PcAVP - Adaptable Vertical Partitioning Algorithm Based on Privacy Constraint for Distributed Database System

Vertical partitioning is a process of generating fragments, each of which is composed of attributes with high affinity. It is widely used in the distributed database to improve the efficiency of system by reducing the connection between the table access operations. The current research on vertical partitioning is mainly focused on how to measure the "affinity" to get the best-fit vertical partitioning and the n-way vertical partitioning which support generating the specific number of fragments required by the user. In this paper, we propose a vertical partitioning algorithm based on privacy constraint. It supports both the best-fit vertical partitioning and the n-way vertical partitioning. It also provides the data privacy protection by privacy constraint checking. We conduct several experimental results to show that our algorithm not only keeps higher efficiency, but also provides data privacy protection.

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A federated interpretable scorecard and its application in credit scoring

International Journal of Financial Engineering ◽

10.1142/s2424786321420093 ◽

2021 ◽

pp. 2142009

Author(s):

Fanglan Zheng ◽

Erihe ◽

Kun Li ◽

Jiang Tian ◽

Xiaojia Xiang

Keyword(s):

Privacy Protection ◽

Data Privacy ◽

Credit Scoring ◽

Training Session ◽

Model Performance ◽

Parameter Tuning ◽

Kolmogorov Smirnov ◽

Data Privacy Protection ◽

Tuning Process ◽

Positive Coefficients

In this paper, we propose a vertical federated learning (VFL) structure for logistic regression with bounded constraint for the traditional scorecard, namely FL-LRBC. Under the premise of data privacy protection, FL-LRBC enables multiple agencies to jointly obtain an optimized scorecard model in a single training session. It leads to the formation of scorecard model with positive coefficients to guarantee its desirable characteristics (e.g., interpretability and robustness), while the time-consuming parameter-tuning process can be avoided. Moreover, model performance in terms of both AUC and the Kolmogorov–Smirnov (KS) statistics is significantly improved by FL-LRBC, due to the feature enrichment in our algorithm architecture. Currently, FL-LRBC has already been applied to credit business in a China nation-wide financial holdings group.

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Is There a Better Option than the Data Transfer Model to Protect Data Privacy?

University of New South Wales Law Journal ◽

10.53637/mrob8894 ◽

2019 ◽

Vol 42 (2) ◽

Author(s):

Alan Toy ◽

Gehan Gunasekara

Keyword(s):

Privacy Protection ◽

Data Privacy ◽

Data Transfer ◽

Business Environment ◽

Transfer Model ◽

Privacy Rights ◽

Choice Of Law ◽

Privacy Laws ◽

Data Privacy Protection ◽

Extraterritorial Jurisdiction

The data transfer model and the accountability model, which are the dominant models for protecting the data privacy rights of citizens, have begun to present significant difficulties in regulating the online and increasingly transnational business environment. Global organisations take advantage of forum selection clauses and choice of law clauses and attention is diverted toward the data transfer model and the accountability model as a means of data privacy protection but it is impossible to have confidence that the data privacy rights of citizens are adequately protected given well known revelations regarding surveillance and the rise of technologies such as cloud computing. But forum selection and choice of law clauses no longer have the force they once seemed to have and this opens the possibility that extraterritorial jurisdiction may provide a supplementary conceptual basis for championing data privacy in the globalised context of the Internet. This article examines the current basis for extraterritorial application of data privacy laws and suggests a test for increasing their relevance.

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Dealing with Data Privacy Protection

IS Management Handbook, 8th Edition ◽

10.1201/9781420031393.ch56 ◽

2003 ◽

Author(s):

Fritz Grupe ◽

William Kuechler ◽

Scott Sweeney

Keyword(s):

Privacy Protection ◽

Data Privacy ◽

Data Privacy Protection

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Challenges Posed by Biometric Technology on Data Privacy Protection and the Way Forward

Ethics and Policy of Biometrics - Lecture Notes in Computer Science ◽

10.1007/978-3-642-12595-9_1 ◽

2010 ◽

pp. 1-6 ◽

Cited By ~ 1

Author(s):

Roderick B. Woo

Keyword(s):

Privacy Protection ◽

Data Privacy ◽

Biometric Technology ◽

Data Privacy Protection ◽

The Way

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Localization of Data Sets in Distributed Database Systems Using Slope-Based Vertical Fragmentation

Handling Priority Inversion in Time-Constrained Distributed Databases - Advances in Data Mining and Database Management ◽

10.4018/978-1-7998-2491-6.ch003 ◽

2020 ◽

pp. 36-60

Author(s):

Ashish Ranjan Mishra ◽

Neelendra Badal

Keyword(s):

Database Systems ◽

Distributed Database ◽

Communication Cost ◽

Data Sets ◽

Distributed Database Systems ◽

The Third ◽

Vertical Partitioning ◽

Vertical Fragmentation ◽

Partitioning Algorithm ◽

Better Than

This chapter explains an algorithm that can perform vertical partitioning of database tables dynamically on distributed database systems. After vertical partitioning, a new algorithm is developed to allocate that fragments to the proper sites. To accomplish this, three major tasks are performed in this chapter. The first task is to develop a partitioning algorithm, which can partition the relation in such a way that it would perform better than most of the existing algorithms. The second task is to allocate the fragments to the appropriate sites where allocating the fragments will incur low communication cost with respect to other sites. The third task is to monitor the change in frequency of queries at different sites as well as same site. If the change in frequency of queries at different sites as well as the same site exceeds the threshold, the re-partitioning and re-allocation are performed.

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