An Encryption Methodology for Enabling the Use of Data Warehouses on the Cloud

2018 ◽  
Vol 14 (4) ◽  
pp. 38-66 ◽  
Author(s):  
Claudivan Cruz Lopes ◽  
Valéria Cesário-Times ◽  
Stan Matwin ◽  
Cristina Dutra de Aguiar Ciferri ◽  
Ricardo Rodrigues Ciferri
Keyword(s):  
Data Warehouse ◽  
Homomorphic Encryption ◽  
Distributed Database ◽  
Symmetric Encryption ◽  
Data Confidentiality ◽  
Cloud Data ◽  
Use Of Data ◽  
Star Schema ◽  
Different Types ◽  
Definition Of

A cloud data warehouse (cloud DW) is a subject-oriented, integrated, time-variant, voluminous, nonvolatile and multidimensional distributed database that is hosted in a cloud. A solution to ensure data confidentiality for a cloud DW is cryptography. In this article, the authors propose an encryption methodology for a cloud DW stored according to the star schema, considering both the data confidentiality maintenance of the DW and the capability of processing analytical queries directly over the encrypted DW. The proposed encryption methodology comprises an encryption strategy for DW called MV-HO (MultiValued and HOmomorphic) for the definition of how the different types of DW's attributes must be encrypted. The proposed MV-HO encryption strategy was compared with encryption strategies based on symmetric encryption, order preserving symmetric encryption and homomorphic encryption. Results indicated that MV-HO is the best solution found, as MV-HO is pareto-optimal with respect to other strategies investigated.

An Encryption Methodology for Enabling the Use of Data Warehouses on the Cloud

2021 ◽  
pp. 528-559
Author(s):  
Claudivan Cruz Lopes ◽  
Valéria Cesário-Times ◽  
Stan Matwin ◽  
Cristina Dutra de Aguiar Ciferri ◽  
Ricardo Rodrigues Ciferri
Keyword(s):  
Data Warehouse ◽  
Homomorphic Encryption ◽  
Distributed Database ◽  
Pareto Optimal ◽  
Symmetric Encryption ◽  
Data Confidentiality ◽  
Cloud Data ◽  
Use Of Data ◽  
Star Schema ◽  
Definition Of

A cloud data warehouse (cloud DW) is a subject-oriented, integrated, time-variant, voluminous, nonvolatile and multidimensional distributed database that is hosted in a cloud. A solution to ensure data confidentiality for a cloud DW is cryptography. In this article, the authors propose an encryption methodology for a cloud DW stored according to the star schema, considering both the data confidentiality maintenance of the DW and the capability of processing analytical queries directly over the encrypted DW. The proposed encryption methodology comprises an encryption strategy for DW called MV-HO (MultiValued and HOmomorphic) for the definition of how the different types of DW's attributes must be encrypted. The proposed MV-HO encryption strategy was compared with encryption strategies based on symmetric encryption, order preserving symmetric encryption and homomorphic encryption. Results indicated that MV-HO is the best solution found, as MV-HO is pareto-optimal with respect to other strategies investigated.

scholarly journals Forward and Backward-Secure Range-Searchable Symmetric Encryption

2021 ◽  
Vol 2022 (1) ◽  
pp. 28-48
Author(s):  
Jiafan Wang ◽  
Sherman S. M. Chow
Keyword(s):  
Homomorphic Encryption ◽  
Inverted Index ◽  
Range Queries ◽  
Symmetric Encryption ◽  
Forward Security ◽  
Injection Attacks ◽  
Searchable Symmetric Encryption ◽  
Encrypted Database ◽  
Definition Of ◽  
Client Side

Abstract Dynamic searchable symmetric encryption (DSSE) allows a client to query or update an outsourced encrypted database. Range queries are commonly needed. Previous range-searchable schemes either do not support updates natively (SIGMOD’16) or use file indexes of many long bit-vectors for distinct keywords, which only support toggling updates via homomorphically flipping the presence bit. (ESORICS’18). We propose a generic upgrade of any (inverted-index) DSSE to support range queries (a.k.a. range DSSE), without homomorphic encryption, and a specific instantiation with a new trade-off reducing client-side storage. Our schemes achieve forward security, an important property that mitigates file injection attacks. Moreover, we identify a variant of injection attacks against the first somewhat dynamic scheme (ESORICS’18). We also extend the definition of backward security to range DSSE and show that our schemes are compatible with a generic upgrade of backward security (CCS’17). We comprehensively analyze the computation and communication overheads, including implementation details of client-side index-related operations omitted by prior schemes. We show high empirical efficiency for million-scale databases over a million-scale keyword space.

scholarly journals Data Confidentiality in Cloud using Multi-party Computation

2020 ◽  
Vol 9 (3) ◽  
pp. 58-62
Keyword(s):  
Homomorphic Encryption ◽  
Input Function ◽  
Third Parties ◽  
Current Paper ◽  
Public Key ◽  
Data Confidentiality ◽  
New Era ◽  
Cloud Data

A new era has approached where we are storing our information in cloud and performing several computations on powerful servers remotely. In cloud, data is not completely secured and sometimes under the control of untrusted Third parties. Some secured protocols are being implemented. The secure multi-party computation protocol, which is existing, demands the inputs to be encrypted using a public key. So, these reasons limit this Secure Multi-party computation to be employed. In the current paper, we put forward a protocol named homomorphic encryption where the input function is being encrypted by different key. This paper also uses Multi-party computation which is one of the most secured technique in cryptography

Facilitate Effective Decision-Making by Warehousing Reduced Data

2015 ◽  
Vol 7 (3) ◽  
pp. 36-64 ◽  
Author(s):  
Faten Atigui ◽  
Franck Ravat ◽  
Jiefu Song ◽  
Olivier Teste ◽  
Gilles Zurfluh
Keyword(s):  
Decision Making ◽  
Data Warehouse ◽  
Conceptual Modeling ◽  
Multidimensional Data ◽  
Meta Model ◽  
Star Schema ◽  
Effective Decision ◽  
Effective Decision Making ◽  
Definition Of ◽  
Reduced Data

The authors' aim is to provide a solution for multidimensional data warehouse's reduction based on analysts' needs which will specify aggregated schema applicable over a period of time as well as retain only useful data for decision support. Firstly, they describe a conceptual modeling for multidimensional data warehouse. A multidimensional data warehouse's schema is composed of a set of states. Each state is defined as a star schema composed of one fact and its related dimensions. The derivation between states is carried out through combination of reduction operators. Secondly, they present a meta-model which allows managing different states of multidimensional data warehouse. The definition of reduced and unreduced multidimensional data warehouse schema can be carried out by instantiating the meta-model. Finally, they describe their experimental assessments and discuss their results. Evaluating their solution implies executing different queries in various contexts: unreduced single fact table, unreduced relational star schema, reduced star schema and reduced snowflake schema. The authors show that queries are more efficiently calculated within a reduced star schema.

Performance Evaluation of Distributed Database Systems

2014 ◽  
Vol 13 (9) ◽  
pp. 4859-4867
Author(s):  
Khaled Saleh Maabreh
Keyword(s):  
Performance Evaluation ◽  
System Performance ◽  
Operation Mode ◽  
Database Systems ◽  
Distributed Database ◽  
Evaluation Study ◽  
Distributed Database Systems ◽  
Different Types ◽  
Distributed Database System ◽  
Distributed Database Management

Distributed database management systems manage a huge amount of data as well as large and increasingly growing number of users through different types of queries. Therefore, efficient methods for accessing these data volumes will be required to provide a high and an acceptable level of system performance.  Data in these systems are varying in terms of types from texts to images, audios and videos that must be available through an optimized level of replication. Distributed database systems have many parameters like data distribution degree, operation mode and the number of sites and replication. These parameters have played a major role in any performance evaluation study. This paper investigates the main parameters that may affect the system performance, which may help with configuring the distributed database system for enhancing the overall system performance.

A Strategy for Design of Marine Pollution Monitoring Studies

1986 ◽  
Vol 18 (4-5) ◽  
pp. 15-26 ◽  
Author(s):  
D. A. Segar ◽  
E. Stamman
Keyword(s):  
Information Needs ◽  
Marine Pollution ◽  
Monitoring Program ◽  
Pollution Monitoring ◽  
Systematic Evaluation ◽  
Management Information ◽  
Different Types ◽  
Management Context ◽  
Definition Of ◽  
Scientific Testing

Most historical marine pollution monitoring has proven useless in a management context. A strategy for development of effective marine pollution monitoring programs is outlined. This strategy is based on the following steps: 1) systematic evaluation of the management information needs, 2) identification of the hypothetical impacts associated with those management concerns, and 3) investigation of the feasibility of monitoring those effects such that the existence, or absence, of a specified level of effects can be established in a statistically-valid manner. There are two fundamentally different types of monitoring program: site-specific and regional. These two types of program differ markedly in scope and approach when designed through application of this strategy. The strategy requires development of null hypotheses which address management concerns and which are amenable to scientific testing. In order for the program to be successful, the null hypotheses selected for inclusion in a marine pollution monitoring program must address levels of effect which are predefined to be environmentally significant. The definition of environmentally significant effect levels is a difficult process which must be primarily the responsibility of the managerial community.

Low Size Cipher Text Homomorphic Encryption Scheme for Cloud Data

2017 ◽  
Vol 4 (1) ◽  
pp. 13-20
Author(s):  
Manish M. Potey ◽  
◽  
C. A. Dhote ◽  
Deepak H. Sharma ◽  
◽  
...  
Keyword(s):  
Homomorphic Encryption ◽  
Encryption Scheme ◽  
Cloud Data ◽  
Cipher Text

scholarly journals Virtual Loom: a tool for the interactive 3D representation of historical fabrics

2021 ◽  
Author(s):  
Cristina Portalés ◽  
Manolo Pérez ◽  
Pablo Casanova-Salas ◽  
Jesús Gimeno
Keyword(s):  
Art History ◽  
3D Modelling ◽  
Current Version ◽  
Close Collaboration ◽  
Design And Implementation ◽  
Different Types ◽  
Interactive 3D ◽  
Silk Fabrics ◽  
Definition Of ◽  
3D Representations

Abstract3D modelling of man-made objects is widely used in the cultural heritage sector, among others. It is relevant for its documentation, dissemination and preservation. Related to historical fabrics, weaves and weaving techniques are still mostly represented in forms of 2D graphics and textual descriptions. However, complex geometries are difficult to represent in such forms, hindering the way this legacy is transmitted to new generations. In this paper, we present the design and implementation of SILKNOW’s Virtual Loom, an interactive tool aimed to document, preserve and represent in interactive 3D forms historical weaves and weaving techniques of silk fabrics, dating from the 15th to the 19th centuries. To that end, our tool only requires an image of a historical fabric. Departing from this image, the tool automatically subtracts the design, and allows the user to apply different weaves and weaving techniques. In its current version, the tool embeds five traditional weaving techniques, 39 weaves and six types of yarns, which have been defined thanks to close collaboration of experts in computer graphics, art history and historical fabrics. Additionally, users can change the color of yarns and produce different 3D representations for a given fabric, which are interactive in real time. In this paper, we bring the details of the design and implementation of this tool, focusing on the input data, the strategy to process images, the 3D modelling of yarns, the definition of weaves and weaving techniques and the graphical user interface. In the results section, we show some examples of image analysis in order to subtract the design of historical fabrics, and then we provide 3D representations for all the considered weaving techniques, combining different types of yarns.

Embracing School Counselors’ Situatedness: Data-Based Decision Making as Fulfillment of a Complex Identity

2021 ◽  
Vol 24 (1_part_3) ◽  
pp. 2156759X2110119
Author(s):  
Brett Zyromski ◽  
Catherine Griffith ◽  
Jihyeon Choi
Keyword(s):  
Decision Making ◽  
School Counselors ◽  
School Counselor ◽  
Use Of Data ◽  
Counselor Identity ◽  
Using Data ◽  
Definition Of ◽  
Support Students ◽  
Students Success ◽  
Data Based Decision Making

Since at least the 1930s, school counselors have used data to inform school counseling programming. However, the evolving complexity of school counselors’ identity calls for an updated understanding of the use of data. We offer an expanded definition of data-based decision making that reflects the purpose of using data in educational settings and an appreciation of the complexity of the school counselor identity. We discuss implications for applying the data-based decision-making process using a multifaceted school counselor identity lens to support students’ success.

scholarly journals Models Applied to Grapevine Pests: A Review

Insects ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 169
Author(s):  
Federico Lessio ◽  
Alberto Alma
Keyword(s):  
Lobesia Botrana ◽  
Grape Berry ◽  
Homalodisca Vitripennis ◽  
Flavescence Dorée ◽  
Or Groups ◽  
Scaphoideus Titanus ◽  
Different Types ◽  
Computer Based ◽  
Biological Aspects ◽  
Definition Of

This paper reviews the existing predictive models concerning insects and mites harmful to grapevine. A brief conceptual description is given on the definition of a model and about different types of models: deterministic vs. stochastics, continuous vs. discrete, analytical vs. computer-based, and descriptive vs. data-driven. The main biological aspects of grapevine pests covered by different types of models are phenology, population growth and dynamics, species distribution, and invasion risk. A particular emphasis is put on forecasting epidemics of plant disease agents transmitted by insects with sucking-piercing mouthparts. The most investigated species or groups are the glassy-winged sharpshooter Homalodisca vitripennis (Germar) and other vectors of Xylella fastidiosa subsp. fastidiosa, a bacterium agent of Pierce’s disease; the European grape berry moth, Lobesia botrana (Denis and Schiffermuller); and the leafhopper Scaphoideus titanus Ball, the main vector of phytoplasmas agents of Flavescence dorée. Finally, the present and future of decision-support systems (DSS) in viticulture is discussed.

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