Integrity and Metadata Protection in Data Retrieval

Secure retrieval of data requires integrity, confidentially, transparency, and metadata-privacy of the process. Existing protection mechanisms, however, provide only partially these properties: encryption schemes still expose cleartext metadata, protocols for private information retrieval neglect data integrity, and data-distribution architectures forego transparency. In this dissertation, by designing new cryptographic primitives and security architectures that provide a more comprehensive protection, we improve on the current security and privacy practices in data retrieval. First, we propose a new format for encrypted data; it protects both content and all encryption metadata, such as the application, the intended recipients, and the algorithms used. The format comes with a cryptographically-agile encoding scheme that facilitates efficient decryption of such ciphertexts without cleartext markers. Second, to address the lack of integrity in privacy-preserving data-retrieval protocols, we introduce the concept of single-server verifiable private information retrieval. In contrast to existing solutions where, in some deployment scenarios, a malicious server can violate client privacy by selectively tampering with the data, our approach ensures that an honest client either correctly obtains the data from the systemâs server or detects server misbehavior and aborts. Finally, we present a software-update framework that reinforces software-distribution processes. Building on the concepts of decentralization and verifiability, our framework eliminates single points of failure, enforces transparency, and ensures integrity and authenticity of software releases. By implementing and experimentally evaluating our primitives and framework, we demonstrate that better protection is practical and incurs only a modest additional cost.

Quantifying and Protecting Location Privacy

Reza Shokri

Recent developments in information and communication technologies have been profound and life-changing. Most people are now equipped with smart phones with high computation power and communication capabilities. These devices can efficiently run multiple software applications in parallel, store a non-negligible amount of (personal) user data, process various sophisticated sensors and actuators, and communicate over multiple wireless media. Furthermore, they are commonly equipped with high-precision localization capabilities based, for example, on a GPS receiver or on triangulation with nearby base stations or access points. Mobile applications take advantage of this feature to provide location-based services to users. The ever-increasing usage of these personal communication devices and mobile applications, although providing convenience to their owners, comes at a very high cost to their privacy. Interacting with location-based services (LBSs) leaves an almost indelible digital trace of users’ whereabouts. Moreover, the contextual information attached to these traces can reveal users’ personal habits, interests, activities, and relationships. Consequently, exposure of this private information to third parties (such as service providers) escalates their power on individuals, and opens the door to various misuses of users’ personal data. Individuals have the right, and should also have the means to control the amount of their private (location) information that is disclosed to others. In the context of location-based services, various privacy enhancing mechanisms, such as location obfuscation and user anonymization, are proposed in the literature. However, the existing design methodologies for location-privacy preserving mechanisms do not consistently model users’ (privacy and service quality) requirements together with the adversary’s knowledge and objectives. Protection mechanisms are instead designed in an ad hoc manner and irrespective of the adversary model. Consequently, there is a mismatch between the goals and results of these protection mechanisms. Furthermore, the evaluation of privacy preserving mechanisms and their comparison remain problematic because of the absence of a systematic method to quantify them. In particular, the assumptions about the adversary model tend to be incomplete, with the risk of a possibly wrong estimation of the users’ location privacy. Arguably, the lack of a generic analytical framework for specifying protection mechanisms and for evaluating location privacy is evident. The absence of such a framework makes the design of effective protection mechanisms and the objective comparisons between them impossible. In this thesis, we address these issues and provide solutions for a systematic quantification and protection of location privacy. To this end, we construct an analytic framework for location privacy. We formalize users’ mobility model, their access pattern to location-based services, and their privacy and service quality requirements. We also model location-privacy preserving mechanisms as probabilistic functions that obfuscate users’ (location and identity) information before being shared with location-based services. Moreover, in order to quantify users’ location privacy, we propose inference mechanisms that measure users’ information leakage to third parties. They combine various pieces of information about users and estimate (by establishing a probabilistic belief on) users’ private information (e.g., their location at a given time). Therefore, we propose the adversary’s expected estimation error as, arguably, the right metric for location privacy. In our inference framework, we formalize the adversary’s prior knowledge on users, his observation (on the users’ accesses to LBS), and his inference objectives (e.g., re-identifying or localizing users). We assume that adversary constructs a (mobility) profile for each user, to be used in his inference attacks. We make use of statistical tools to construct these profiles, given users’ partial traces. Moreover, we model the inference attacks as the estimation of users’ actual locations, given their profiles and their LBS accesses (observed by the adversary). We mainly use Bayesian inference to perform the estimation. In particular, we use known inference algorithms for hidden Markov models to design de-anonymization, localization, and tracking attacks. To cover more adversary’s objectives, we propose an algorithm for generic location inference attacks, based on Markov-chain Monte-Carlo methods. We also provide a software tool: the Location-Privacy and Mobility Meter (LPM). It is designed based on our formal framework for evaluating the effectiveness of various location-privacy preserving mechanisms and quantifying users’ location privacy. As an example, using LPM, we validate the efficacy of existing location obfuscation and anonymization mechanisms on real location traces. We show that users’ location privacy measured by existing popular metrics, k-anonymity and entropy, is not correlated with the adversary’s success (in learning users’ private information), thus these metrics are inappropriate as privacy metrics. Our results also confirm that anonymization alone is a weak location-privacy preserving mechanism. Moreover, our results show how the resilience of a protection mechanism varies with respect to different inference attacks. Hence, it is a necessity for privacy protection mechanisms to be designed with concrete attack objectives in mind. Relying on these findings, we design optimal location obfuscation techniques tailored against localization attacks. A user needs a protection mechanism that maximizes her location privacy. This is at odds with the objectives of the adversary who designs inference attacks that minimize his estimation error. We propose a game-theoretic methodology that models the conflicting objectives of user and adversary simultaneously. More precisely, we model the problem as a Bayesian Stackelberg game and solve it by using linear programming. In the optimization problem, users constrain the protection mechanism to respect their service quality requirements. This enables us to find the optimal point in the tradeoff curve between privacy and service quality that satisfies both user privacy and service quality requirements. Our results indicate that anticipating for the inference attacks and considering the adversary’s knowledge lead to the design of more effective protection mechanisms. This thesis is a step towards a more systematic modeling, analysis, and design of (location) privacy enhancing technologies. We believe that our analytical approach can be used to quantify and protect privacy in scenarios and domains that are not covered in this thesis.

EPFL2013

Bounded Tamper Resilience: How to go beyond the Algebraic Barrier

Sebastian Faust

Related key attacks (RKAs) are powerful cryptanalytic attacks where an adversary can change the secret key and observe the effect of such changes at the output. The state of the art in RKA security protects against an a-priori unbounded number of certain algebraic induced key relations, e.g., affine functions or polynomials of bounded degree. In this work, we show that it is possible to go beyond the algebraic barrier and achieve security against arbitrary key relations, by restricting the number of tampering queries the adversary is allowed to ask for. The latter restriction is necessary in case of arbitrary key relations, as otherwise a generic attack of Gennaro et al. (TCC 2004) shows how to recover the key of almost any cryptographic primitive. We describe our contributions in more detail below. 1. We show that standard ID and signature schemes constructed from a large class of -protocols (including the Okamoto scheme, for instance) are secure even if the adversary can arbitrarily tamper with the prover's state a bounded number of times and obtain some bounded amount of leakage. Interestingly, for the Okamoto scheme we can allow also independent tampering with the public parameters. 2. We show a bounded tamper and leakage resilient CCA secure public key cryptosystem based on the DDH assumption. We first define a weaker CPA-like security notion that we can instantiate based on DDH, and then we give a general compiler that yields CCA-security with tamper and leakage resilience. This requires a public tamperproof common reference string. 3. Finally, we explain how to boost bounded tampering and leakage resilience (as in 1. and 2. above) to continuous tampering and leakage resilience, in the so-called floppy model where each user has a personal hardware token (containing leak- and tamper-free information) which can be used to refresh the secret key. We believe that bounded tampering is a meaningful and interesting alternative to avoid known impossibility results and can provide important insights into the security of existing standard cryptographic schemes.

2013

Provably Secure Authenticated Encryption

Damian Vizár

Authenticated Encryption (AE) is a symmetric key cryptographic primitive that ensures confidentiality and authenticity of processed messages at the same time. The research of AE as a primitive in its own right started in 2000. The security goals of AE were captured in formal definitions in the tradition in the tradition of provable security (such as NAE, MRAE, OAE, RAE or the RUP), where the security of a scheme is formally proven assuming the security of an underlying building block. The prevailing syntax moved to nonce-based AE with associated data (which is an additional input that gets authenticated, but not encrypted). Other types of AE schemes appeared as well, e.g. ones that supported stateful sessions. Numerous AE schemes were designed; in the early years, these were almost exclusively blockcipher modes of operation, most notably OCB in 2001, CCM in 2003 and GCM in 2004. At the same time, issues were discovered both with the security and applicability of the most popular AE schemes, and other applications of symmetric key cryptography. As a response, the Competition for Authenticated Encryption: Security, Applicability, and Robustness (CAESAR) was started in 2013. Its goals were to identify a portfolio of new, secure and reliable AE schemes that would satisfy the needs of practical applications, and also to boost the research in the area of AE. Prompted by CAESAR, 57 new schemes were designed, new types of constructions that gained popularity appeared (such as the Sponge-based AE schemes), and new notions of security were proposed (such as RAE). The final portfolio of the CAESAR competition should be announced in 2018. In this thesis, we push the state of the art in the field of AE in several directions. All of them are related to provable security, in one way, or another. We propose OMD, the first provably secure dedicated AE scheme that is based on a compression function. We further modify OMD to achieve nonce misuse-resistant security (MRAE). We also propose another provably secure variant of OMD called pure OMD, which enjoys a great improvement of performance over OMD. Inspired by the modifications that gave rise to pure OMD, we turn to the popular Sponge-based AE schemes and prove that similar measures can also be applied to the keyed Sponge and keyed Duplex (a variant of the Sponge), allowing a substantial increase of performance without an impact on security. We then address definitional aspects of AE. We critically evaluate the security notion of OAE, whose authors claimed that it provides the best possible security for online schemes under nonce reuse. We challenge these claims, and discuss what are the meaningful requirements for online AE schemes. Based on our findings, we formulate a new definition of online AE security under nonce-reuse, and demonstrate its feasibility. We next turn our attention to the security of nonce-based AE schemes under stretch misuse; i.e. when a scheme is used with varying ciphertext expansion under the same key, even though it should not be. We argue that varying the stretch is plausible, and formulate several notions that capture security in presence of variable stretch. We establish their relations to previous notions, and demonstrate the feasibility of security in this setting. We finally depart from provable security, with the intention to complement it. We compose a survey of universal forgeries, decryption attacks and key recovery attacks on 3rd round CAESAR candidates.

EPFL2018