In the era of “big data,” a huge number of people, devices, and sensors are connected via digital networks and the cross‐plays among these entities generate enormous valuable data that facilitate organizations to innovate and grow. However, the data deluge also raises serious privacy concerns which may cause a regulatory backlash and hinder further organizational innovation. To address the challenge of information privacy, researchers have explored privacy‐preserving methodologies in the past two decades. However, a thorough study of privacy preserving big data analytics is missing in existing literature. The main contributions of this article include a systematic evaluation of various privacy preservation approaches and a critical analysis of the state‐of‐the‐art privacy preserving big data analytics methodologies. More specifically, we propose a four‐dimensional framework for analyzing and designing the next generation of privacy preserving big data analytics approaches. Besides, we contribute to pinpoint the potential opportunities and challenges of applying privacy preserving big data analytics to business settings. We provide five recommendations of effectively applying privacy‐preserving big data analytics to businesses. To the best of our knowledge, this is the first systematic study about state‐of‐the‐art in privacy‐preserving big data analytics. The managerial implication of our study is that organizations can apply the results of our critical analysis to strengthen their strategic deployment of big data analytics in business settings, and hence to better leverage big data for sustainable organizational innovation and growth.
This article is categorized under:
Commercial, Legal, and Ethical Issues > Security and Privacy
Fundamental Concepts of Data and Knowledge > Big Data Mining
Fundamental Concepts of Data and Knowledge > Data Concepts
A circular cavity resonance method is improved to measure the frequency dependence of complex permittivity of a dielectric plate by using multimode TE 0m1 with integer m of the higher order. The measurement principle is based on a rigorous analysis by the Ritz-Galerkin method. A new circular cavity with lowered height is designed to decrease the number of unwanted modes near the TE 0m1 modes from a mode chart of a cavity. Then the frequency dependence of a glass cloth PTFE dielectric plate is measured over the frequency range 15~35GHz by using TE 0m1 (m=1, 2, 3, 4) modes in a circular cavity designed at 20GHz for the TE 011 mode. The measured results are compared with ones measured by using the conventional four different size cavities with TE 011 mode. It is verified that the designed cavity structure is useful to measure the frequency dependence of a dielectric plate.
Abstract-Peak to Average Power Ratio (PAPR) of OrthogonalFrequency Division Multiplexing (OFDM) is a long-standing problem which has been hindering its performance for decades. In this paper, we propose a new PAPR reduction scheme based on shifting pilot locations among the data symbols. Since no side information is sent to the receiver about the pilot locations, a novel pilot detection algorithm is devised here exploiting the pilot power and the relative constant distance property of pilots. The proposed scheme attains around 1.5 dB PAPR reduction. The pilot detection accuracy is shown to be very excellent ranging from 80% to 99% at 0 dB of Signal to Noise Ratio (SNR) in different parameters. This scheme is very spectrally efficient with reduced complexity without degrading BER performance significantly.
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