Analysis of information leakage from encrypted Skype conversations

Voice over IP (VoIP) has experienced a tremendous growth over the last few years and is now widely used among the population and for business purposes. The security of such VoIP systems is often assumed, creating a false sense of privacy. This paper investigates in detail the leakage of information from Skype, a widely used and protected VoIP application. Experiments have shown that isolated phonemes can be classified and given sentences identified. By using the dynamic time warping (DTW) algorithm, frequently used in speech processing, an accuracy of 60% can be reached. The results can be further improved by choosing specific training data and reach an accuracy of 83% under specific conditions. The initial results being speaker dependent, an approach involving the Kalman filter is proposed to extract the kernel of all training signals.

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.

Risks to patient confidentiality when communicating health information to blind and partially sighted patients.

The research reports on a survey of 228 blind and partially sighted persons in 15 health authorities across Scotland. The survey reports data on patient experience of receiving health information in accessible reading formats. Data indicated that about 90% of blind and partially sighted persons did not receive communications from various NHS health departments in a format that they could read by themselves. The implications for patient privacy, confidentiality and wider impact on life and health care are highlighted. The implications for professional ethical medical practice and for public policy are also discussed. Recommendations for improved practice are made.

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.

The perceived impact of interprofessional information sharing on young people about their sexual health care

This article presents the results from an analysis of data from service providers and young adults who were formerly in state care about how information about the sexual health of young people in state care is managed. In particular, the analysis focuses on the perceived impact of information sharing between professionals on young people. Twenty-two service providers from a range of professions including social work, nursing and psychology, and 19 young people aged 18–22 years who were formerly in state care participated in the study. A qualitative approach was employed in which participants were interviewed in depth and data were analysed using modified analytical induction (Bogdan & Biklen, 2007). Findings suggest that within the care system in which service provider participants worked it was standard practice that sensitive information about a young person’s sexual health would be shared across team members, even where there appeared to be no child protection issues. However, the accounts of the young people indicated that they experienced the sharing of information in this way as an invasion of their privacy. An unintended outcome of a high level of information sharing within teams is that the privacy of the young person in care is compromised in a way that is not likely to arise in the case of young people who are not in care. This may deter young people from availing themselves of the sexual health services.