Max Hoffmann, Michael Klooß, Markus Raiber and Andy Rupp
Black-box accumulation (BBA) is a building block which enables a privacy-preserving implementation of point collection and redemption, a functionality required in a variety of user-centric applications including loyalty programs, incentive systems, and mobile payments. By definition, BBA+ schemes (Hartung et al. CCS ‘17) offer strong privacy and security guarantees, such as unlinkability of transactions and correctness of the balance flows of all (even malicious) users. Unfortunately, the instantiation of BBA+ presented at CCS ‘17 is, on modern smartphones, just fast enough for comfortable use. It is too slow for wearables, let alone smart-cards. Moreover, it lacks a crucial property: For the sake of efficiency, the user’s balance is presented in the clear when points are deducted. This may allow to track owners by just observing revealed balances, even though privacy is otherwise guaranteed. The authors intentionally forgo the use of costly range proofs, which would remedy this problem.
We present an instantiation of BBA+ with some extensions following a different technical approach which significantly improves efficiency. To this end, we get rid of pairing groups, rely on different zero-knowledge and fast range proofs, along with a slightly modified version of Baldimtsi-Lysyanskaya blind signatures (CCS ‘13). Our prototype implementation with range proofs (for 16 bit balances) outperforms BBA+ without range proofs by a factor of 2.5. Moreover, we give estimates showing that smart-card implementations are within reach.
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[DPP18] Demertzis, I., Papadopoulos, D., and Papamanthou, C. Searchable encryption with optimal locality: Achieving sublogarithmic read efficiency. In: H. Shacham and A. Boldyreva (eds.), CRYPTO 2018, Part I, LNCS , vol. 10991, pp. 371–406. Springer, Heidelberg (Aug
Private information retrieval (PIR) is a way for clients to query a remote database without the database holder learning the clients’ query terms or the responses they generate. Compelling applications for PIR are abound in the cryptographic and privacy research literature, yet existing PIR techniques are notoriously inefficient. Consequently, no such PIRbased application to date has seen real-world at-scale deployment. This paper proposes new “batch coding” techniques to help address PIR’s efficiency problem. The new techniques exploit the connection between ramp secret sharing schemes and efficient information-theoretically secure PIR (IT-PIR) protocols. This connection was previously observed by Henry, Huang, and Goldberg (NDSS 2013), who used ramp schemes to construct efficient “batch queries” with which clients can fetch several database records for the same cost as fetching a single record using a standard, non-batch query. The new techniques in this paper generalize and extend those of Henry et al. to construct “batch codes” with which clients can fetch several records for only a fraction the cost of fetching a single record using a standard non-batch query over an unencoded database. The batch codes are highly tuneable, providing a means to trade off (i) lower server-side computation cost, (ii) lower server-side storage cost, and/or (iii) lower uni- or bi-directional communication cost, in exchange for a comparatively modest decrease in resilience to Byzantine database servers.
Ágnes Kiss, Jian Liu, Thomas Schneider, N. Asokan and Benny Pinkas
Private set intersection (PSI) is a cryptographic technique that is applicable to many privacy-sensitive scenarios. For decades, researchers have been focusing on improving its efficiency in both communication and computation. However, most of the existing solutions are inefficient for an unequal number of inputs, which is common in conventional client-server settings. In this paper, we analyze and optimize the efficiency of existing PSI protocols to support precomputation so that they can efficiently deal with such input sets. We transform four existing PSI protocols into the precomputation form such that in the setup phase the communication is linear only in the size of the larger input set, while in the online phase the communication is linear in the size of the smaller input set. We implement all four protocols and run experiments between two PCs and between a PC and a smartphone and give a systematic comparison of their performance. Our experiments show that a protocol based on securely evaluating a garbled AES circuit achieves the fastest setup time by several orders of magnitudes, and the fastest online time in the PC setting where AES-NI acceleration is available. In the mobile setting, the fastest online time is achieved by a protocol based on the Diffie-Hellman assumption.
We study both the practical and theoretical efficiency of private information retrieval (PIR) protocols in a model wherein several untrusted servers work to obliviously service remote clients’ requests for data and yet no pair of servers colludes in a bid to violate said obliviousness. In exchange for such a strong security assumption, we obtain new PIR protocols exhibiting remarkable efficiency with respect to every cost metric—download, upload, computation, and round complexity—typically considered in the PIR literature.
The new constructions extend a multiserver PIR protocol of Shah, Rashmi, and Ramchandran (ISIT 2014), which exhibits a remarkable property of its own: to fetch a b-bit record from a collection of r such records, the client need only download b + 1 bits total. We find that allowing “a bit more” download (and optionally introducing computational assumptions) yields a family of protocols offering very attractive trade-offs. In addition to Shah et al.’s protocol, this family includes as special cases (2-server instances of) the seminal protocol of Chor, Goldreich, Kushilevitz, and Sudan (FOCS 1995) and the recent DPF-based protocol of Boyle, Gilboa, and Ishai (CCS 2016). An implicit “folklore” axiom that dogmatically permeates the research literature on multiserver PIR posits that the latter protocols are the “most efficient” protocols possible in the perfectly and computationally private settings, respectively. Yet our findings soundly refute this supposed axiom: These special cases are (by far) the least performant representatives of our family, with essentially all other parameter settings yielding instances that are significantly faster.
Confidential Content-Based Publish/Subscribe (C-CBPS) is an interaction model that allows parties to exchange content while protecting their security and privacy interests. In this paper we advance the state of the art in C-CBPS by showing how all predicate circuits in NC1 (logarithmic-depth, bounded fan-in) can be confidentially computed by a broker while guaranteeing perfect information-theoretic security. Previous work could handle only strictly shallower circuits (e.g. those with depth O(ℑ)). We present three protocols—UGP-Match, FSGP-Match and OFSGP-Match—based on 2-decomposable randomized encodings of group programs for circuits in NC1. UGP-Match is conceptually simple and has a clean proof of correctness but its running time is a polynomial with a high exponent and hence impractical. FSGP-Match uses a “fixed structure” construction that reduces the exponent drastically and achieves efficiency and scalability. OFSGP-Match optimizes the group programs further to shave off a linear factor.
We identify two vulnerabilities for existing highspeed network-layer anonymity protocols, such as LAP and Dovetail. First, the header formats of LAP and Dovetail leak path information, reducing the anonymity-set size when an adversary launches topological attacks. Second, ASes can launch session hijacking attacks to deanonymize destinations. HORNET addresses these problems but incurs additional bandwidth overhead and latency.
In this paper, we propose PHI, a Path-HIdden lightweight anonymity protocol that solves both challenges while maintaining the same level of efficiency as LAP and Dovetail. We present an efficient packet header format that hides path information and a new back-off setup method that is compatible with current and future network architectures. Our experiments demonstrate that PHI expands anonymity sets of LAP and Dovetail by over 30x and reaches 120 Gbps forwarding speed on a commodity software router.
We present an efficient method for answering one-dimensional range and closest-point queries in a verifiable and privacy-preserving manner. We consider a model where a data owner outsources a dataset of key-value pairs to a server, who answers range and closest-point queries issued by a client and provides proofs of the answers. The client verifies the correctness of the answers while learning nothing about the dataset besides the answers to the current and previous queries. Our work yields for the first time a zero-knowledge privacy assurance to authenticated range and closest-point queries. Previous work leaked the size of the dataset and used an inefficient proof protocol. Our construction is based on hierarchical identity-based encryption. We prove its security and analyze its efficiency both theoretically and with experiments on synthetic and real data (Enron email and Boston taxi datasets).
Sazzadur Rahaman, Long Cheng, Danfeng Daphne Yao, He Li and Jung-Min Jerry Park
Group signature schemes enable anonymous-yet-accountable communications. Such a capability is extremely useful for applications, such as smartphone-based crowdsensing and citizen science. However, the performance of modern group signature schemes is still inadequate to manage large dynamic groups. In this paper, we design the first provably secure verifier-local revocation (VLR) - based group signature scheme that supports sublinear revocation, named Sublinear Revocation with Backward unlinkability and Exculpability (SRBE). To achieve this performance gain, SRBE introduces time bound pseudonyms for the signer. By introducing low-cost short-lived pseudonyms with sublinear revocation checking, SRBE drastically improves the efficiency of the group-signature primitive. The backward-unlinkable anonymity of SRBE guarantees that even after the revocation of a signer, her previously generated signatures remain unlinkable across epochs. This behavior favors the dynamic nature of real-world crowdsensing settings. We prove its security and discuss parameters that influence its scalability. Using SRBE, we also implement a prototype named GroupSense for anonymous-yet-accountable crowdsensing, where our experimental findings confirm GroupSense’s scalability. We point out the open problems remaining in this space.