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1. Towards Multiparty Computation Withstanding Coercion of All Parties

   Canetti, Ran; Poburinnaya, Oxana (November 2021, Theory of Cryptography Conference)

   null (Ed.)

   Incoercible multi-party computation (Canetti-Gennaro ’96) allows parties to engage in secure computation with the additional guarantee that the public transcript of the computation cannot be used by a coercive outsider to verify representations made by the parties regarding their inputs, outputs, and local random choices. That is, it is guaranteed that the only deductions regarding the truthfulness of such representations, made by an outsider who has witnessed the communication among the parties, are the ones that can be drawn just from the represented inputs and outputs alone. To date, all incoercible secure computation protocols withstand coercion of only a fraction of the parties, or else assume that all parties use an execution environment that makes some crucial parts of their local states physically inaccessible even to themselves. We consider, for the first time, the setting where all parties are coerced, and the coercer expects to see the entire history of the computation. We allow both protocol participants and external attackers to access a common reference string which is generated once and for all by an uncorruptable trusted party. In this setting we construct: - A general multi-party function evaluation protocol, for any number of parties, that withstands coercion of all parties, as long as all parties use the prescribed ``faking algorithm'' upon coercion. This holds even if the inputs and outputs represented by coerced parties are globally inconsistent with the evaluated function. - A general two-party function evaluation protocol that withstands even the %``mixed'' case where some of the coerced parties do follow the prescribed faking algorithm. (For instance, these parties might collude with the coercer and disclose their true local states.) This protocol is limited to functions where the input of at least one of the parties is taken from a small (poly-size) domain. It uses fully deniable encryption with public deniability for one of the parties; when instantiated using the fully deniable encryption of Canetti, Park, and Poburinnaya (Crypto'20), it takes 3 rounds of communication. Both protocols operate in the common reference string model, and use fully bideniable encryption (Canetti Park and Poburinnaya, Crypto'20) and sub-exponential indistinguishability obfuscation. Finally, we show that protocols with certain communication pattern cannot be incoercible, even in a weaker setting where only some parties are coerced. 

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2. The More The Merrier: Reducing the Cost of Large Scale MPC

   Gordon, S. Dov; Starin, Daniel; Yerukhimovich, Arkady (January 2021, Eurocrypt)

   Canteaut, Anne; Standaert, Francois-Xavier (Ed.)

   Secure multi-party computation (MPC) allows multiple par-ties to perform secure joint computations on their private inputs. To-day, applications for MPC are growing with thousands of parties wish-ing to build federated machine learning models or trusted setups for blockchains. To address such scenarios we propose a suite of novel MPC protocols that maximize throughput when run with large numbers of parties. In particular, our protocols have both communication and computation complexity that decrease with the number of parties. Our protocols build on prior protocols based on packed secret-sharing, introducing new techniques to build more efficient computation for general circuits. Specifically, we introduce a new approach for handling linear attacks that arise in protocols using packed secret-sharing and we propose a method for unpacking shared multiplication triples without increasingthe asymptotic costs. Compared with prior work, we avoid the log|C|overhead required when generically compiling circuits of size |C| for use in a SIMD computation, and we improve over folklore “committee-based” solutions by a factor of O(s), the statistical security parameter. In practice, our protocol is up to 10X faster than any known construction, under a reasonable set of parameters. 

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3. The More The Merrier: Reducing the Cost of Large Scale MPC

   Gordon, S. Dov; Starin, Daniel; Yerukhimovich, Arkady (January 2021, Eurocrypt)

   Canteaut, Anne; Standaert, Francois-Xavier (Ed.)

   Secure multi-party computation (MPC) allows multiple par-ties to perform secure joint computations on their private inputs. To-day, applications for MPC are growing with thousands of parties wish-ing to build federated machine learning models or trusted setups for blockchains. To address such scenarios we propose a suite of novel MPC protocols that maximize throughput when run with large numbers of parties. In particular, our protocols have both communication and computation complexity that decrease with the number of parties. Our protocols build on prior protocols based on packed secret-sharing, introducing new techniques to build more efficient computation for general circuits. Specifically, we introduce a new approach for handling linear attacks that arise in protocols using packed secret-sharing and we propose a method for unpacking shared multiplication triples without increasingthe asymptotic costs. Compared with prior work, we avoid the log|C|overhead required when generically compiling circuits of size |C| for use in a SIMD computation, and we improve over folklore “committee-based” solutions by a factor of O(s), the statistical security parameter. In practice, our protocol is up to 10X faster than any known construction, under a reasonable set of parameters. 

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4. Enabling Real-Time Restoration of Compromised ECU Firmware in Connected and Autonomous Vehicles

   https://doi.org/10.1007/978-3-031-51630-6_2  

   Dafoe, Josh; Singh, Harsh; Chen, Niusen; Chen, Bo (February 2024, Springer Nature Switzerland)

   With increasing development of connected and autonomous vehicles, the risk of cyber threats on them is also increasing. Compared to traditional computer systems, a CAV attack is more critical, as it does not only threaten confidential data or system access, but may endanger the lives of drivers and passengers. To control a vehicle, the attacker may inject malicious control messages into the vehicle’s controller area network. To make this attack persistent, the most reliable method is to inject malicious code into an electronic control unit’s firmware. This allows the attacker to inject CAN messages and exhibit significant control over the vehicle, posing a safety threat to anyone in proximity. In this work, we have designed a defensive framework which allows restoring compromised ECU firmware in real time. Our framework combines existing intrusion detection methods with a firmware recovery mechanism using trusted hardware components equipped in ECUs. Especially, the firmware restoration utilizes the existing FTL in the flash storage device. This process is highly efficient by minimizing the necessary restored information. Further, the recovery is managed via a trusted application running in TrustZone secure world. Both the FTL and TrustZone are secure when the ECU firmware is compromised. Steganography is used to hide communications during recovery. We have implemented and evaluated our prototype implementation in a testbed simulating the real-world in-vehicle scenario. 

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5. Secure Comparisons of Single Nucleotide Polymorphisms Using Secure Multiparty Computation: Method Development

   https://doi.org/10.2196/44700  

   Woods, Andrew; Kramer, Skyler T; Xu, Dong; Jiang, Wei (January 2023, JMIR Bioinformatics and Biotechnology)

   Background While genomic variations can provide valuable information for health care and ancestry, the privacy of individual genomic data must be protected. Thus, a secure environment is desirable for a human DNA database such that the total data are queryable but not directly accessible to involved parties (eg, data hosts and hospitals) and that the query results are learned only by the user or authorized party. Objective In this study, we provide efficient and secure computations on panels of single nucleotide polymorphisms (SNPs) from genomic sequences as computed under the following set operations: union, intersection, set difference, and symmetric difference. Methods Using these operations, we can compute similarity metrics, such as the Jaccard similarity, which could allow querying a DNA database to find the same person and genetic relatives securely. We analyzed various security paradigms and show metrics for the protocols under several security assumptions, such as semihonest, malicious with honest majority, and malicious with a malicious majority. Results We show that our methods can be used practically on realistically sized data. Specifically, we can compute the Jaccard similarity of two genomes when considering sets of SNPs, each with 400,000 SNPs, in 2.16 seconds with the assumption of a malicious adversary in an honest majority and 0.36 seconds under a semihonest model. Conclusions Our methods may help adopt trusted environments for hosting individual genomic data with end-to-end data security. 

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