Data privacy approaches from US and EU perspectives

Steinke, Gerhard

doi:10.1016/s0736-5853(01)00013-2

Cited by 35 publications

(19 citation statements)

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“…To bridge this gap and allow US companies to do business in the EU and conform to the EU Privacy Directive, EU and US arrived at an agreement, known as the Safe Harbor Agreement. This agreement offers a convenient way of complying with the adequacy requirements of the EU Directive [57].…”

Section: Privacy As a Commoditymentioning

confidence: 99%

Privacy challenges in Ambient Intelligence systems

Caire

Moawad

Efthymiou

et al. 2016

AIS

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Abstract. Today, privacy is a key concept. It is also one which is rapidly evolving with technological advances, and there is no consensus on a single definition for it. In fact, the concept of privacy has been defined in many different ways, ranging from the "right to be left alone" to being a "commodity" that can be bought and sold. In the same time, powerful Ambient Intelligence (AmI) systems are being developed, that deploy context-aware, personalised, adaptive and anticipatory services. In such systems personal data is vastly collected, stored, and distributed, making privacy preservation a critical issue. The humancentred focus of AmI systems has prompted the introduction of new kinds of technologies, e.g. Privacy Enhancing Technologies (PET), and methodologies, e.g. Privacy by Design (PbD), whereby privacy concerns are included in the design of the system. One particular application field, where privacy preservation is of critical importance is Ambient Assisted Living (AAL). Emerging from the continuous increase of the ageing population, AAL focuses on intelligent systems of assistance for a better, healthier and safer life in their living environment. In this paper, we first build on our previous work, in which we introduced a new tripartite categorisation of privacy as a right, an enabler, and a commodity. Second, we highlight the specific privacy issues raised in AAL. Third, we review and discuss current approaches for privacy preservation. Finally, drawing on lessons learned from AAL, we provide insights on the challenges and opportunities that lie ahead. Part of our methodology is a statistical analysis performed on the IEEE publications database. We illustrate our work with AAL scenarios elaborated in cooperation with the city of Luxembourg.

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Section: Privacy As a Commoditymentioning

confidence: 99%

Privacy challenges in Ambient Intelligence systems

Caire

Moawad

Efthymiou

et al. 2016

AIS

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“…It came into force on 1st March 2000. This totally replaced the previous Data Protection Act of 1984 [4].…”

Section: Government Regulation Approachmentioning

confidence: 99%

“…The political views of a country can affect its view on data protection [4]. The military of Nigeria has played a major role in the country's history, often seizing control of the country and ruling it for long periods of time.…”

Section: Political Historymentioning

confidence: 99%

“…Fear about privacy and the lack of trust continue to be the biggest obstacles to the growth of online commerce. The Internet industry is built on trust between businesses [4]. These developments have forced several nations of the world to enact legislation and procedures to protect the information privacy of their citizens and corporations.…”

Section: Introductionmentioning

confidence: 99%

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Privacy and Data Protection in E-commerce in Developing Nations: Evaluation of Different Data Protection Approaches

Adelola¹,

Dawson²,

Batmaz³

2014

IJDS

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“…On the reverse, the Europe Union (EU) Data Protection Directive (Steinke, 2002) contains two statements contradicting the U.S. one. The first statement requires that an organization must inform individuals why it collects and uses information, how to contact the organization, and the types of third parties to which it discloses the information.…”

Section: Introductionmentioning

confidence: 99%

Privacy Issues of Applying RFID in Retail Industry

Hung

Zhang

et al. 2006

International Journal of Cases on Electronic Commerce

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EXECUTIVE SUMMARY This case study describes the privacy issues of applying Radio Frequency Identification (RFID) in the retail industry. With the dramatic price drop of RFID tags, it is possible that RFID be applied to individual items sold by a retailer. However, the RFID technology poses critical privacy challenges. In this study, we analyze the potential privacy issue of RFID utilization, and we propose a privacy authorization model aiming for precisely defining RFID privacy policies for the retail industry. Keywords: RFID, Privacy, RBAC, EPAL INTRODUCTIONIn present retail industry, retailers are under tremendous pressure to improve their efficiency. One way to increase productivity is through the adoption of new technologies. History has revealed that retailers are the early adopters of Electronic Data Interchange (EDI) and Business-to-Business (B2B) E-Commerce. The benefits of adopting these new technologies are obvious: reduced time to market and reduced cost associated with office and manufacturing floor automation. In recent years, Radio Frequency Identification (RFID) has caught significant attention in retail industry. RFID is a generic term for the technologies that use radio waves to automatically identify individual items wirelessly. RFID is capable of enabling retailers to effectively and efficiently track the entire circulation process of items from suppliers to end users. It allows to identify, orientate, and trace objects directly and continuously. In addition, RFID is able to deliver information at real time. As a result, RFID is widely considered as an emerging technology that could potentially revolutionize the way retailers do business. Among other examples, Wal-Mart has mandated its top 100 suppliers to use RFID by January 2005 (Vijayan, 2003); U.S. Department of Defense has also made the similar requests to its military suppliers (U.S. Department of Defense, 2003).Although it seems that RFID is a boom to e-Commerce, the actual adoption of RFID in retail industry is quite slow (Bradner, 2005). Retail industry poses typical enterprise computing challenges (Neogi, 2004) as a retailer normally deals with multiple parties belonging to different organizations: suppliers, manufacturers, distributors, and end consumers. Nowadays, the focus of enterprise computing efforts of retailers mainly aims for suppliers. To date there is little work conducted on how to provide enterprise-level computing capability for individual customers. In addition to the known security issue, one such capability we have identified is consumer's privacy protection. There is a growing concern for data privacy among businesses and consumers, because of the possible unwanted revelation of confidential or personal data stored within RFID devices.1 The third author is currently with BEA Systems, Inc., and also a Guest Scientist of National Institute of Standards and Technology (NIST).2 Privacy is a state or condition of limited access to a person (Schoeman, 1984). Particularly, information privacy refers to an individual's rig...

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Data privacy approaches from US and EU perspectives

Cited by 35 publications

References 0 publications

Privacy challenges in Ambient Intelligence systems

Privacy challenges in Ambient Intelligence systems

Privacy and Data Protection in E-commerce in Developing Nations: Evaluation of Different Data Protection Approaches

Privacy Issues of Applying RFID in Retail Industry

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