Measuring Conditional Anonymity—A Global Study

The realm of digital health is experiencing a global surge, with mobile applications extending their reach into various facets of daily life. From tracking daily eating habits and vital functions to monitoring sleep patterns and even the menstrual cycle, these apps have become ubiquitous in their pursuit of comprehensive health insights. Many of these apps collect sensitive data and promise users to protect their privacy - often through pseudonymization. We analyze the real anonymity that users can expect by this approach and report on our findings. More concretely: We introduce the notion of conditional anonymity sets derived from statistical properties of the population; We measure anonymity sets for two real-world applications and present overarching findings from 39 countries; We develop a graphical tool for people to explore their own anonymity set. One of our case studies is a popular app for tracking the menstruation cycle. Our findings for this app show that, despite their promise to protect privacy, the collected data can be used to identify users up to groups of 5 people in 97% of all the US counties, allowing the de-anonymization of the individuals. Given that the US Supreme Court recently overturned abortion rights, the possibility of determining individuals is a calamity

Security of Verifiably Encrypted Signatures

In a verifiably encrypted signature scheme, signers encrypt their signature under the public key of a trusted third party and prove that they did so correctly. The security properties are unforgeability and opacity. Unforgeability states that a malicious signer should not be able to forge verifiably encrypted signatures and opacity prevents extraction from an encrypted signature. This paper proposes two novel fundamental requirements for verifiably encrypted signatures, called \emph{extractability} and \emph{abuse-freeness}, and analyze its effects on the security model of Boneh et al. Extractability ensures that the trusted third party is always able to extract a valid signature from a valid verifiably encrypted signature and abuse-freeness guarantees that a malicious signer, who cooperates with the trusted party, is not able to forge a verifiably encrypted signature. We further show that both properties are not covered by the model of Boneh et al., introduced at Eurocrypt 2003

Housekeeping gene validation for RT-qPCR studies on synovial fibroblasts derived from healthy and osteoarthritic patients with focus on mechanical loading

Selection of appropriate housekeeping genes is essential for the validity of data normalization in reverse transcription quantitative PCR (RT-qPCR). Synovial fibroblasts (SF) play a mediating role in the development and progression of osteoarthritis (OA) pathogenesis, but there is no information on reliable housekeeping genes available. Therefore the goal of this study was to identify a set of reliable housekeeping genes suitable for studies of mechanical loading on SF from healthy and OA patients. Nine genes were evaluated towards expression stability and ranked according their relative stability determined by four different mathematical procedures (geNorm, NormFinder, BestKeeper and comparative ΔCq). We observed that RPLP0 (ribosomal protein, large, P0) and EEF1A1 (eukaryotic translation elongation factor 1 alpha 1) turned out to be the genes with the most stable expression in SF from non-OA or OA patients treated with or without mechanical loading. According to geNorm two genes are sufficient for normalization throughout. Expression of one tested target gene varied considerably, if normalized to different candidate housekeeping genes. Our study provides a tool for accurate and valid housekeeping gene selection in gene expression experiments on SF from healthy and OA patients with and without mechanical loading in consistent with the MIQE (Minimum Information for Publication of Quantitative Real-Time PCR Experiments) guidelines and additionally demonstrates the impact of proper housekeeping gene selection on the expression of the gene of interest

On Tight Security Proofs for Schnorr Signatures

The Schnorr signature scheme is the most efficient signature scheme based on the discrete logarithm problem and a long line of research investigates the existence of a tight security reduction for this scheme in the random oracle model. Almost all recent works present lower tightness bounds and most recently Seurin (Eurocrypt 2012) showed that under certain assumptions the non-tight security proof for Schnorr signatures in the random oracle by Pointcheval and Stern (Eurocrypt 1996) is essentially optimal. All previous works in this direction rule out tight reductions from the (one-more) discrete logarithm problem. In this paper we introduce a new meta-reduction technique, which shows lower bounds for the large and very natural class of generic reductions. A generic reduction is independent of a particular representation of group elements. Most reductions in state-of-the-art security proofs have this property. It is desirable, because then the reduction applies generically to any concrete instantiation of the group. Our approach shows unconditionally that there is no tight generic reduction from any natural non-interactive computational problem $\Pi$ defined over algebraic groups to breaking Schnorr signatures, unless solving $\Pi$ is easy. In an additional application of the new meta-reduction technique, we also unconditionally rule out any (even non-tight) generic reduction from natural non-interactive computational problems defined over algebraic groups to breaking Schnorr signatures in the non-programmable random oracle model

Delegatable Functional Signatures

We introduce delegatable functional signatures (DFS) which support the delegation of signing capabilities to another party, called the evaluator, with respect to a functionality F. In a DFS, the signer of a message can choose an evaluator, specify how the evaluator can modify the signature without voiding its validity, allow additional input and decide how the evaluator can further delegate its capabilities. The main contribution of this paper is twofold. First, we propose DFS, a novel cryptographic primitive that unifies several seemingly different signature primitives, including functional signatures as defined by Boyle, Goldwasser, and Ivan (eprint 2013/401), sanitizable signatures, identity based signatures, and blind signatures. To achieve this unification, we present several definitions of unforgeability and privacy. Finding appropriate and meaningful definitions in this context is challenging due to the natural mealleability of DFS and due to the multi-party setting that may involve malicious keys. Second, we present a complete characterization of the instantiability of DFS under common assumptions, like the existence of one-way functions. Here, we present both positive and negative results. On the positive side we show that DFS not achieving our notion of privacy can be constructed from one-way functions. Furthermore, we show that unforgerable and private DFS can be constructed from doubly enhanced trapdoor permutations. On the negative side we show that the previous result is optimal regarding its underlying assumptions presenting an impossibility result for unforgeable private DFS from one-way permutations

Liar, Liar, Coins on Fire! — Penalizing Equivocation By Loss of Bitcoins

We show that equivocation, i.e., making conflicting statements to others in a distributed protocol, can be monetarily disincentivized by the use of crypto-currencies such as Bitcoin. To this end, we design completely decentralized non-equivocation contracts, which make it possible to penalize an equivocating party by the loss of its money. At the core of these contracts, there is a novel cryptographic primitive called accountable assertions, which reveals the party's Bitcoin credentials if it equivocates. Non-equivocation contracts are particularly useful for distributed systems that employ public append-only logs to protect data integrity, e.g., in cloud storage and social networks. Moreover, as double-spending in Bitcoin is a special case of equivocation, the contracts enable us to design a payment protocol that allows a payee to receive funds at several unsynchronized points of sale, while being able to penalize a double-spending payer after the fact

Measuring Conditional Anonymity - A Global Study

The realm of digital health is experiencing a global surge, with mobile applications extending their reach into various facets of daily life. From tracking daily eating habits and vital functions to monitoring sleep patterns and even the menstrual cycle, these apps have become ubiquitous in their pursuit of comprehensive health insights. Many of these apps collect sensitive data and promise users to protect their privacy - often through pseudonymization. We analyze the real anonymity that users can expect by this approach and report on our findings. More concretely: 1. We introduce the notion of conditional anonymity sets derived from statistical properties of the population. 2. We measure anonymity sets for two real-world applications and present overarching findings from 39 countries. 3. We develop a graphical tool for people to explore their own anonymity set. One of our case studies is a popular app for tracking the menstruation cycle. Our findings for this app show that, despite their promise to protect privacy, the collected data can be used to identify users up to groups of 5 people in 97% of all the US counties, allowing the de-anonymization of the individuals. Given that the US Supreme Court recently overturned abortion rights, the possibility of determining individuals is a calamity

GORAM -- Group ORAM for Privacy and Access Control in Outsourced Personal Records

Cloud storage has rapidly become a cornerstone of many IT infrastructures, constituting a seamless solution for the backup, synchronization, and sharing of large amounts of data. Putting user data in the direct control of cloud service providers, however, raises security and privacy concerns related to the integrity of outsourced data, the accidental or intentional leakage of sensitive information, the profiling of user activities and so on. Furthermore, even if the cloud provider is trusted, users having access to outsourced files might be malicious and misbehave. These concerns are particularly serious in sensitive applications like personal health records and credit score systems. To tackle this problem, we present GORAM, a cryptographic system that protects the secrecy and integrity of outsourced data with respect to both an untrusted server and malicious clients, guarantees the anonymity and unlinkability of accesses to such data, and allows the data owner to share outsourced data with other clients, selectively granting them read and write permissions. GORAM is the first system to achieve such a wide range of security and privacy properties for outsourced storage. In the process of designing an efficient construction, we developed two new, generally applicable cryptographic schemes, namely, batched zero-knowledge proofs of shuffle and an accountability technique based on chameleon signatures, which we consider of independent interest. We implemented GORAM in Amazon Elastic Compute Cloud (EC2) and ran a performance evaluation demonstrating the scalability and efficiency of our construction

Inner Product Functional Commitments with Constant-Size Public Parameters and Openings

Functional commitments (Libert et al.~[ICALP\u2716]) allow a party to commit to a vector $\vec v$ of length $n$ and later open the commitment at functions of the committed vector succinctly, namely with communication logarithmic or constant in $n$. Existing constructions of functional commitments rely on trusted setups and have either $O(1)$ openings and $O(n)$ parameters, or they have short parameters generatable using public randomness but have $O(\log n)$-size openings. In this work, we ask whether it is possible to construct functional commitments in which both parameters and openings can be of constant size. Our main result is the construction of FC schemes matching this complexity. Our constructions support the evaluation of inner products over small integers; they are built using groups of unknown order and rely on succinct protocols over these groups that are secure in the generic group and random oracle model

Practical Schnorr Threshold Signatures Without the Algebraic Group Model

Threshold signatures are digital signature schemes in which a set of $n$ signers specify a threshold $t$ such that any subset of size $t$ is authorized to produce signatures on behalf of the group. There has recently been a renewed interest in this primitive, largely driven by the need to secure highly valuable signing keys, e.g., DNSSEC keys or keys protecting digital wallets in the cryptocurrency ecosystem. Of special interest is FROST, a practical Schnorr threshold signature scheme, which is currently undergoing standardization in the IETF and whose security was recently analyzed at CRYPTO\u2722. We continue this line of research by focusing on FROST\u27s unforgeability combined with a practical distributed key generation (DKG) algorithm. Existing proofs of this setup either use non-standard heuristics, idealized group models like the AGM, or idealized key generation. Moreover, existing proofs do not consider all practical relevant optimizations that have been proposed. We close this gap between theory and practice by presenting the Schnorr threshold signature scheme Olaf, which combines the most efficient known FROST variant FROST3 with a variant of Pedersen\u27s DKG protocol (as commonly used for FROST), and prove its unforgeability. Our proof relies on the AOMDL assumption (a weaker and falsifiable variant of the OMDL assumption) and, like proofs of regular Schnorr signatures, on the random oracle model