Practical homomorphic encryption: A survey

Cloud computing technology has rapidly evolved over the last decade, offering an alternative way to store and work with large amounts of data. However data security remains an important issue particularly when using a public cloud service provider. The recent area of homomorphic cryptography allows computation on encrypted data, which would allow users to ensure data privacy on the cloud and increase the potential market for cloud computing. A significant amount of research on homomorphic cryptography appeared in the literature over the last few years; yet the performance of existing implementations of encryption schemes remains unsuitable for real time applications. One way this limitation is being addressed is through the use of graphics processing units (GPUs) and field programmable gate arrays (FPGAs) for implementations of homomorphic encryption schemes. This review presents the current state of the art in this promising new area of research and highlights the interesting remaining open problems.

The Library of Essays on Law and Privacy

Privacy has now become a major topic not only in law but in computing, psychology, economics and social studies, and the explosion in scholarship has made it difficult for the student to traverse the field and identify the significant issues across the many disciplines. This series brings together a collection of significant papers with a multi-disciplinary approach which enable the reader to navigate through the complexities of the issues and make sense of the prolific scholarship published in this field.

The three volumes in this series address different themes: an anthropological approach to what privacy means in a cultural context; the issue of state surveillance where the state must both protect the individual and protect others from that individual and also protect itself; and, finally, what privacy might mean in a world where government and commerce collect data incessantly. The regulation of privacy is continually being called for and these papers help enable understanding of the ethical rationales behind the choices made in the sphere of regulation of privacy.

The articles presented in each of these collections have been chosen for the quality of their scholarship and their utility to the researcher, and feature a variety of approaches. The articles which debate the technical context of privacy are accessible to those from the arts and humanities; overall, the breadth of approach taken in the choice of articles has created a series which is an invaluable and important resource for lecturers, researchers and student.

Self-disclosure decision making based on intimacy and privacy

Autonomous agents may encapsulate their principals' personal data attributes. These attributes may be disclosed to other agents during agent interactions, producing a loss of privacy. Thus, agents need self-disclosure decision-making mechanisms to autonomously decide whether disclosing personal data attributes to other agents is acceptable or not. Current self-disclosure decision-making mechanisms consider the direct benefit and the privacy loss of disclosing an attribute. However, there are many situations in which the direct benefit of disclosing an attribute is a priori unknown. This is the case in human relationships, where the disclosure of personal data attributes plays a crucial role in their development. In this paper, we present self-disclosure decision-making mechanisms based on psychological findings regarding how humans disclose personal information in the building of their relationships. We experimentally demonstrate that, in most situations, agents following these decision-making mechanisms lose less privacy than agents that do not use them. (C) 2012 Elsevier Inc. All rights reserved.

The Impact of EU Privacy Legislation on Biometric System Deployment: Protecting citizens but constraining applications

Biometric systems provide a valuable service in helping to identify individuals from their stored personal details. Unfortunately, with the rapidly increasing use of such systems, there is a growing concern about the possible misuse of that information. To counteract the threat, the European Union (EU) has introduced comprehensive legislation that seeks to regulate data collection and help strengthen an individual’s right to privacy. This article looks at the implications of the legislation for biometric system deployment. After an initial consideration of current privacy concerns, it examines what is meant by ‘personal data’ and its protection, in legislation terms. Also covered are issues around the storage of biometric data, including its accuracy, its security, and justification for what is collected. Finally, the privacy issues are illustrated through three biometric use cases: border security, online bank access control and customer profiling in stores.

On the Privacy of Encrypted Skype Communications

The privacy of voice over IP (VoIP) systems is achieved by compressing and encrypting the sampled data. This paper investigates in detail the leakage of information from Skype, a widely used VoIP application. In this research, it has been demonstrated by using the dynamic time warping (DTW) algorithm, that sentences can be identified with an accuracy of 60%. The results can be further improved by choosing specific training data. An approach involving the Kalman filter is proposed to extract the kernel of all training signals.