"When the immediate vicinity is neither visible nor audible, the city apartment integrated into the urban fabric can be far more luxurious than the detached country home, provided both alternatives offer identical, house-like qualities of living: in the interior and at the transition to the appropriate exterior space - a small yard, a winter garden or a roof patio... ...the decision to opt for home ownership beyond the city boundaries, a voluntary choice it would seem, is in truth a flight from the insufficient housing options in the city, and less a rejection of the city as a place to live." Klaus-Dieter Weiss / Master of Architecture

Wireless cameras dominate the home surveillance market, providing an additional layer of security for homeowners. Cameras are not limited to private residences; retail stores, public bathrooms, and public beaches represent only some of the possible locations where wireless cameras may be monitoring people's movements. When cameras are deployed into an environment, one would typically expect the user to disclose the presence of the camera as well as its location, which should be outside of a private area. However, adversarial camera users may withhold information and prevent others from discovering the camera, forcing others to determine if they are being recorded on their own. To uncover hidden cameras, a wireless camera detection system must be developed that will recognize the camera's network traffic characteristics. We monitor the network traffic within the immediate area using a separately developed packet sniffer, a program that observes and collects information about network packets. We analyze and classify these packets based on how well their patterns and features match those expected of a wireless camera. We used a Support Vector Machine classifier and a secondary-level of classification to reduce false positives to design and implement a system that uncovers the presence of hidden wireless cameras within an area. / Master of Science / Wireless cameras may be found almost anywhere, whether they are used to monitor city traffic and report on travel conditions or to act as home surveillance when residents are away. Regardless of their purpose, wireless cameras may observe people wherever they are, as long as a power source and Wi-Fi connection are available. While most wireless camera users install such devices for peace of mind, there are some who take advantage of cameras to record others without their permission, sometimes in compromising positions or places. Because of this, systems are needed that may detect hidden wireless cameras. We develop a system that monitors network traffic packets, specifically based on their packet lengths and direction, and determines if the properties of the packets mimic those of a wireless camera stream. A double-layered classification technique is used to uncover hidden wireless cameras and filter out non-wireless camera devices.

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The visual display terminal (VDT) is an integral part of the modern office. An issue of concern associated with the use of the VDT is maintaining privacy of on-screen materials. Privacy filters are products designed to restrict the viewing angle to documents displayed on a VDT, so that the on-screen material is not visible to persons other than the VDT operator. Privacy filters restrict the viewing angle either by diffraction or diffusion of the light emitted from the VDT. Constrained posture is a human factors engineering problem that has been associated with VDT use. The purpose of this research was to evaluate whether the use of privacy filters affected: 1) the restriction of postures associated with VDT use, 2) operator performance, and 3) subjective ratings of display issues, posture, and performance. Nine participants performed three types of tasks: word processing, data entry, and Web browsing. Each task was performed under three filter conditions: no filter, diffraction filter, and diffusion filter. Participants were videotaped during the tasks using a camera mounted above the VDT workstation. The videotape was analyzed and horizontal head deviation was measured at 50 randomly selected points during each task. Horizontal head deviation was measured as the angle between an absolute reference line, which bisects the center of the VDT screen, and a reference point located at the center of the participant's head. Standard deviation of head deviation were evaluated across filter type and task type. Accuracy- and/or time-based measures were used to evaluate performance within each task. Participants used a seven-point scale to rate the following: readability, image quality, brightness, glare, posture restriction, performance, and discomfort. The results indicated that the interaction between task and filter type affected the standard deviation of horizontal head deviation (a measure of the average range of horizontal deviation). The standard deviation of horizontal deviation was significantly larger within the Web browsing task under the no filter and diffusion filter conditions as compared to the diffraction filter condition. Filter type affected subjective ratings of the following: readability, image quality, brightness, posture restriction, and discomfort. The diffraction filter resulted in lower readability, image quality, and brightness ratings than the diffusion and no filter conditions. Participants reported that the ability to change postures was significantly decreased by the use of the diffraction filter as compared to the no filter and diffraction filter conditions. The diffraction filter resulted in an increase in reported discomfort as compared to the no filter condition. The interaction between filter and task type affected subjective ratings of performance. Participants reported a decrease in the rating of perceived performance under the diffraction filter / Web browsing condition as compared to the no filter / word processing, diffusion filter / Web browsing, and diffusion filter / data entry conditions. A decrease in the rating of perceived performance was reported in the diffraction filter / data entry condition as compared to the no filter / word processing and diffusion filter / Web browsing conditions. Neither diffraction nor diffusion filter affected performance within any of the tasks, based on the objective performance measures used in the experiment. / Master of Science

Perceptual, "context-aware" applications that observe their environment and interact with users via cameras and other sensors are becoming ubiquitous on personal computers, mobile phones, gaming platforms, household robots, and augmented-reality devices. This dissertation's main thesis is that perceptual applications present several new classes of security and privacy risks to both their users and the bystanders. Existing perceptual platforms are often completely inadequate for mitigating these risks. For example, we show that the augmented reality browsers, a class of popular perceptual platforms, contain numerous inherent security and privacy flaws. The key insight of this dissertation is that perceptual platforms can provide stronger security and privacy guarantees by controlling the interfaces they expose to the applications. We explore three different approaches that perceptual platforms can use to minimize the risks of perceptual computing: (i) redesigning the perceptual platform interfaces to provide a fine-grained permission system that allows least-privileged application development; (ii) leveraging existing perceptual interfaces to enforce access control on perceptual data, apply algorithmic privacy transforms to reduce the amount of sensitive content sent to the applications, and enable the users to audit/control the amount of perceptual data that reaches each application; and (iii) monitoring the applications' usage of perceptual interfaces to find anomalous high-risk cases. To demonstrate the efficacy of our approaches, first, we build a prototype perceptual platform that supports fine-grained privileges by redesigning the perceptual interfaces. We show that such a platform not only allows creation of least-privileged perceptual applications but also can improve performance by minimizing the overheads of executing multiple concurrent applications. Next, we build DARKLY, a security and privacy-aware perceptual platform that leverages existing perceptual interfaces to deploy several different security and privacy protection mechanisms: access control, algorithmic privacy transforms, and user audit. We find that DARKLY can run most existing perceptual applications with minimal changes while still providing strong security and privacy protection. Finally, We introduce peer group analysis, a new technique that detects anomalous high-risk perceptual interface usages by creating peer groups with software providing similar functionality and comparing each application's perceptual interface usages against those of its peers. We demonstrate that such peer groups can be created by leveraging information already available in software markets like textual descriptions and categories of applications, list of related applications, etc. Such automated detection of high-risk applications is essential for creating a safer perceptual ecosystem as it helps the users in identifying and installing safer applications with any desired functionality and encourages the application developers to follow the principle of least privilege. / text

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The ability to control one’s own personally identifiable information is a worthwhile human right that is becoming increasingly vulnerable. However just as significant, if not more so, is the right to health. With increasing globalisation and threats of natural disasters and acts of terrorism, this right is also becoming increasingly vulnerable. Public health practice – which is charged with the protection, promotion and mitigation of the health of society and its individuals – has been at odds with the right to privacy. This is particularly significant when location privacy is under consideration. Spatial information is an important aspect of public health, yet the increasing availability of spatial imagery and location-sensitive applications and technologies has brought location-privacy to the forefront, threatening to negatively impact the practice of public health by inhibiting or severely limiting data-sharing. This study begins by reviewing the current relevant legislation as it pertains to public health and investigates the public health community’s perceptions on location privacy barriers to the practice. Bureaucracy and legislation are identified by survey participants as the two greatest privacy-related barriers to public health. In response to this clash, a number of solutions and workarounds are proposed in the literature to compensate for location privacy. However, as their weaknesses are outlined, a novel approach - the multidimensional point transform - that works synergistically on multiple dimensions, including location, to anonymise data is developed and demonstrated. Finally, a framework for guiding decisions on data-sharing and identifying requirements is proposed and a sample implementation is demonstrated through a fictitious scenario. For each aspect of the study, a tool prototype and/or design for implementation is proposed and explained, and the need for further development of these is highlighted. In summary, this study provides a multi-disciplinary and multidimensional solution to the clash between privacy and data-sharing in public health practice.

Space exploration is a uniquely human activity. As humans continue to push the limits of exploring the unknown, they have sought knowledge supporting the sustenance of life in outer space. New technologies, advancements in medicine, and rethinking what it means to be a “community” will need to emerge to support life among the stars. Crews traveling beyond the Moon will rely on the development of new technologies to support the technological aspects of their missions as well as their quality of life while away from Earth. Likewise, through advancements in medicine, scientists will need to address remaining questions regarding the effects of long-duration spaceflight on the human body and crew performance. Space explorers must learn to utilize these new technologies and medical advancements while learning to adapt to their new environment in space and as a space community. It is important that researchers address these issues so that human survival beyond Earth is not only achievable but so that life among the stars is worth living and sustaining. This thesis addressed these issues in an attempt to extend the trajectory of space exploration to new horizons.

<p>Following the trend of online data sharing and publishing, researchers raise their concerns about the privacy problem. Online Social Networks (OSNs), for example, often contain sensitive information about individuals. Therefore, anonymizing network data before releasing it becomes an important issue. This dissertation studies the privacy preservation problem from the perspectives of both attackers and defenders. </p> <p><br></p> <p>To defenders, preserving the private information while keeping the utility of the published OSN is essential in data anonymization. At one extreme, the final data equals the original one, which contains all the useful information but has no privacy protection. At the other extreme, the final data is random, which has the best privacy protection but is useless to the third parties. Hence, the defenders aim to explore multiple potential methods to strike a desirable tradeoff between privacy and utility in the published data. This dissertation draws on the very fundamental problem, the definition of utility and privacy. It draws on the design of the privacy criterion, the graph abstraction model, the utility method, and the anonymization method to further address the balance between utility and privacy. </p> <p><br></p> <p>To attackers, extracting meaningful information from the collected data is essential in data de-anonymization. De-anonymization mechanisms utilize the similarities between attackers’ prior knowledge and published data to catch the targets. This dissertation focuses on the problems that the published data is periodic, anonymized, and does not cover the target persons. There are two thrusts in studying the de-anonymization attacks: the design of seed mapping method and the innovation of generating-based attack method. To conclude, this dissertation studies the online data privacy problem from both defenders’ and attackers’ point of view and introduces privacy and utility enhancement mechanisms in different novel angles.</p>