We propose a novel scheme for selective distribution of content, encoded as documents, that preserves the privacy of the users to whom the documents are delivered and is based on an efficient and novel group key management scheme.

Our document broadcasting approach is based on access control policies specifying which users can access which documents, or subdocuments. Based on such policies, a broadcast document is segmented into multiple subdocuments, each encrypted with a different key. In line with modern attribute-based access control, policies are specified against identity attributes of users. However our broadcasting approach is privacy-preserving in that users are granted access to a specific document, or subdocument, according to the policies without the need of providing in clear information about their identity attributes to the document publisher. Under our approach, not only does the document publisher not learn the values of the identity attributes of users, but it also does not learn which policy conditions are verified by which users, thus inferences about the values of identity attributes are prevented. Moreover, our key management scheme on which the proposed broadcasting approach is based is efficient in that it does not require to send the decryption keys to the users along with the encrypted document. Users are able to reconstruct the keys to decrypt the authorized portions of a document based on subscription information they have received from the document publisher. The scheme also efficiently handles new subscription of users and revocation of subscriptions.

Client honeypots are typically implemented using some form of virtualization to contain malware encountered by the client machine. However, current virtual environments can be detected in multiple ways by malware. The malware can be executed from within a browser or require escaping from the browser to detect the virtualization. In many cases, detection is accomplished by a simple test. Malware can then modify its behavior based on this information. Thus, an implementation of client honeypots which does not depend on virtualization is needed to fully study malware.

In recent years, the field of uncertainty management in databases has received considerable interest due to the presence of numerous applications that handle probabilistic data. In this dissertation, we identify and solve important issues for managing uncertain data natively at the database level. We propose the semantics of join operation in the presence of attribute uncertainty and present various pruning techniques to significantly improve the join performance. Two index structures for indexing categorical uncertain data are also presented. For optimization of probabilistic queries, we discuss novel selectivity estimation techniques. We also introduce a new model for handling arbitrary pdf (both discrete and continuous) attributes natively at the database level. This model is consistent with Possible Worlds Semantics and is closed under the fundamental relation operations of selection, projection and join. We also present and discuss the implementation of Orion � a relational database with native support for uncertain data. Orion is developed as an extension of the open source relational database, PostgreSQL. The experiments performed in Orion show the effectiveness and efficiency of our approach.

Preserving a strong connection between mathematics and information security, elliptic and hyperelliptic curve cryptography are playing an increasingly important role during the past decade.  We present some problems that relate low genus curves and cryptography.

We first discuss a new application of elliptic curve cryptography (ECC) to a real-world problem of access control in secure broadcasting of data.  The asymmetry, introduced by the elliptic curve discrete logarithm problem, is the key to achieving the required security feature that existing methods fail to obtain.

We then talk about the use of genus 2 curves in the ``real model’’ in cryptography, and present explicit divisor doubling formulas for such curves.  These formulas are particularly important for implementation purposes.

Finally, we present a new method for finding cryptographically strong parameters for the CM construction of genus 2 curves. This method uses the idea of polynomial parameterization, which allows suitable parameters to be generated in batches. We give a brief analysis of the algorithm. We also provide algorithms for generating parameters for genus 2 curves to be used in pairing-based cryptography. Our method is an adaptation of the Cocks-Pinch construction for pairing-friendly elliptic curves. Our methods start from a prescribed embedding degree $k$ and a primitive quartic CM field $K$, and output a prime subgroup order $r$ of the Jacobian over a prime field $mathbb_p$, with $rho = 2log(p)/log(r)approx 8$.

This research investigates the development and testing of the Human- Biometric Sensor Interaction Evaluation Method that used ergonomics, usability, and image quality criteria as explanatory variables of overall biometric system performance to evaluate swipe-based fingerprint recognition devices. The HBSI method was proposed because of questions regarding the thoroughness of traditional testing and performance evaluation metrics such as FTA, FTE, FAR, and FRR used in standardized evaluation methods; questioning if traditional metrics were acceptable enough to fully test and understand biometric systems, or determine if important data were not being collected.

The Design and Evaluation of the Human-Biometric Sensor Interaction Method had four objectives: (a) analyze the literature to determine what influences the interaction of humans and biometric devices, (b) develop a conceptual model based on previous research, (c) design two alternative swipe fingerprint sensors, and (d) to compare how people interact with the commercial and designed swipe fingerprint sensors, to examine if changing the form factor improves the usability of the device in terms of the proposed HBSI evaluation method.

Data was collected from 85 individuals over 3 visits that accounted for 33,394 interactions with the 4 sensors used. The HBSI Evaluation Method provided additional detail about how users interact with the devices collecting data on: image quality, number of detected minutiae, fingerprint image size, fingerprint image contrast, user satisfaction, task time, task completeness, user effort, number of assists; in addition to traditional biometric testing and reporting metrics of: acquisition failures (FTA), enrollment failures (FTE), and matching performance (FAR and FRR).

Results from the HBSI Evaluation Method revealed that traditional biometric evaluations that focus on system-reported metrics are not providing sufficient reporting details. For example, matching performance for right and left index finger reported a FRR under 1% for all sensors at the operational point 0.1% FAR: UPEK (0.24%), PUSH (0.98%), PULL (0.36%), and large area (0.34%). However, the FTA rate was 11.28% and accounted for 3,768 presentations. From this research, two metrics previously unaccounted for and contained in the traditional FTA rate: Failure to Present (FTP) and False Failure to Present (FFTP) were created to better understand human interaction with biometric sensors and attribute errors accordingly. The FTP rate accounted for 1,187 of the 3,768 (31.5%) of interactions traditionally labeled as FTAs. The FFTP was much smaller at 0.35%, but can provide researchers further insight to help explain abnormal behaviors in matching rates, ROC and DET curves. In addition, traditional metrics of image quality and number of detected minutiae did not reveal a statistical difference across the sensors, however HBSI metrics of fingerprint image size and contrast did reveal a statistical difference, indicating the design of the PUSH sensor provided images of less gray level variation, while the PULL sensor provided images of larger pixel consistency during some of the data collection visits. The level of learning or habituation was also documented in this research through three metrics: task completion, Maximum User Effort (MUE), and the number of assists provided. All three reported the PUSH with the lowest rates, but improved the most over the visits, which was a function of learning how to use a “push”-based swipe sensor, as opposed to the “pull” swipe type.

Overall the HBSI Evaluation Method provided the foundation for the future of biometric evaluations as it linked system feedback from erroneous interactions to the human-sensor interaction that caused the failure. This linkage will enable system developers and researchers the ability to re-examine the data to see if the errors are the result of the algorithm or human interaction that can be solved with revised training techniques, design modifications, or other adjustments in the future.

Users increasingly use their mobile devices for electronic transactions to store related information, such as digital receipts. However, such information can be target of several attacks. There are some security issues related to M-commerce: the loss or theft of mobile devices results in a exposure of transaction information; transaction receipts that are send over WI-FI or 3G networks can be easily intercepted; transaction receipts can also be captured via Bluetooth connections without the user’s consent; and mobile viruses, worms and Trojan horses can access the transaction information stored on mobile devices if this information is not protected by passwords or PIN numbers. Therefore, assuring privacy and security of transactions’ information, as well as of any sensitive information stored on mobile devices is crucial. In this paper, we propose a privacy-preserving approach to manage electronic transaction receipts on mobile devices. The approach is based on the notion of transaction receipts issued by service providers upon a successful transaction and combines Pedersen commitment and Zero Knowledge Proof of Knowledge (ZKPK) techniques and Oblivious Commitment-Based Envelope (OCBE) protocols. We have developed a version of such protocol for Near Field Communication (NFC) enabled cellular phones.

This project examines the nature of privacy in communicative, social, and technological contexts, and is based on the premise that the ubiquity of technology and networked environments has changed multiple aspects of communicative processes. These include the realms of social interaction, the medium by which humans communicate, the means by which information about people is collected and stored, and the visibility of individuals in social worlds. These changes call into question the conceptualizations and boundaries of what constitutes privacy in today’s world. Craig’s (1999) metatheoretical traditions of communication theory are used to reconceptualize privacy, yielding a framework with seven distinct lenses: privacy as identity; privacy as relational(ity); privacy as social; privacy as cultural; privacy as autonomy; privacy as mediated; and privacy as discursive. These multi-theoretical approaches provide a structure or logic for organizing new understandings for privacy theory in the 21st century. Following the development of this framework, two empirical studies were completed: (a) a discursive examination of the meaning of privacy for young millennial adults; and (b) a social network analysis of the social structure of privacy. The results provide some intriguing insights.

First, the analysis of the social structure of privacy provides preliminary evidence that privacy does not influence the size, density, or positioning of individuals within a network, although it does reveal unique signatures that suggest privacy may influence the clustering and compartmentalization of groups within networks. Second, a survey of privacy attitudes confirms young adults have strong concerns about privacy, and especially with identity theft, electronic fraud, and controlling access to their identities and information. Finally, an inductive thematic analysis of discourse provides confirmation that privacy is meaningful to young adults, and is defined and articulated in multiple and sometimes dialectic ways, between: (a) identity and relational; (b) states of autonomy (being in control) and mediation (being surveilled by others); and in (c) material and discursive ways. Cross-cutting these dialectics are themes of cultural and contextual elements of privacy.

The contributions of this project are both theoretical and methodological. This is one of the first empirical studies to examine the discursive meaning of privacy to young college-age adults within the context of sociotechnical realms and the first empirical study of privacy from a social networks standpoint. Theoretically, I provide new conceptual frameworks for theorizing about privacy in communication contexts, and expand understanding about how privacy is enacted in social contexts through the methodological use of social network analysis. These understandings contribute to both social theory and communication theory. Finally, new methodological approaches are introduced for the access and processing of large-scale network data from social network sites that may be of interest to scholars.