Key Indicators for Data Sharing - In Relation with Digital Services
Rapid growth of data intensive digital services are creating potential risks of violating consumer centric data privacy. Protection of data privacy is becoming one of the key challenges for most of the big data business entities. Due to thank of big data,
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Daffodil International University, Dhaka, Bangladesh [email protected], [email protected] 2 Telenor Group, Snaroyveien, 30 N-1360, Fornebu, Norway [email protected] 3 Linnaeus University, V¨ axj¨ o, Sweden [email protected]
Abstract. Rapid growth of data intensive digital services are creating potential risks of violating consumer centric data privacy. Protection of data privacy is becoming one of the key challenges for most of the big data business entities. Due to thank of big data, recommendation and personalization are becoming very popular in digital space. However it is hard to find a well-defined boundary which illustrates privacy threat to consumers’ in relation with improving already opted-in communication services. In this paper, we initiated identifying key indicators for consumer configured privacy policy in relation with personalized services taking into consideration that “Privacy is a tool for balancing personalization”. We survey user attitudes towards privacy and personalization and discovered key indicators for configuring privacy policy by analyzing survey data about privacy concern and data sharing attitude of the consumers. We found that consumers did not want to stop using social media based communication services due to privacy risks. Moreover, consumers have attitude of sharing their data, provided that appropriate personalization features are in place.
Keywords: Data sharing
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· Big data driven digital services
Introduction
Due to dynamic growth of data intensive communication services such as Facebook, Google+, and Twitter, there are potential risks of violating consumercentric data privacy. In a way, protection of data privacy is becoming one of the key challenges for most of the big data business entities. For example in 2011, Facebook went through a privacy audit by the Irish data protection commissioner. Generally, it is hard to find a well-defined boundary or guidelines J. Rana—The work has been carried out as part of an academic research project and does not necessarily represent Telenor views and positions. c Springer International Publishing Switzerland 2016 Y. Tan and Y. Shi (Eds.): DMBD 2016, LNCS 9714, pp. 353–363, 2016. DOI: 10.1007/978-3-319-40973-3 35
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which illustrates privacy threat to consumers’ in relation with improving or personalizing already opted-in communication services. Because, consumers usually receive less transparent information during the time of changing or adding new features for the services they already opted-in, and as a consequence of this, consumers usually have vague idea regarding the privacy configuration of most of the opted-in Web based communication services. During the last few decades, telecom operators have been loyal in preserving and protecting personal data such as Communication Detail Records (CDR) from external privacy and security threads. Generally, the telecommunication industries have been providing good level of consumers’ privacy. However, in some exceptional cases, telecom operators n
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