Today, the increasing interconnection of mobile devices and people by Internet services raises more and more questions regarding privacy. Many services rely on private information in their functional, as well as commercial, designs. For example, a web search engine that is not able to evaluate location information is also not able to provide location-specific results making it essentially unusable for many applications. Furthermore, advertisement on the Internet is usually personalized and guided by information that should be regarded private in general. Therefore, a thorough and fair discussion of privacy should be performed by society.

In order to enable such a fair discussion, we are interested in bringing together results explaining privacy-friendly or even privacy-preserving algorithms for the age of big data and distributed systems. This includes results about privacy-preserving data mining in a central location and privacy-friendly data publication, as well as distributed protocols for privacy-preserving computation, including consensus algorithms and multiparty approaches.

In addition to these technical abilities, which have to be explored, we should also start discussing the value of privacy and the tradeoff between privacy and fidelity of computation. In general, a call for privacy levels, which are too high, will destroy the ability to provide specific types of services. On the contrary, calling for low privacy or no privacy at all makes it impossible to protect the informational self-determination.

A third topic of major interest is the fact that any privacy level can only be achieved by secure systems and architectures. If a given system is insecure, protecting privacy in communication networks and algorithms is of no point, because attackers can directly access the private information.

A final twist on the topic of mobile security and privacy is given by the limited computational capabilities of such systems. Applying very complicated approaches, such as private information retrieval, are limited by the fact that the involved computational overhead and communication are simply too much for common handheld devices.

Dr. Martin Werner
Guest Editor

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• Privacy in Mobile Systems
• Integrated Approaches to Security and Privacy
• Consensus Protocols and Distributed Multiparty Computation
• Differential Privacy
• Privacy Algorithms for handheld devices
• Privacy and Fidelity Tradeoff—From Algorithms to the User Interface