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1. Single-Server Private Information Retrieval with Sublinear Amortized Time

   https://doi.org/10.1007/978-3-031-07085-3_1  

   Corrigan-Gibbs, H. ( May 2022 , Lecture notes in computer science)

   Dunkelman, D. ; Dziembowski, S. (Ed.)

   We construct new private-information-retrieval protocols in the single-server setting. Our schemes allow a client to privately fetch a sequence of database records from a server, while the server answers each query in average time sublinear in the database size. Specifically, we introduce the first single-server private-information-retrieval schemes that have sublinear amortized server time, require sublinear additional storage, and allow the client to make her queries adaptively. Our protocols rely only on standard cryptographic assumptions (decision Diffie-Hellman, quadratic residuosity, learning with errors, etc.). They work by having the client first fetch a small “hint” about the database contents from the server. Generating this hint requires server time linear in the database size. Thereafter, the client can use the hint to make a bounded number of adaptive queries to the server, which the server answers in sublinear time—yielding sublinear amortized cost. Finally, we give lower bounds proving that our most efficient scheme is optimal with respect to the trade-off it achieves between server online time and client storage. 

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2. One Server for the Price of Two: Simple and Fast Single-Server Private Information Retrieval

   Henzinger, Alexandra ; Hong, Matthew M. ; Corrigan-Gibbs, Henry ; Meiklejohn, Sarah ; Vaikuntanathan, Vinod ( January 2023 , USENIX Security Symposium)

   We present SimplePIR, the fastest single-server private information retrieval scheme known to date. SimplePIR’s security holds under the learning-with-errors assumption. To answer a client’s query, the SimplePIR server performs fewer than one 32-bit multiplication and one 32-bit addition per database byte. SimplePIR achieves 10 GB/s/core server throughput, which approaches the memory bandwidth of the machine and the performance of the fastest two-server private-information-retrieval schemes (which require non-colluding servers). SimplePIR has relatively large communication costs: to make queries to a 1 GB database, the client must download a 121 MB "hint" about the database contents; thereafter, the client may make an unbounded number of queries, each requiring 242 KB of communication. We present a second single-server scheme, DoublePIR, that shrinks the hint to 16 MB at the cost of slightly higher per-query communication (345 KB) and slightly lower throughput (7.4 GB/s/core). Finally, we apply our new private-information-retrieval schemes, together with a novel data structure for approximate set membership, to the task of private auditing in Certificate Transparency. We achieve a strictly stronger notion of privacy than Google Chrome’s current approach with modest communication overheads: 16 MB of download per month, along with 150 bytes per TLS connection. 

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3. Amortizing Rate-1 OT and Applications to PIR and PSI

   https://doi.org/10.1007/978-3-030-90456-2_5  

   Chase, M. ; Garg, S. ; Hajiabadi, M. ; Li, J. ; Miao, P. ( November 2022 , 19th Theory of Cryptography Conference (TCC))

   Nissim, K. ; Waters, B. (Ed.)

   Recent new constructions of rate-1 OT [Döttling, Garg, Ishai, Malavolta, Mour, and Ostrovsky, CRYPTO 2019] have brought this primitive under the spotlight and the techniques have led to new feasibility results for private-information retrieval, and homomorphic encryption for branching programs. The receiver communication of this construction consists of a quadratic (in the sender's input size) number of group elements for a single instance of rate-1 OT. Recently [Garg, Hajiabadi, Ostrovsky, TCC 2020] improved the receiver communication to a linear number of group elements for a single string-OT. However, most applications of rate-1 OT require executing it multiple times, resulting in large communication costs for the receiver. In this work, we introduce a new technique for amortizing the cost of multiple rate-1 OTs. Specifically, based on standard pairing assumptions, we obtain a two-message rate-1 OT protocol for which the amortized cost per string-OT is asymptotically reduced to only four group elements. Our results lead to significant communication improvements in PSI and PIR, special cases of SFE for branching programs. - PIR: We obtain a rate-1 PIR scheme with client communication cost of $O(\lambda\cdot\log N)$ group elements for security parameter $\lambda$ and database size $N$. Notably, after a one-time setup (or one PIR instance), any following PIR instance only requires communication cost $O(\log N)$ number of group elements. - PSI with unbalanced inputs: We apply our techniques to private set intersection with unbalanced set sizes (where the receiver has a smaller set) and achieve receiver communication of $O((m+\lambda) \log N)$ group elements where $m, N$ are the sizes of the receiver and sender sets, respectively. Similarly, after a one-time setup (or one PSI instance), any following PSI instance only requires communication cost $O(m \cdot \log N)$ number of group elements. All previous sublinear-communication non-FHE based PSI protocols for the above unbalanced setting were also based on rate-1 OT, but incurred at least $O(\lambda^2 m \log N)$ group elements. 

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4. Lattice-Based Public Key Searchable Encryption from Experimental Perspectives

   https://doi.org/10.1109/TDSC.2018.2867462  

   Behnia, Rouzbeh ; Ozmen, Muslum Ozgur ; Yavuz, Attila Altay ( August 2018 , IEEE Transactions on Dependable and Secure Computing)

   Public key Encryption with Keyword Search (PEKS) aims in mitigating the impacts of data privacy versus utilization dilemma by allowing any user in the system to send encrypted files to the server to be searched by a receiver. The receiver can retrieve the encrypted files containing specific keywords by providing the corresponding trapdoors of these keywords to the server. Despite their merits, the existing PEKS schemes introduce a high end-to-end delay that may hinder their adoption in practice. Moreover, they do not scale well for large security parameters and provide no post-quantum security promises. In this paper, we propose novel lattice-based PEKS schemes that offer a high computational efficiency along with better security assurances than that of the existing alternatives. Specifically, our NTRU-PEKS scheme achieves 18 times lower end-to-end delay than the most efficient pairing-based alternatives. Our LWE-PEKS offers provable security in the standard model with a reduction to the worst-case lattice problems. We fully implemented our NTRU-PEKS scheme and benchmarked its performance as deployed on Amazon Web Services cloud infrastructures. 

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5. Proximity Searchable Encryption for the Iris Biometric

   https://doi.org/10.1145/3488932.3497754  

   Cachet, Chloe ; Ahmad, Sohaib ; Demarest, Luke ; Hamlin, Ariel ; Fuller, Benjamin ( May 2022 , ASIA CCS'22)

   Biometric databases collect people's information and allow users to perform proximity searches (finding all records within a bounded distance of the query point) with few cryptographic protections. This work studies proximity searchable encryption applied to the iris biometric. Prior work proposed inner product functional encryption as a technique to build proximity biometric databases (Kim et al., SCN 2018). This is because binary Hamming distance is computable using an inner product. This work identifies and closes two gaps to using inner product encryption for biometric search: Biometrics naturally use long vectors often with thousands of bits. Many inner product encryption schemes generate a random matrix whose dimension scales with vector size and have to invert this matrix. As a result, setup is not feasible on commodity hardware unless we reduce the dimension of the vectors. We explore state of the art techniques to reduce the dimension of the iris biometric and show that all known techniques harm the accuracy of the resulting system. That is, for small vector sizes multiple unrelated biometrics are returned in the search. For length 64 vectors, at a 90% probability of the searched biometric being returned, 10% of stored records are erroneously returned on average. Rather than changing the feature extractor, we introduce a new cryptographic technique that allows one to generate several smaller matrices. For vectors of length 1024 this reduces time to run setup from 23 days to 4 minutes. At this vector length, for the same $90%$ probability of the searched biometric being returned, .02% of stored records are erroneously returned on average. Prior inner product approaches leak distance between the query and all stored records. We refer to these as distance-revealing. We show a natural construction from function hiding, secret-key, predicate, inner product encryption (Shen, Shi, and Waters, TCC 2009). Our construction only leaks access patterns, and which returned records are the same distance from the query. We refer to this scheme as distance-hiding. We implement and benchmark one distance-revealing and one distance-hiding scheme. The distance-revealing scheme can search a small (hundreds) database in 4 minutes while the distance-hiding scheme is not yet practical, requiring 3.5 hours. 

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