…We used analytic data mined from the CIS database using Crystal Report Tools for the years of 2017. Data analytics is the application of tests on information that is electronically available, either from the Enterprise's Resource Planning (ERP) systems or through brokers' databases and other digital sources (Arlyn, 2019;Jacentha & Dalbir, 2020;Wahdain, Baharudin & Ahmad, 2019). The analytical data obtained are particulars of K1 digital forms which is used for declaration and releasing of goods under Customs control.…”

Section: Data and Methodology Data Sources And Componentsmentioning

confidence: 99%

Integrity Risk in The Customs Automation System

Omar¹,

Selamat²,

Aziz³

et al. 2021

IJARAFMS

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The major benefits of transforming the Customs manual system into automation is making data processing faster, reduce time delay and increase transparency for the international logistics management. A robust digital system of automation by default is assumed to be able to barricades any mistake made by parties involved in the process of declaration, assessing, and releasing goods from the Customs control. In this paper, we focused on the Integrity issues concerning the result of using the Customs Information System (CIS) in Malaysia as it is the only automation software used by The Royal Malaysian Customs for processing and releasing goods under its control. As a semi-digital system, CIS has its advantages and disadvantages that may affect integrity issues among Customs officials who administrated it. In this article, we used 795 samples of analytic data for imported prefabricated used vehicles (Toyota Wish) mined from CIS databank to examine whether this output data is administrated consistent, or otherwise, deteriorate with the requirements stipulated under the Customs importation rules and circulars in force? Our focus of analyses will be on the examination of how far the items in K1 electronic forms, namely tariff code declaration, vehicles first registration date, CIF value, imposed tax rates, physical check of vehicles and approval permit is consistent with the Customs Taxation law and Circulars. The finding shows that many output data are inconsistent with the current tax laws and circulars in force. These include 28.05% inaccurate samples for tariff code declaration, 80.63% that are not declared the vehicles first registration date in the origin country, and 98.62% are declared false or wrong CIF values. We found that CIS also failed to include the detailed records of vehicles year's made, VIN, seating capacity and the engine type as required by K-1 form. The output data also shows that there are 3% of samples charged with an inaccurate excise duty rate for different types of vehicles models or variants. In the physical inspection records, data showed that 100% of prefabricated vehicles brought in were not marked as inspected via CIS module. Meanwhile, for AP records, 73.21% of samples do not have valid approved permits and were classified as Record Not Found (RNF), while 7.05% have expired AP. This evidence shows that CIS is a weak automation software and can be manipulated by the parties involved in the transaction process, either Customs officials or company agents. The main disadvantage is the design of the software that permit users to input value that may be incorrect, inaccurate,

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Section: Data and Methodology Data Sources And Componentsmentioning

confidence: 99%

Integrity Risk in The Customs Automation System

Omar¹,

Selamat²,

Aziz³

et al. 2021

IJARAFMS

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“…Se denominan big data (BD) al conjunto de datos estructurados y no estructurados generados a gran escala por diversas organizaciones y entidades sociales, debido que muchas actividades humanas suelen dejar huellas digitales producto de casi todas las actividades diarias realizadas, como cada vez que alguien está en línea sea mediante un teléfono inteligente equipado con GPS o por interacción a través de las redes sociales o realizando compras on-line (Singh, 2020;Gregory & Halff, 2020). Por otro lado, Castro et al (2021) manifestaron que BD supera el hecho de ser más que procesar volúmenes masivos de datos, ya que asume una amplia gama de aspectos tales como la variabilidad múltiple de las fuentes de datos, la alta velocidad de cambio de datos y la garantía de veracidad de los datos para generar valor a las empresas con la transformación de los datos en conocimiento.…”

Section: Introductionunclassified

Gestión pública y gobernanza para el desarrollo de los pueblos

2023

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La Gestión Pública contempla tomar decisiones adecuadas y realizar acciones concretas con el fin de generar bienestar en las personas y la sociedad; la gobernanza puede ser la ruta adecuada para conseguir dar soluciones a los problemas que afronta el Perú. La Gestión pública y la Gobernanza, en los países de Latinoamérica, son aspectos relevantes que requieren de la reflexión de la comunidad científica dado que su eficacia y eficiencia implican un mejor estilo de vida de la población. Por esta razón el presente libro tiene como fin dar una mirada académica a diversos aspectos vinculados con la Gestión Pública en el Perú y América del Sur, la cual es entendida como el conjunto de procesos y operaciones que realizan las organizaciones o entidades del sector público para administrar los recursos que disponen. Implica que los gestores o funcionarios públicos, tengan competencias sobre aplicación de proyectos de inversión, gestión por resultados y gestión por procesos en el marco de la gestión de calidad. Inicia el primer capítulo con una reflexión sobre la Gobernanza y los problemas comunes que afectan a la región como son: la corrupción, inseguridad ciudadana, la dificultad de afrontar los problemas ambientales como el manejo de los desechos y la violencia contra la mujer.

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“…The vast influence of emerging computing techniques has encouraged the generation of large data volumes in the past few years, leading to the trending concept known as "big data" [1,2]. Data publishing assists many research institutions in running big data analytic operations to reveal the information embedded and provide several opportunities with great unprecedented benefits in many fields [3].…”

Section: Introductionmentioning

confidence: 99%

“…Data publishing assists many research institutions in running big data analytic operations to reveal the information embedded and provide several opportunities with great unprecedented benefits in many fields [3]. This process helps organizations improve their efficiency and future plans [1,[4][5][6]. Analyzing big data and extracting new knowledge while protecting sensitive information is now considered as one of the imperative needs [7].…”

Section: Introductionmentioning

confidence: 99%

Slicing-Based Enhanced Method for Privacy-Preserving in Publishing Big Data

BinJubier¹,

Ismail²,

Ahmed³

et al. 2022

Computers, Materials &Amp; Continua

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Publishing big data and making it accessible to researchers is important for knowledge building as it helps in applying highly efficient methods to plan, conduct, and assess scientific research. However, publishing and processing big data poses a privacy concern related to protecting individuals' sensitive information while maintaining the usability of the published data. Several anonymization methods, such as slicing and merging, have been designed as solutions to the privacy concerns for publishing big data. However, the major drawback of merging and slicing is the random permutation procedure, which does not always guarantee complete protection against attribute or membership disclosure. Moreover, merging procedures may generate many fake tuples, leading to a loss of data utility and subsequent erroneous knowledge extraction. This study therefore proposes a slicingbased enhanced method for privacy-preserving big data publishing while maintaining the data utility. In particular, the proposed method distributes the data into horizontal and vertical partitions. The lower and upper protection levels are then used to identify the unique and identical attributes' values. The unique and identical attributes are swapped to ensure the published big data is protected from disclosure risks. The outcome of the experiments demonstrates that the proposed method could maintain data utility and provide stronger privacy preservation.

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Towards Data Privacy and Security Framework in Big Data Governance

Cited by 23 publications

References 17 publications

Integrity Risk in The Customs Automation System

Integrity Risk in The Customs Automation System

Gestión pública y gobernanza para el desarrollo de los pueblos

Slicing-Based Enhanced Method for Privacy-Preserving in Publishing Big Data

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