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The increasing adoption of health information technologies in the United States accelerates their potential to facilitate beneficial studies that combine large, complex data sets from multiple sources. The process of de-identification, by which identifiers are removed from the health information, mitigates privacy risks to individuals and thereby supports the secondary use of data for comparative...
In the past two decades, targeted online advertising has led to massive data collection, aggregation, and exchange. This infrastructure raises significant privacy concerns. While several prominent theories of data privacy have been proposed over the same period of time, these notions have limited application to advertising ecosystems. Differential privacy, the most robust of them, is inherently inapplicable...
We show that it is possible to achieve information theoretic location privacy for secondary users (SUs) in database-driven cognitive radio networks (CRNs) with an end-to-end delay less than a second, which is significantly better than that of the existing alternatives offering only a computational privacy. This is achieved based on a keen observation that, by the requirement of Federal Communications...
Location-based queries have brought challenging privacy issues for mobile users. Having access to data, anytime from anywhere, raises many security concerns. One of these concerns is user's location privacy, where a user must reveal her location to get the desired result. The question is how to benefit from such queries without endangering user's location privacy. This paper presents a new method...
The database-driven CRN has emerged as a promising solution for the spectrum scarcity issue. However, it also raises severe privacy concerns. Although there are some existing works on this topic, they are far from practical due to their restrict on particular database structures or extremely heavy computation and communication overhead. To address these issues, in this paper we develop two practical...
We propose a privacy preserving mobile advertising system for in-app ad placement, that enables user profiling and targeted ads without revealing user interests to the mobile advertising companies. Our proposal relies on device-based user profiles, derived from app activity, on the use of Private Information Retrieval (PIR) to query ads database(s) for matching (to profile) ads, without the database(s)...
Biometric R&D has to deal with personal data. From the Universal Declaration of Human Rights, privacy of a human being shall be protected, and this is addressed in different forms in each region of the world. In the case of the European Union, Data Protection Directives, Laws and Regulation have been established, and interpreted in different ways by each European Member State. Such a diversity...
The iKaaS platform has been developed as a Horizon 2020 project to construct a multi-cloud environment in order to share data and knowledge. In this paper, we add a framework for knowledge sharing/reuse in the iKaaS platform. Furthermore, we design a revenue-sharing mechanism for knowledge sharing, which uses a blockchain for registration and use of data processing services.
Our aim is to use randomly generated image transformation in order to obtain image features of low dimensionality. The transformation consists of local projections of spatiallyorganized parts of an image, for example rectangular image blocks. After this transformation the content of an image is hidden and will not be stably recoverable, so it can be used in systems where privacy-preserving property...
In the last decades, the explosion of the volume of digital document images, and the development of consumer tools to modify these images, has lead to a huge increase on reported fraudulent document cases. This situation has promoted the development of automatic methods for both preventing forgeries in modified documents and detecting them. However, document forensics is a sensitive topic. Data is...
This paper argues that the privacy concerns that are associated with national identification systems is because of the failure of various countries to implement national identification systems with a strong privacy theory backing the implementation. This work is therefore aimed at addressing the privacy concerns of those countries debating national identification system adoption. Furthermore, the...
Radio frequency identification (RFID) is one of the key technologies of Internet of Things, which have many security issues in an open environment. In order to solve the communication problem between RFID tags and readers, security protocols has been improved constantly as the first choice. But the form of attack is also changing constantly with the development of technology. In this paper we classify...
Cyber-physical systems are subject to natural uncertainties and sensor noise that can be amplified/attenuated due to feedback. In this work, we want to leverage these properties in order to define the inherent differential privacy of feedback-control systems without the addition of an external differential privacy noise. If larger levels of privacy are required, we introduce a methodology to add an...
With the phenomenal increase in Android apps usage and storing of personal information on mobile devices, securing this sensitive information has assumed significance. The Android application developers knowingly or unknowingly create apps that may directly or indirectly leak this information to outside world. The majority of state-of-the-art approachesdetect leaks through inter-component communication...
We propose a natural relaxation of differential privacy based on the Rényi divergence. Closely related notions have appeared in several recent papers that analyzed composition of differentially private mechanisms. We argue that the useful analytical tool can be used as a privacy definition, compactly and accurately representing guarantees on the tails of the privacy loss.We demonstrate that the new...
In this paper, we address privacy issues related to ranked retrieval model in web databases, each of which takes private attributes as part of input in the ranking function. Many web databases have both public attributes and private attributes which serve different purposes. The owners of web databases, which normally are websites, show the public attributes but keep private attributes invisible to...
A major concern of the large-scale deployment of location based services (LBSs) is the safeguards of the user's location data collected by service providers, since person's location information may imply sensitive private information. Most existing techniques have addressed privacy protection mainly for snapshot queries. However, providing anonymity for continuous queries is important, since users'...
Demand response (DR) programs have emerged as a potential key enabling ingredient in the context of smart grid (SG). Nevertheless, the rising concerns over privacy issues raised by customers subscribed to these programs constitute a formidable hurdle towards their effective deployment and utilization. This has driven extensive research to resolve the hindrance confronted, resulting in a number of...
The abundance of various embedded sensors on mobile devices results in huge amount of data generation, storage requirement and also causes the encroachment into the personal privacy. But for the development of new applications or making organizational decisions, the trajectory data is to be published. Moving objects trajectory publication may result in the serious violation and a threat to the individual's...
Mobile phones provide an excellent opportunity for building context-aware applications. In particular, location-based services are important context-aware services that are more and more used for enforcing security policies, for supporting indoor room navigation, and for providing personalized assistance. However, a major problem still remains unaddressed--the lack of solutions that work across buildings...
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