Design and Implementation of S-MARKS: A Secure Middleware for Pervasive Computing Applications

As portable devices have become a part of our everyday life, more people are unknowingly participating in a pervasive computing environment. People engage with not a single device for a specific purpose but many devices interacting with each other in the course of ordinary activity. With such prevalence of pervasive technology, the interaction between portable devices needs to be continuous and imperceptible to device users. Pervasive computing requires a small, scalable and robust network which relies heavily on the middleware to resolve communication and security issues. In this paper, we present the design and implementation of S-MARKS which incorporates device validation, resource discovery and a privacy module

An Approach for Ensuring Robust Support for Location Privacy and Identity Inference Protection

The challenge of preserving a user\u27s location privacy is more important now than ever before with the proliferation of handheld devices and the pervasive use of location based services. To protect location privacy, we must ensure k-anonymity so that the user remains indistinguishable among k-1 other users. There is no better way but to use a location anonymizer (LA) to achieve k-anonymity. However, its knowledge of each user\u27s current location makes it susceptible to be a single-point-of-failure. In this thesis, we propose a formal location privacy framework, termed SafeGrid that can work with or without an LA. In SafeGrid, LA is designed in such a way that it is no longer a single point of failure. In addition, it is resistant to known attacks and most significantly, the cloaking algorithm it employs meets reciprocity condition. Simulation results exhibit its better performance in query processing and cloaking region calculation compared with existing solutions. In this thesis, we also show that satisfying k-anonymity is not enough in preserving privacy. Especially in an environment where a group of colluded service providers collaborate with each other, a user\u27s privacy can be compromised through identity inference attacks. We present a detailed analysis of such attacks on privacy and propose a novel and powerful privacy definition called s-proximity. In addition to building a formal definition for s-proximity, we show that it is practical and it can be incorporated efficiently into existing systems to make them secure

Obfuscation and anonymization methods for locational privacy protection : a systematic literature review

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesThe mobile technology development combined with the business model of a majority of application companies is posing a potential risk to individuals’ privacy. Because the industry default practice is unrestricted data collection. Although, the data collection has virtuous usage in improve services and procedures; it also undermines user’s privacy. For that reason is crucial to learn what is the privacy protection mechanism state-of-art. Privacy protection can be pursued by passing new regulation and developing preserving mechanism. Understanding in what extent the current technology is capable to protect devices or systems is important to drive the advancements in the privacy preserving field, addressing the limits and challenges to deploy mechanism with a reasonable quality of Service-QoS level. This research aims to display and discuss the current privacy preserving schemes, its capabilities, limitations and challenges

A vision for global privacy bridges: Technical and legal measures for international data markets

From the early days of the information economy, personal data has been its most valuable asset. Despite data protection laws and an acknowledged right to privacy, trading personal information has become a business equated with "trading oil". Most of this business is done without the knowledge and active informed consent of the people. But as data breaches and abuses are made public through the media, consumers react. They become irritated about companies' data handling practices, lose trust, exercise political pressure and start to protect their privacy with the help of technical tools. As a result, companies' Internet business models that are based on personal data are unsettled. An open conflict is arising between business demands for data and a desire for privacy. As of 2015 no true answer is in sight of how to resolve this conflict. Technologists, economists and regulators are struggling to develop technical solutions and policies that meet businesses' demand for more data while still maintaining privacy. Yet, most of the proposed solutions fail to account for market complexity and provide no pathway to technological and legal implementation. They lack a bigger vision for data use and privacy. To break this vicious cycle, we propose and test such a vision of a personal information market with privacy. We accumulate technical and legal measures that have been proposed by technical and legal scholars over the past two decades. And out of this existing knowledge, we compose something new: a four-space market model for personal data

A privacy awareness system for ubiquitous computing environments

www.inf.ethz.ch/˜langhein Abstract. Protecting personal privacy is going to be a prime concern for the deployment of ubiquitous computing systems in the real world. With daunting Orwellian visions looming, it is easy to conclude that tamper-proof technical protection mechanisms such as strong anonymization and encryption are the only solutions to such privacy threats. However, we argue that such perfect protection for personal information will hardly be achievable, and propose instead to build systems that help others respect our personal privacy, enable us to be aware of our own privacy, and to rely on social and legal norms to protect us from the few wrongdoers. We introduce a privacy awareness system targeted at ubiquitous computing environments that allows data collectors to both announce and implement data usage policies, as well as providing data subjects with technical means to keep track of their personal information as it is stored, used, and possibly removed from the system. Even though such a system cannot guarantee our privacy, we believe that it can create a sense of accountability in a world of invisible services that we will be comfortable living in and interacting with.