Simplifying Data Disclosure Configurations in a Cloud Computing Environment

Ron S. Hirschprung

doi:10.1145/2700472

2015-04-30

PRE

DOI：10.1145/2700472

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摘要

En 中文

Cloud computing offers a compelling vision of computation, enabling an unprecedented level of data distribution and sharing. Beyond improving the computing infrastructure, cloud computing enables a higher level of interoperability between information systems, simplifying tasks such as sharing documents between coworkers or enabling collaboration between an organization and its suppliers. While these abilities may result in significant benefits to users and organizations, they also present privacy challenges due to unwanted exposure of sensitive information. As information-sharing processes in cloud computing are complex and domain specific, configuring these processes can be an overwhelming and burdensome task for users. This article investigates the feasibility of configuring sharing processes through a small and representative set of canonical configuration options. For this purpose, we present a generic method, named SCON-UP (Simplified CON-figuration of User Preferences). SCON-UP simplifies configuration interfaces by using a clustering algorithm that analyzes a massive set of sharing preferences and condenses them into a small number of discrete disclosure levels. Thus, the user is provided with a usable configuration model while guaranteeing adequate privacy control. We describe the algorithm and empirically evaluate our model using data collected in two user studies (n = 121 and n = 352). Our results show that when provided with three canonical configuration options, on average, 82% of the population can be covered by at least one option. We exemplify the feasibility of discretizing sharing levels and discuss the tradeoff between coverage and simplicity in discrete configuration options.

Keyword:

Design

Privacy

Human Factors

Cloud Computing

Clustering

Configuration

Privacy

preference clustering

human-computer interaction

information disclosure

intelligent agents