Homomorphic encryption (HE) is a promising approach for privacy-preserving applications, enabling a third party to assess functions on encrypted data. However, problems persist in implementing privacy-preserving applications through HE, including 1) long function evaluation latency and 2) limited HE primitives only allowing us to perform additions and multiplications. A homomorphic lookup-table (LUT) method has emerged to solve the above problems and enhance function evaluation efficiency. By leveraging homomorphic LUTs, intricate operations can be substituted. Previously proposed LUTs use bit-wise HE, such as TFHE, to evaluate single-input functions. However, the latency increases with the bit-length of the function’s input(s) and output. Additionally, an efficient implementation of multi-input functions remains an open question. This paper proposes a novel LUT-based privacy-preserving function evaluation method to handle multi-input functions while reducing the latency by adopting word-wise HE. Our optimization strategy adjusts table sizes to minimize the latency while preserving function output accuracy, especially for common machine-learning functions. Through our experimental evaluation utilizing the BFV scheme of the Microsoft SEAL library, we confirmed the runtime of arbitrary functions whose LUTs consist of all input-output combinations represented by given input bits: 1) single-input 12-bit functions in 0.14 s, 2) single-input 18-bit functions in 2.53 s, 3) two-input 6-bit functions in 0.17 s, and 4) three-input 4-bit functions in 0.20 s, employing four threads. Besides, we confirmed that our proposed table size optimization strategy worked well, achieving 1.2 times speed up with the same absolute error of order of magnitude of -4 (a × 10-4 where 1/$\sqrt{10}$ ≤ a < $\sqrt{10})$ for Swish and 1.9 times speed up for ReLU while decreasing the absolute error from order -2 to -4 compared to the baseline, i.e., polynomial approximation.

Homomorphic encryption (HE) is public key encryption that enables computation over ciphertexts without decrypting them. To overcome an issue that HE cannot achieve IND-CCA2 security, the notion of keyed-homomorphic encryption (KH-PKE) was introduced (Emura et al., PKC 2013), which has a separate homomorphic evaluation key and can achieve stronger security named KH-CCA security. The contributions of this paper are twofold. First, recall that the syntax of KH-PKE assumes that homomorphic evaluation is performed for single operations, and KH-CCA security was formulated based on this syntax. Consequently, if the homomorphic evaluation algorithm is enhanced in a way of gathering up sequential operations as a single evaluation, then it is not obvious whether or not KH-CCA security is preserved. In this paper, we show that KH-CCA security is in general not preserved under such modification, while KH-CCA security is preserved when the original scheme additionally satisfies circuit privacy. Secondly, Catalano and Fiore (ACM CCS 2015) proposed a conversion method from linearly HE schemes into two-level HE schemes, the latter admitting addition and a single multiplication for ciphertexts. In this paper, we extend the conversion to the case of linearly KH-PKE schemes to obtain two-level KH-PKE schemes. Moreover, based on the generalized version of Catalano-Fiore conversion, we also construct a similar conversion from d-level KH-PKE schemes into 2d-level KH-PKE schemes.

We propose how to homomorphically evaluate arbitrary univariate and bivariate integer functions such as division. A prior work proposed by Okada et al. (WISTP'18) uses polynomial evaluations such that the scheme is still compatible with the SIMD operations in BFV and BGV schemes, and is implemented with the input domain ℤ257. However, the scheme of Okada et al. requires the quadratic numbers of plaintext-ciphertext multiplications and ciphertext-ciphertext additions in the input domain size, and although these operations are more lightweight than the ciphertext-ciphertext multiplication, the quadratic complexity makes handling larger inputs quite inefficient. In this work, first we improve the prior work and also propose a new approach that exploits the packing method to handle the larger input domain size instead of enabling the SIMD operation, thus making it possible to work with the larger input domain size, e.g., ℤ215 in a reasonably efficient way. In addition, we show how to slightly extend the input domain size to ℤ216 with a relatively moderate overhead. Further we show another approach to handling the larger input domain size by using two ciphertexts to encrypt one integer plaintext and applying our techniques for uni/bivariate function evaluation. We implement the prior work of Okada et al., our improved version of Okada et al., and our new scheme in PALISADE with the input domain ℤ215, and confirm that the estimated run-times of the prior work and our improved version of the prior work are still about 117 days and 59 days respectively while our new scheme can be computed in 307 seconds.

Orbital angular momentum (OAM) multiplexing technology is being investigated for high-capacity point-to-point (PtP) wireless transmission toward beyond 5G systems. OAM multiplexing is a spatial multiplexing technique that utilizes the twisting of electromagnetic waves. Its advantage is that it reduces the computational complexity of the signal processing on spatial multiplexing. Meanwhile point-to-multi point (PtMP) wireless transmission, such as integrated access and backhaul (IAB) will be expected to simultaneously accommodates a high-capacity prioritized backhaul-link and access-links. In this paper, we study the extension of OAM multiplexing transmission from PtP to PtMP to meet the above requirements. We propose a backhaul prioritized resource control algorithm that maximizes the received signal-to-interference and noise ratio (SINR) of the access-links while maintaining the backhaul-link. The proposed algorithm features adaptive mode selection that takes into account the difference in the received power of each OAM mode depending on the user equipment position and the guaranteed power allocation of the backhaul capacity. We then evaluate the performance of the proposed method through computer simulation. The results show that throughput of the access-links improved compared with the conventional multi-beam multi-user multi-input multi-output (MIMO) techniques while maintaining the throughput of the backhaul-link above the required value with minimal feedback information.

Vibrating intrinsic reverberation chamber is being used as an in-situ EMC test equipment for large and complex systems such as automobiles and aircrafts. In this paper, the stirring conditions, such as tightness and shaking amplitude of the walls, of a vibrating intrinsic reverberation chamber have been analyzed using the method of moments. From the viewpoint of quantitative evaluation of the flexible moving walls configuration, it was found that the random electromagnetic environment can be generated under the stirring conditions of loose configuration and a shaking amplitude more than one eighth of the wavelength at the test frequency above the lowest usable frequency.

Fully homomorphic encryption (FHE) enables secret computations. Users can perform computation using data encrypted with FHE without decryption. Uploading private data without encryption to a public cloud has the risk of data leakage, which makes many users hesitant to utilize a public cloud. Uploading data encrypted with FHE avoids this risk, while still providing the computing power of the public cloud. In many cases, data are stored in HDDs because the data size increases significantly when FHE is used. One important data analysis is Apriori data mining. In this application, two files are accessed alternately, and this causes long-distance seeking on its HDD and low performance. In this paper, we propose a new striping layout with reservations for write areas. This method intentionally fragments files and arranges blocks to reduce the distance between blocks in a file and another file. It reserves the area for intermediate files of FHE Apriori. The performance of the proposed method was evaluated based on the I/O processing of a large FHE Apriori, and the results showed that the proposed method could improve performance by up to approximately 28%.

This paper presents a deep neural network (DNN) based symbol detection and modulation classification detector (SDMCD) for mixed blind signals detection. Unlike conventional methods that employ symbol detection after modulation classification, the proposed SDMCD can perform symbol recovery and modulation identification simultaneously. A cumulant and moment feature vector is presented in conjunction with a low complexity sparse autoencoder architecture to complete mixed signals detection. Numerical results show that SDMCD scheme has remarkable symbol error rate performance and modulation classification accuracy for various modulation formats in AWGN and Rayleigh fading channels. Furthermore, the proposed detector has robust performance under the impact of frequency and phase offsets.

Volume integral equations combined with orthogonality of guided mode and non-guided field are proposed for the TE incidence of two-dimensional optical slab waveguide. The slab waveguide is assumed to satisfy the single mode condition. The formulation of the integral equations are described in detail. The matrix equation obtained by applying the method of moments to the integral equations is shown. Numerical results for step, gap, and grating waveguides are given. They are compared to published papers to validate the proposed method.

In this paper, we propose the first private decision tree evaluation (PDTE) schemes which are suitable for use in Machine Learning as a Service (MLaaS) scenarios. In our schemes, a user and a model owner send the ciphertexts of a sample and a decision tree model, respectively, and a single server classifies the sample without knowing the sample nor the decision tree. Although many PDTE schemes have been proposed so far, most of them require to reveal the decision tree to the server. This is undesirable because the classification model is the intellectual property of the model owner, and/or it may include sensitive information used to train the model, and therefore the model also should be hidden from the server. In other PDTE schemes, multiple servers jointly conduct the classification process and the decision tree is kept secret from the servers under the assumption they do not collude. Unfortunately, this assumption may not hold because MLaaS is usually provided by a single company. In contrast, our schemes do not have such problems. In principle, fully homomorphic encryption allows us to classify an encrypted sample based on an encrypted decision tree, and in fact, the existing non-interactive PDTE scheme can be modified so that the server classifies only handling ciphertexts. However, the resulting scheme is less efficient than ours. We also show the experimental results for our schemes.

We propose deep neural network (DNN)-based speech enhancement that reduces musical noise and achieves better auditory impressions. The musical noise is an artifact generated by nonlinear signal processing and negatively affects the auditory impressions. We aim to develop musical-noise-free speech enhancement methods that suppress the musical noise generation and produce perceptually-comfortable enhanced speech. DNN-based speech enhancement using a soft mask achieves high noise reduction but generates musical noise in non-speech regions. Therefore, first, we define kurtosis matching for DNN-based low-musical-noise speech enhancement. Kurtosis is the fourth-order moment and is known to correlate with the amount of musical noise. The kurtosis matching is a penalty term of the DNN training and works to reduce the amount of musical noise. We further extend this scheme to standardized-moment matching. The extended scheme involves using moments whose orders are higher than kurtosis and generalizes the conventional musical-noise-free method based on kurtosis matching. We formulate standardized-moment matching and explore how effectively the higher-order moments reduce the amount of musical noise. Experimental evaluation results 1) demonstrate that kurtosis matching can reduce musical noise without negatively affecting noise suppression and 2) newly reveal that the sixth-moment matching also achieves low-musical-noise speech enhancement as well as kurtosis matching.

In this short note, we formally show that Keyed-Homomorphic Public Key Encryption (KH-PKE) is secure against key recovery attacks and ciphertext validity attacks that have been introduced as chosen-ciphertext attacks for homomorphic encryption.

A fully homomorphic encryption (FHE) would be the important cryptosystem as the basic scheme for the cloud computing. Since Gentry discovered in 2009 the first fully homomorphic encryption scheme, some fully homomorphic encryption schemes were proposed. In the systems proposed until now the bootstrapping process is the main bottleneck and the large complexity for computing the ciphertext is required. In 2011 Zvika Brakerski et al. proposed a leveled FHE without bootstrapping. But circuit of arbitrary level cannot be evaluated in their scheme while in our scheme circuit of any level can be evaluated. The existence of an efficient fully homomorphic cryptosystem would have great practical implications in the outsourcing of private computations, for instance, in the field of the cloud computing. In this paper, IND-CCA1secure FHE based on the difficulty of prime factorization is proposed which does not need the bootstrapping and it is thought that our scheme is more efficient than the previous schemes. In particular the computational overhead for homomorphic evaluation is O(1).

The impedance expansion method (IEM) is a circuit-modeling technique for electrically small devices based on the method of moments. In a previous study, a circuit model of a wireless power transfer (WPT) system was developed by utilizing the IEM and eigenmode analysis. However, this technique assumes that all the coupling elements (e.g., feeding loops and resonant coils) are in the absence of neighboring scatters (e.g., bodies of vehicles). This study extends the theory of the IEM to obtain the circuit model of a WPT system in the vicinity of a perfectly conducting scatterer (PCS). The numerical results show that the proposed method can be applied to the frequencies at which the dimension of the PCS is less than approximately a quarter wavelength. In addition, the yielded circuit model is found to be valid at the operating frequency band.

Two-ray (TR) fading model is one of the fading models to represent a worst-case fading scenario. We derive the exact closed-form expressions of the generalized moment generating function (G-MGF) for the TR fading model, which enables us to analyze the numerous types of wireless communication applications. Among them, we carry out several analytical results for the TR fading model, including the exact ergodic capacity along with asymptotic expressions and energy detection performance. Finally, we provide numerical results to validate our evaluations.

Angular Momentum (AM) has been considered as a new dimension of wireless transmissions as well as the intrinsic property of Electro-Magnetic (EM) waves. So far, AM is utilized as a discrete mode not only in the quantum states, but also in the statistical beam forming. Traditionally, the continuous value of AM is ignored and only the quantized mode number is identified. However, the recent discovery on electrons in spiral motion producing twisted radiation with AM, including Spin Angular Momentum (SAM) and Orbital Angular Momentum (OAM), proves that the continuous value of AM is available in the statistical EM wave beam. This is also revealed by the so-called fractional OAM, which is reported in optical OAM beams. Then, as the new dimension with continuous real number field, AM should turn out to be a certain spectrum, similar to the frequency spectrum usually in the wireless signal processing. In this letter, we mathematically define the AM spectrum and show the applications in the information theory analysis, which is expected to be an efficient tool for the future wireless communications with AM.

This paper proposes a generative moment matching network (GMMN)-based post-filtering method for providing inter-utterance pitch variation to singing voices and discusses its application to our developed mixing method called neural double-tracking (NDT). When a human singer sings and records the same song twice, there is a difference between the two recordings. The difference, which is called inter-utterance variation, enriches the performer's musical expression and the audience's experience. For example, it makes every concert special because it never recurs in exactly the same manner. Inter-utterance variation enables a mixing method called double-tracking (DT). With DT, the same phrase is recorded twice, then the two recordings are mixed to give richness to singing voices. However, in synthesized singing voices, which are commonly used to create music, there is no inter-utterance variation because the synthesis process is deterministic. There is also no inter-utterance variation when only one voice is recorded. Although there is a signal processing-based method called artificial DT (ADT) to layer singing voices, the signal processing results in unnatural sound artifacts. To solve these problems, we propose a post-filtering method for randomly modulating synthesized or natural singing voices as if the singer sang again. The post-filter built with our method models the inter-utterance pitch variation of human singing voices using a conditional GMMN. Evaluation results indicate that 1) the proposed method provides perceptible and natural inter-utterance variation to synthesized singing voices and that 2) our NDT exhibits higher double-trackedness than ADT when applied to both synthesized and natural singing voices.

Homomorphic encryption allows computation over encrypted data, and can be used for delegating computation: data providers encrypt their data and send them to an aggregator, who can then perform computation over the encrypted data on behalf of a client, without the underlying data being exposed to the aggregator. However, since the aggregator is merely a third party, it may be malicious, and in particular, may submit an incorrect aggregation result to the receiver. Ohara et al. (APKC2014) studied secure aggregation of time-series data while enabling the correctness of aggregation to be verified. However, they only provided a concrete construction in the smart metering system and only gave an intuitive argument of security. In this paper, we define verifiable homomorphic encryption (VHE) which generalizes their scheme, and introduce formal security definitions. Further, we formally prove that Ohara et al.'s VHE scheme satisfies our proposed security definitions.

In this paper, we propose the decomposition ring homomorphic encryption scheme, that is a homomorphic encryption scheme built on the decomposition ring, which is a subring of cyclotomic ring. By using the decomposition ring the structure of plaintext slot becomes ℤpl, instead of GF(pd) in conventional schemes on the cyclotomic ring. For homomorphic multiplication of integers, one can use the full of ℤpl slots using the proposed scheme, although in conventional schemes one can use only one-dimensional subspace GF(p) in each GF(pd) slot. This allows us to realize fast and compact homomorphic encryption for integer plaintexts. In fact, our benchmark results indicate that our decomposition ring homomorphic encryption schemes are several times faster than HElib for integer plaintexts due to its higher parallel computation.

In this paper, we show that the orbital angular momentum (OAM) communication performance with a circular loop antenna array can be drastically improved by exploiting the port azimuth effect at the 5-GHz band. The received signal and interference powers are analytically derived with generalized Z-matrices and the perturbation method for short-range OAM communication. The resulting formulas show that the interference power can be drastically suppressed by selecting the proper combination of port azimuths. We also explain the mechanism behind the reduction in interference power. For the obtained port azimuth combination, the simulated and measured transmission isolations at 1cm are better than 24.0 and 23.6dB at 5.3GHz, respectively. Furthermore, to estimate performance in 2×2 MIMO communication, constellations for 64-QAM are estimated. Measured EVMs are less than 3% where signals are clearly discriminated without any signal processing. For long-range OAM communication using paraboloids, the optimum port azimuth combination is estimated by monitoring the current distribution. For the obtained combination of the port azimuths, simulated and measured transmission isolations at 125cm are better than 15.7 and 12.0dB at 5.3GHz, respectively. The measured isolation for short and long ranges are improved by 9.2 and 4.5dB, respectively, compared with the data for the combination of the identical port azimuth.

In this letter, we investigate a design of efficient antenna allocation at the full duplex receiver (FDR) in a multi-input multi-output multi-eavesdropper (MIMOME) wiretap channel for physical layer security improvement. Specifically, we propose the allocation which are feasible for the practical scenario with self-interference (SI) taken into account, because the jamming signals from FDR not only confuse the eavesdropper but also inevitably cause SI at the FDR. Due to the nolinear and coupling of the antenna allocation optimization problem, we transform the original problem into an integer programming problem. Then, we derive the optimal solution and the corresponding beamforming matrices in closed-form by means of combining spatial alignment and null-space projection method. Furthermore, we present the feasibility condition and full-protection condition, which offer insight into principles that enable more efficient and effective use of FDR in the wiretap channel for security improvement. From the simulation results, we validate the theoretical analysis and demonstrate the outstanding performance of the proposed antennas allocation at FDR.