In this paper, we propose memory- and round-efficient protocols for securely evaluating arithmetic primitives. We focus on secure two-party computation over the ring ℤ2k that achieves security against semi-honest adversaries and works in the pre-processing model. Our protocols rely on the unit vectorization technique introduced by Boyle et al. (TCC 2019). The unit vectorization technique provides online-optimal protocols for several fundamental operations in the pre-processing model. However, a relatively large memory cost for correlated randomness is required, which might become an obstacle in a large-scale application. In order to achieve both memory and communication efficiency, we propose a size reduction method that uses unit vectorization only for short-length inputs, and based on this, construct two-round protocols for equality test, detecting the most significant non-zero bit, detecting wrap-around, and less-than comparison. In addition, as applications of these results, we provide practically efficient protocols for integer division, integer square root, integer logarithm, and modular exponentiation.

Parallel computation is an important aspect of multi-party computation, not only in terms of improving efficiency, but also in terms of providing privacy for computation involving conditional branching based on private data. While applying multi-party computation in parallel over several sets of input data is straightforward if the partitioning of the input data into sets is publicly known, the problem becomes much more challenging when this partitioning is private. This setting is relevant to broad class of secure computations, in particular to secure graph and database analysis in which the underlying data (graph or database) is private. In this paper, we consider a general class of functions which can be expressed via the iterative evaluation of a binary associative operation, and propose efficient protocols for evaluating such functions in parallel over privately partitioned input data. Our protocols are optimal in terms of the required number of evaluations of the underlying binary operation (i.e.\ N-1 evaluations for total input size N), while simultaneously achieving a round complexity which is only logarithmic in the total size of the input data (i.e.\ O(łog N)).

Dynamic searchable symmetric encryption (SSE) enables clients to update and search encrypted data stored on a server and provides efficient search operations instead of leakages of inconsequential information. The amount of permitted leakage is a crucial factor of dynamic SSE; more leakage allows us to design an efficient scheme, while leakage attacks tell us that the leakage has a real-world impact. Leakage-abuse attacks (NDSS 2012) and subsequent works suggest that dynamic SSE schemes should not unnecessarily reveal extra information during the search procedure, and in particular, file-injection attacks (USENIX Security 2016) showed that forward privacy, which restricts the leakage during the addition procedure, is a vital security notion for dynamic SSE. In this paper, we propose a new dynamic SSE scheme with a good balance of efficiency and security levels; our scheme achieves both high efficiency and forward-privacy and only requires the decent leakage, i.e., only allows the leakage of search and access patterns during search operations. Specifically, we first show there is still no such scheme by uncovering a flaw in the security proof of Etemad et al.'s scheme (PoPETs 2018) and showing that extra leakage is required to fix it. We then propose the first forward-private dynamic SSE scheme that only requires symmetric-key primitives and the standard, decent leakage to prove the security. Although the client's information is slightly larger than existing schemes, our experimental results show that our scheme is comparable to Etemad et al.'s scheme, which is the most-efficient-ever scheme with forward privacy, in terms of efficiency.

We present a highly-scalable secure computation of graph algorithms, which hides all information about the topology of the graph or other input values associated with nodes or edges. The setting is where all nodes and edges of the graph are secret-shared between multiple servers, and a secure computation protocol is run between these servers. While the method is general, we demonstrate it in a 3-server setting with an honest majority, with either semi-honest security or full security. A major technical contribution of our work is replacing the usage of secure sort protocols with secure shuffles, which are much more efficient. Full security against malicious behavior is achieved by adding an efficient verification for the shuffle operation, and computing circuits using fully secure protocols. We demonstrate the applicability of this technology by implementing two major algorithms: computing breadth-first search (BFS), which is also useful for contact tracing on private contact graphs, and computing maximal independent set (MIS). We implement both algorithms, with both semi-honest and full security, and run them within seconds on graphs of millions of elements.

In this paper we propose efficient two-party protocols for obliviously applying a (possibly random) linear group action to a data set. Our protocols capture various applications such as oblivious shuffles, circular shifts, matrix multiplications, to name just a few. A notable feature enjoyed by our protocols, is that they admit a round-optimal (more precisely, one-round) online computation phase, once an input-independent off-line computation phase has been completed. Our oblivious shuffle is the first to achieve a round-optimal online phase. The most efficient instantiations of our protocols are obtained in the so-called client-aided client-server setting, where the offline phase is run by a semi-honest input party (client) who will then distribute the generated correlated randomness to the computing parties (servers). When comparing the total running time to the previous best two-party oblivious shuffle protocol by Chase et al. (Asiacrypt 2020), our shuffle protocol in this client-aided setting is up to 105 times and 152 times faster, in the LAN and WAN setting, respectively. We additionally show how the Chase et al. protocol (which is a standard two-party protocol) can be modified to leverage the advantages of the client-aided setting, but show that, even doing so, our scheme is still two times faster in the online phase and 1.34 times faster in total on average.

Biometric authentication is one of the promising alternatives to standard password-based authentication offering better usability and security. In this work, we revisit the biometric authentication based on fuzzy signatures introduced by Takahashi et al. (ACNS'15, IJIS'19). These are special types of digital signatures where the secret signing key can be a ''fuzzy'' data such as user's biometrics. Compared to other cryptographically secure biometric authentications as those relying on fuzzy extractors, the fuzzy signature-based scheme provides a more attractive security guarantee. However, despite their potential values, fuzzy signatures have not attracted much attention owing to their theory-oriented presentations in all prior works. For instance, the discussion on the practical feasibility of the assumptions (such as the entropy of user biometrics), which the security of fuzzy signatures hinges on, is completely missing.

This paper introduces a new capability for group signatures called message-dependent opening. It is intended to weaken the high trust placed on the opener; i.e., no anonymity against the opener is provided by an ordinary group signature scheme. In a group signature scheme with message-dependent opening (GS-MDO), in addition to the opener, we set up an admitter that is not able to extract any user’s identity but admits the opener to open signatures by specifying messages where signatures on the specified messages will be opened by the opener. The opener cannot extract the signer’s identity from any signature whose corresponding message is not specified by the admitter. This paper presents formal definitions of GS-MDO and proposes a generic construction of it from identity-based encryption and adaptive non-interactive zero-knowledge proofs. Moreover, we propose two specific constructions, one in the standard model and one in the random oracle model. Our scheme in the standard model is an instantiation of our generic construction but the message-dependent opening property is bounded. In contrast, our scheme in the random oracle model is not a direct instantiation of our generic construction but is optimized to increase efficiency and achieves the unbounded message-dependent opening property. Furthermore, we also demonstrate that GS-MDO implies identity-based encryption, thus implying that identity-based encryption is essential for designing GS-MDO schemes.

Protocols for secure multiparty computation (MPC) enable a set of mutually distrusting parties to compute an arbitrary function of their inputs while preserving basic security properties like privacy and correctness. The study of MPC was initiated in the 1980s where it was shown that any function can be securely computed, thus demonstrating the power of this notion. However, these proofs of feasibility were theoretical in nature and it is only recently that MPC protocols started to become efficient enough for use in practice. Today, we have protocols that can carry out large and complex computations in very reasonable time (and can even be very fast, depending on the computation and the setting). Despite this amazing progress, there is still a major obstacle to the adoption and use of MPC due to the huge expertise needed to design a specific MPC execution. In particular, the function to be computed needs to be represented as an appropriate Boolean or arithmetic circuit, and this requires very specific expertise. In order to overcome this, there has been considerable work on compilation of code to (typically) Boolean circuits. One work in this direction takes a different approach, and this is the SPDZ compiler (not to be confused with the SPDZ protocol) that takes high-level Python code and provides an MPC run-time environment for securely executing that code. The SPDZ compiler can deal with arithmetic and non-arithmetic operations and is extremely powerful. However, until now, the SPDZ compiler could only be used for the specific SPDZ family of protocols, making its general applicability and usefulness very limited. In this paper, we extend the SPDZ compiler so that it can work with general underlying protocols. Our SPDZ extensions were made in mind to enable the use of SPDZ for arbitrary protocols and to make it easy for others to integrate existing and new protocols. We integrated three different types of protocols, an honest-majority protocol for computing arithmetic circuits over a field (for any number of parties), a three-party honest majority protocol for computing arithmetic circuits over the ring of integers Z2n, and the multiparty BMR protocol for computing Boolean circuits. We show that a single high-level SPDZ-Python program can be executed using all of these underlying protocols (as well as the original SPDZ protocol), thereby making SPDZ a true general run-time MPC environment.In order to be able to handle both arithmetic and non-arithmetic operations, the SPDZ compiler relies on conversions from field elements to bits and back. However, these conversions do not apply to ring elements (in particular, they require element division), and we therefore introduce new bit decomposition and recomposition protocols for the ring over integers with replicated secret sharing. These conversions are of independent interest and utilize the structure of Z2n (which is much more amenable to bit decomposition than prime-order fields), and are thus much more efficient than all previous methods. We demonstrate our compiler extensions by running a complex SQL query and a decision tree evaluation over all protocols.

A variety of secure multiparty computation (MPC) protocols have been proposed up to now. Since their performance characteristics are incomparable, the most suitable MPC protocol may be completely different depending on the given computational task and environment. It is tedious work to compare all the possibility to choose the most suitable MPC. The paper " Generalizing the SPDZ Compiler For Other Protocols'' in this ACM-CCS 2018 shows a framework for adding MPC protocols to a development tool of MPC program called "SPDZ'', which enables to compare multiple protocols easily. This poster and demo show how this framework is useful for choosing the suitable protocol for given target computation and environment.

Secure multiparty computation enables a set of parties to securely carry out a joint computation of their private inputs without revealing anything but the output. In the past few years, the efficiency of secure computation protocols has increased in leaps and bounds. However, when considering the case of security in the presence of malicious adversaries (who may arbitrarily deviate from the protocol specification), we are still very far from achieving high efficiency. In this paper, we consider the specific case of three parties and an honest majority. We provide general techniques for improving efficiency of cut-and-choose protocols on multiplication triples and utilize them to significantly improve the recently published protocol of Furukawa et al. (ePrint 2016/944). We reduce the bandwidth of their protocol down from 10 bits per AND gate to 7 bits per AND gate, and show how to improve some computationally expensive parts of their protocol. Most notably, we design cache-efficient shuffling techniques for implementing cut-and-choose without randomly permuting large arrays (which is very slow due to continual cache misses). We provide a combinatorial analysis of our techniques, bounding the cheating probability of the adversary. Our implementation achieves a rate of approximately 1.15 billion AND gates per second on a cluster of three 20-core machines with a 10Gbps network. Thus, we can securely compute 212,000 AES encryptions per second (which is hundreds of times faster than previous work for this setting). Our results demonstrate that high-throughput secure computation for malicious adversaries is possible.

Secure multi-party computation (SMPC) is a cryptographic tool that enables a set of parties to jointly compute any function of their inputs while keeping the privacy of inputs. The paper "High Throughput Semi-Honest Secure Three-Party Computation with an Honest Majority" in this ACM CCS 2016 [4] presents a new protocol which its implementation carried out over 1,300,000 AESs per second and was able to support 35,000 login queries of Kerberos authentication per second. This poster/demo presents the design of the implementation and demonstrates the Kerberos authentication over here. The design will show how this high-throughput three-party computation can be done using simple servers. The demonstration proves that secure multiparty computation of Kerberos authentications in large organizations is now practical.

In this paper, we describe a new information-theoretic protocol (and a computationally-secure variant) for secure three-party computation with an honest majority. The protocol has very minimal computation and communication; for Boolean circuits, each party sends only a single bit for every AND gate (and nothing is sent for XOR gates). Our protocol is (simulation-based) secure in the presence of semi-honest adversaries, and achieves privacy in the client/server model in the presence of malicious adversaries. On a cluster of three 20-core servers with a 10Gbps connection, the implementation of our protocol carries out over 1.3 million AES computations per second, which involves processing over 7 billion gates per second. In addition, we developed a Kerberos extension that replaces the ticket-granting-ticket encryption on the Key Distribution Center (KDC) in MIT-Kerberos with our protocol, using keys/ passwords that are shared between the servers. This enables the use of Kerberos while protecting passwords. Our implementation is able to support a login storm of over 35,000 logins per second, which suffices even for very large organizations. Our work demonstrates that high-throughput secure computation is possible on standard hardware.

Group signature with message-dependent opening (GS-MDO) is a kind of group signature in which only the signers who have created group signatures on problematic messages will be identified. In the previous GS-MDO scheme, however, the number of problematic messages is bounded owing to a limitation of the Groth-Sahai proofs. In this paper, we propose the first GS-MDO scheme with the unbounded-MDO functionality in the random oracle model. Our unbounded GS-MDO scheme is based on the short group signature scheme proposed by Boneh, Boyen, and Shacham and the Boneh-Franklin identity-based encryption scheme. To combine these building blocks and to achieve CCA-anonymity, we also construct a special type of multiple encryption. This technique yields an efficient construction compared with the previous bounded GS-MDO scheme: the signature of our scheme contains about 16 group elements (3630 bits), whereas that of the previous scheme has about 450 group elements (75820 bits).