Data Minimisation in Communication Protocols: A Formal Analysis Framework and Application to Identity Management

With the growing amount of personal information exchanged over the Internet, privacy is becoming more and more a concern for users. One of the key principles in protecting privacy is data minimisation. This principle requires that only the minimum amount of information necessary to accomplish a certain goal is collected and processed. "Privacy-enhancing" communication protocols have been proposed to guarantee data minimisation in a wide range of applications. However, currently there is no satisfactory way to assess and compare the privacy they offer in a precise way: existing analyses are either too informal and high-level, or specific for one particular system. In this work, we propose a general formal framework to analyse and compare communication protocols with respect to privacy by data minimisation. Privacy requirements are formalised independent of a particular protocol in terms of the knowledge of (coalitions of) actors in a three-layer model of personal information. These requirements are then verified automatically for particular protocols by computing this knowledge from a description of their communication. We validate our framework in an identity management (IdM) case study. As IdM systems are used more and more to satisfy the increasing need for reliable on-line identification and authentication, privacy is becoming an increasingly critical issue. We use our framework to analyse and compare four identity management systems. Finally, we discuss the completeness and (re)usability of the proposed framework

A formal privacy analysis of identity management systems

With the growing amount of personal information exchanged over the Internet, privacy is becoming more and more a concern for users. In particular, personal information is increasingly being exchanged in Identity Management (IdM) systems to satisfy the increasing need for reliable on-line identification and authentication. One of the key principles in protecting privacy is data minimization. This principle states that only the minimum amount of information necessary to accomplish a certain goal should be collected. Several "privacy-enhancing" IdM systems have been proposed to guarantee data minimization. However, currently there is no satisfactory way to assess and compare the privacy they offer in a precise way: existing analyses are either too informal and high-level, or specific for one particular system. In this work, we propose a general formal method to analyse privacy in systems in which personal information is communicated and apply it to analyse existing IdM systems. We first elicit privacy requirements for IdM systems through a study of existing systems and taxonomies, and show how these requirements can be verified by expressing knowledge of personal information in a three-layer model. Then, we apply the formal method to study four IdM systems, representative of different research streams, analyse the results in a broad context, and suggest improvements. Finally, we discuss the completeness and (re)usability of the proposed method

SECURITY, PRIVACY AND APPLICATIONS IN VEHICULAR AD HOC NETWORKS

With wireless vehicular communications, Vehicular Ad Hoc Networks (VANETs) enable numerous applications to enhance traffic safety, traffic efficiency, and driving experience. However, VANETs also impose severe security and privacy challenges which need to be thoroughly investigated. In this dissertation, we enhance the security, privacy, and applications of VANETs, by 1) designing application-driven security and privacy solutions for VANETs, and 2) designing appealing VANET applications with proper security and privacy assurance. First, the security and privacy challenges of VANETs with most application significance are identified and thoroughly investigated. With both theoretical novelty and realistic considerations, these security and privacy schemes are especially appealing to VANETs. Specifically, multi-hop communications in VANETs suffer from packet dropping, packet tampering, and communication failures which have not been satisfyingly tackled in literature. Thus, a lightweight reliable and faithful data packet relaying framework (LEAPER) is proposed to ensure reliable and trustworthy multi-hop communications by enhancing the cooperation of neighboring nodes. Message verification, including both content and signature verification, generally is computation-extensive and incurs severe scalability issues to each node. The resource-aware message verification (RAMV) scheme is proposed to ensure resource-aware, secure, and application-friendly message verification in VANETs. On the other hand, to make VANETs acceptable to the privacy-sensitive users, the identity and location privacy of each node should be properly protected. To this end, a joint privacy and reputation assurance (JPRA) scheme is proposed to synergistically support privacy protection and reputation management by reconciling their inherent conflicting requirements. Besides, the privacy implications of short-time certificates are thoroughly investigated in a short-time certificates-based privacy protection (STCP2) scheme, to make privacy protection in VANETs feasible with short-time certificates. Secondly, three novel solutions, namely VANET-based ambient ad dissemination (VAAD), general-purpose automatic survey (GPAS), and VehicleView, are proposed to support the appealing value-added applications based on VANETs. These solutions all follow practical application models, and an incentive-centered architecture is proposed for each solution to balance the conflicting requirements of the involved entities. Besides, the critical security and privacy challenges of these applications are investigated and addressed with novel solutions. Thus, with proper security and privacy assurance, these solutions show great application significance and economic potentials to VANETs. Thus, by enhancing the security, privacy, and applications of VANETs, this dissertation fills the gap between the existing theoretic research and the realistic implementation of VANETs, facilitating the realistic deployment of VANETs

An identity- and trust-based computational model for privacy

The seemingly contradictory need and want of online users for information sharing and privacy has inspired this thesis work. The crux of the problem lies in the fact that a user has inadequate control over the flow (with whom information to be shared), boundary (acceptable usage), and persistence (duration of use) of their personal information. This thesis has built a privacy-preserving information sharing model using context, identity, and trust to manage the flow, boundary, and persistence of disclosed information. In this vein, privacy is viewed as context-dependent selective disclosures of information. This thesis presents the design, implementation, and analysis of a five-layer Identity and Trust based Model for Privacy (ITMP). Context, trust, and identity are the main building blocks of this model. The application layer identifies the counterparts, the purpose of communication, and the information being sought. The context layer determines the context of a communication episode through identifying the role of a partner and assessing the relationship with the partner. The trust layer combines partner and purpose information with the respective context information to determine the trustworthiness of a purpose and a partner. Given that the purpose and the partner have a known level of trustworthiness, the identity layer constructs a contextual partial identity from the user's complete identity. The presentation layer facilitates in disclosing a set of information that is a subset of the respective partial identity. It also attaches expiration (time-to-live) and usage (purpose-to-live) tags into each piece of information before disclosure. In this model, roles and relationships are used to adequately capture the notion of context to address privacy. A role is a set of activities assigned to an actor or expected of an actor to perform. For example, an actor in a learner role is expected to be involved in various learning activities, such as attending lectures, participating in a course discussion, appearing in exams, etc. A relationship involves related entities performing activities involving one another. Interactions between actors can be heavily influenced by roles. For example, in a learning-teaching relationship, both the learner and the teacher are expected to perform their respective roles. The nuances of activities warranted by each role are dictated by individual relationships. For example, two learners seeking help from an instructor are going to present themselves differently. In this model, trust is realized in two forms: trust in partners and trust of purposes. The first form of trust assesses the trustworthiness of a partner in a given context. For example, a stranger may be considered untrustworthy to be given a home phone number. The second form of trust determines the relevance or justification of a purpose for seeking data in a given context. For example, seeking/providing a social insurance number for the purpose of a membership in a student organization is inappropriate. A known and tested trustee can understandably be re-trusted or re-evaluated based on the personal experience of a trustor. In online settings, however, a software manifestation of a trusted persistent public actor, namely a guarantor, is required to help find a trustee, because we interact with a myriad of actors in a large number of contexts, often with no prior relationships. The ITMP model is instantiated as a suite of Role- and Relationship-based Identity and Reputation Management (RRIRM) features in iHelp, an e-learning environment in use at the University of Saskatchewan. This thesis presents the results of a two-phase (pilot and larger-scale) user study that illustrates the effectiveness of the RRIRM features and thus the ITMP model in enhancing privacy through identity and trust management in the iHelp Discussion Forum. This research contributes to the understanding of privacy problems along with other competing interests in the online world, as well as to the development of privacy-enhanced communications through understanding context, negotiating identity, and using trust

Pseudo Identities Based on Fingerprint Characteristics

This paper presents the integrated project TURBINE which is funded under the EU 7th research framework programme. This research is a multi-disciplinary effort on privacy enhancing technology, combining innovative developments in cryptography and fingerprint recognition. The objective of this project is to provide a breakthrough in electronic authentication for various applications in the physical world and on the Internet. On the one hand it will provide secure identity verification thanks to fingerprint recognition. On the other hand it will reliably protect the biometric data through advanced cryptography technology. In concrete terms, it will provide the assurance that (i) the data used for the authentication, generated from the fingerprint, cannot be used to restore the original fingerprint sample, (ii) the individual will be able to create different "pseudo-identities" for different applications with the same fingerprint, whilst ensuring that these different identities (and hence the related personal data) cannot be linked to each other, and (iii) the individual is enabled to revoke an biometric identifier (pseudo-identity) for a given application in case it should not be used anymore

Economic location-based services, privacy and the relationship to identity

Mobile telephony and mobile internet are driving a new application paradigm: location-based services (LBS). Based on a person’s location and context, personalized applications can be deployed. Thus, internet-based systems will continuously collect and process the location in relationship to a personal context of an identified customer. One of the challenges in designing LBS infrastructures is the concurrent design for economic infrastructures and the preservation of privacy of the subjects whose location is tracked. This presentation will explain typical LBS scenarios, the resulting new privacy challenges and user requirements and raises economic questions about privacy-design. The topics will be connected to “mobile identity” to derive what particular identity management issues can be found in LBS