We present an improved constant-round secure two-party protocol for integer comparison functionality, which is one of the most fundamental building blocks in secure computation. Our protocol is in the so-called client-server model, which is utilized in real-world MPC products such as Sharemind, where any number of clients can create shares of their input and distribute to the servers who then jointly compute over the shares and return the shares of the result to the client. In the client-aided client-server model, as mentioned briefly by Mohassel and Zhang (S&P'17), a client further generates and distributes some necessary correlated randomness to servers. Such correlated randomness admits efficient protocols since otherwise, servers have to jointly generate randomness by themselves, which can be inefficient. In this paper, we improve the state-of-the-art constant-round comparison protocols by Damgå rd et al. (TCC'06) and Nishide and Ohta (PKC'07) in the client-aided model. Our techniques include identifying correlated randomness in these comparison protocols. Along the way, we also use tree-based techniques for a building block, which deviate from the above two works. Our proposed protocol requires only 5 communication rounds, regardless of the bit length of inputs. This is at least 5 times fewer rounds than existing protocols. We implement our secure comparison protocol in C++. Our experimental results show that this low-round complexity benefits in high-latency networks such as WAN. We also present secure Min/Argmin protocols using the secure comparison protocol.

Research on adversarial examples for machine learning has received much attention in recent years. Most of previous approaches are white-box attacks; this means the attacker needs to obtain before-hand internal parameters of a target classifier to generate adversarial examples for it. This condition is hard to satisfy in practice. There is also research on black-box attacks, in which the attacker can only obtain partial information about target classifiers; however, it seems we can prevent these attacks, since they need to issue many suspicious queries to the target classifier. In this paper, we show that a naive defense strategy based on surveillance of number query will not suffice. More concretely, we propose to generate not pixel-wise but block-wise adversarial perturbations to reduce the number of queries. Our experiments show that such rough perturbations can confuse the target classifier. We succeed in reducing the number of queries to generate adversarial examples in most cases. Our simple method is an untargeted attack and may have low success rates compared to previous results of other black-box attacks, but needs in average fewer queries. Surprisingly, the minimum number of queries (one and three in MNIST and CIFAR-10 dataset, respectively) is enough to generate adversarial examples in some cases. Moreover, based on these results, we propose a detailed classification for black-box attackers and discuss countermeasures against the above attacks.

Secure multi-party computation (MPC) allows a set of parties to compute a function jointly while keeping their inputs private. MPC has been actively studied, and there are many research results both in the theoretical and practical research fields. In this paper, we introduce the basic matters on MPC and show recent practical advances. We first explain the settings, security notions, and cryptographic building blocks of MPC. Then, we show and discuss current situations on higher-level secure protocols, privacy-preserving data analysis, and frameworks/compilers for implementing MPC applications with low-cost.

Integer division is one of the most fundamental arithmetic operators and is ubiquitously used. However, the existing division protocols in secure multi-party computation (MPC) are inefficient and very complex, and this has been a barrier to applications of MPC such as secure machine learning. We already have some secure division protocols working in Z2n. However, these existing results have drawbacks that those protocols needed many communication rounds and needed to use bigger integers than in/output. In this paper, we improve a secure division protocol in two ways. First, we construct a new protocol using only the same size integers as in/output. Second, we build efficient constant-round building blocks used as subprotocols in the division protocol. With these two improvements, communication rounds of our division protocol are reduced to about 36% (87 rounds → 31 rounds) for 64-bit integers in comparison with the most efficient previous one.

The concept of threshold public key encryption (TPKE) with the special property called key re-splittability (re-splittable TPKE, for short) was introduced by Hanaoka et al. (CT-RSA 2012), and used as one of the building blocks for constructing their proxy re-encryption scheme. In a re-splittable TPKE scheme, a secret key can be split into a set of secret key shares not only once, but also multiple times, and the security of the TPKE scheme is guaranteed as long as the number of corrupted secret key shares under the same splitting is smaller than the threshold. In this paper, we show several new constructions of a re-splittable TPKE scheme by extending the previous (ordinary) TPKE schemes. All of our proposed schemes are based on discrete logarithm (DL)-type assumptions. Therefore, our results suggest that key re-splittability is a very natural property for DL-type TPKE schemes.