In conventional ( k , n ) threshold secret sharing, secret information or input can be recovered by collecting k shares from n servers, regardless of the honesty of the player. However, in asymmetric secret sharing, the input remains unrecoverable even if the attacker collects all shares from all data servers. Asymmetric secret sharing provides an asymmetric structure in which only an honest/authorized player can regain the input by combining shares from the data servers with pseudorandom numbers that are generated by the authorized player to complete the required k shares. Nevertheless, the asymmetric secret sharing scheme does not rely on information-theoretic security but rather on computational security. In this study, we first demonstrate the vulnerability of the conventional computationally secure asymmetric secret sharing scheme by presenting possible attacks on the scheme. We then show that by introducing true random numbers, an asymmetric secret sharing scheme with information-theoretic security can be achieved under certain conditions. We also identify and provide a detailed discussion of the conditions required to achieve information-theoretic security. However, the required conditions result in a reduction in storage efficiency on the server. We implemented our proposed method and evaluated its efficiency under these conditions, and showed that the execution time remains within the acceptable range and has a minimal effect on practical use. Moreover, we show that the proposed method can realize new applications that are not possible with conventional secret sharing schemes, such as secure data management that does not leak secret information even if the entire dataset in the cloud containing the shares is compromised, and communication, including IoT communication.

Secure computation methods include methods that use homomorphic encryption (HE) and those that use secret sharing (SS). Secure computation based on HE can be realized using one server, and the computation process can be made public if the encryption key is kept secure. However, HE generally requires a substantial computation cost. In contrast, SS has the advantage of low computation cost, allowing for high-speed processing; however, all servers must be managed independently. And the process of k or more servers cannot be disclosed. In particular, secret input will be leaked when the same organization manages multiple servers to implement SS. Therefore, a complex model where each server is independently managed is required. Iwamura et al. proposed a secure computation that is information-theoretic secure in n≥k instead of n≥2k−1 by assuming a trusted third party (TTP). In this paper, by making more effective use of a TTP, we demonstrate that secure computation based on SS is possible with only one computing server. Moreover, we show that the entire computation process can be disclosed if the key is managed safely. We realize a method that solves the disadvantages of conventional approaches with a faster computation than those methods.

Federated Learning (FL) [1] , a new form of distributed machine learning, has attracted much attention as a technique for privacy-preserving big data analysis. Because FL does not disclose raw data outside the device, it can improve data privacy compared to the method aggregating raw data in the cloud.

With the increase in Internet of Things (IoT) devices, machine learning and big data analysis have been rapidly developing. The current big data analysis based on deep learning assumes that the raw data owned by countless users is aggregated into the cloud. However, the number of applications requiring data containing personal information, such as healthcare, increases every year. There are many concerns about operating a system that assumes data aggregation to the cloud due to risks such as data leakage.

e realize MPC of multiplication with the setting of N=k,n≥2k-1. We also show that our proposed method is information theoretic secure against a semi-honest adversary.

In recent years, the concept of Internet of Things (IoT) network has been extensively discussed. Hamasaki et al. proposed a method of group key sharing using geometric characteristic. Thereafter, a method for sharing a pairwise key by implementing the Hamasaki et al.'s method had been proposed by Nishigami et al. However, we found that in this method, when a node and its fellow nodes are attacked together, the keys of the rest of the nodes will be leaked. Therefore, in this paper, we propose a method that enables a pairwise key to be securely shared. In addition, we extend our method of pairwise key sharing to efficiently share pairwise, group, and global keys. Finally, we evaluate the efficiency of our proposed method.

This paper proposes a secure routing protocol based on an ad-hoc on-demand distance vector (AODV) that successfully achieves both security and communication efficiency. Although many studies have previously discussed such a secure protocol, the conventional methods significantly degrade the communication efficiency because of large packets and complex communication procedures. The proposed method allows the intermediate node to generate a route reply (RREP). This is impossible in conventional methods due to the restriction of digital signatures in route requests (RREQ). In the proposed method, each intermediate node holds a packet received from a specific node in the past, and appends the held packet to the RREQ of another node and generates its own signed RREP. This procedure guarantees that the third party holds the route to the destination. It is shown that the proposed method outperforms conventional secure protocols in terms of network load.

In this paper, we propose secure and efficient outsourcing of matrix multiplication based on secret sharing scheme and using only one server. Matrix multiplication has been widely used in the field of machine learning, including deep learning. However, as the size of a matrix becomes larger, the computational complexity becomes more enormous (e.g., matrix multiplication between two m ×$m$matrices can be done with O($m$3) complexity). Because of the limited performance or storage on the device, it is impossible for an individual to perform such large-scale computations. To solve this problem, the technology that enables the consumer as a client to outsource computation securely to a high-performance server in the cloud, namely, secure outsourcing computation is studied. Our method is realized by multiplying some shares of a secret by different random numbers. The proposed method removes the disadvantage of secret sharing scheme that needs multiple servers to perform operations of less computational complexity than those of the method based on homomorphic encryption. We prove the security of our method against not only passive but also active adversaries. In addition, we show that our method is more efficient than existing methods of secure outsourcing computation.

A wireless sensor network (WSN) is composed of sensor nodes and a base station. In WSNs, constructing an efficient key-sharing scheme to ensure a secure communication is important. In this paper, we propose a new key-sharing scheme for groups, which shares a group key in a single broadcast without being dependent on the number of nodes. This scheme is based on geometric characteristics and has information-theoretic security in the analysis of transmitted data. We compared our scheme with conventional schemes in terms of communication traffic, computational complexity, flexibility, and security, and the results showed that our scheme is suitable for an Internet-of-Things (IoT) network.

Typically, when secrecy multiplication is performed in multiparty computation using Shamir's (k,n) threshold secret sharing scheme, the result is a polynomial with degree of 2k-2 instead of k-1 This causes a problem where, in order to reconstruct a multiplication result, the number of polynomials needed will increase from k to 2k-1. In this paper, we propose a multiparty computation that uses a secret sharing scheme that is secure against a product-sum operation but does not increase the degree of polynomial of the output. We prove that all combinations of the basic operations (addition, subtraction, multiplication, and division) can be performed securely using this scheme. We also propose three preconditions and finally show that our proposed method is information-theoretic secure against a passive adversary.

An aggregate signature scheme is a primitive whereby each signer signs an individual document and combines them to compress data size. We propose an aggregate signature scheme which is an extension in two standpoints of structured signatures and ID-based signatures, i.e., we construct an identity-based structured aggregate signature scheme. The proposed scheme is expected to be used with consumer-generated media services. We prove the security of the proposed scheme with tight reduction under the computational Diffie-Hellman (CDH) assumption in the random oracle model. Tight reduction means that the cost of a reduction algorithm is independent of an adversary's capability, i.e., security is not downgraded by the adversary's capability. To the best of our knowledge, no structured signature scheme with tight reduction has been proposed to date because it contains complicated structures that make the reduction inefficient. Note that the security of our scheme captures the switching attack (CCS 2007, Boldyreva et al.) and the re-ordering attack (ISPEC 2007, Shao), which break several famous schemes.

Secret sharing schemes have recently been considered to apply for cloud computing in which many users distribute multiple data to servers. However, when Shamir's (k, n) secret sharing is applied to cloud systems, the amount of share increases more than n times the amount of the secret. Therefore, in this paper we propose a new secret sharing scheme that can reduce the amount of share different from Ramp type secret sharing, suitable for cloud systems, and we prove that it is computationally secure.

In recent years, wireless sensor network technology has been frequently used in various fields, thereby making it increasingly important to ensure that the data being transferred remains confidential. Symmetric-key cryptography, which does not require high computing capacity, is a method that is generally used because the computing and memory requirements of sensor nodes are low. An implementation of symmetric-key cryptography is needed in order to achieve high-speed processing of sensor nodes. In this paper, we propose and evaluate a fast implementation scheme of the Advanced Encryption Standard using an inline-assembler that is suitable for the ATmega1281 microcontroller. This microcontroller is a part of the Atmel AVR series and is often equipped with sensor nodes for use in wireless sensor networks.

A sensor node has extremely limited power supply capacity and operation performance, therefore, key management schemes that can be achieved with less calculation in sensor networks have been proposed. However, these key management schemes cannot be flexibly applied to various connection topologies and network configurations. In this paper, we propose a key management scheme that can be generally used in a network that supports various connection topologies and that is capable of adding new nodes. Finally, we implement and evaluate our scheme.

Attribute information such as age, gender, and job is used in user registration and questionnaires.A verifier must consider what method to use for confirming attribute information when it is used online.For instance,the reliability of the information varies with the method:the verifier can accept the user's claim,confirm by certificate,confirm face-to-face or use other methods. Therefore, the reliability of attribute information becomes a problem when strict verification is necessary for a contract.In this paper,we consider the reliability of registration and attribute information that is exchanged and propose a method by which the reliability of attribute information and its grounds can be returned when attributes are exchanged.

Digital watermarks provide the capability to insert additional information onto various media, such as still images, movies and audio, by utilizing features of the content. Several methods for printed documents have already been proposed using features of the text or images. In order to overcome the disadvantages of existing methods, we have proposed a new information hiding scheme for printed documents; namely, the artificial fiber pattern by using the features of the paper instead of those of the contents. The method has features of rotational invariance and low visibility. In this paper, we improve the algorithm aimed at equipment independence and the robustness against physical attacks.

Fragile watermarking is a technology for detecting manipulations in an image, such as the digital signature in cryptography. However, the classification of attacks is not fixed in the security evaluation of existing fragile watermarking schemes, although many schemes have been proposed. In this paper, typical fragile watermarking schemes using a public key cryptosystem are evaluated from the viewpoint of a practical watermarking service. In this evaluation, nine attacks on watermarked images are defined and are classified as: watermarked image attacks, similar to cipher text attacks in cryptography; known original image attacks, similar to known plain text attacks; chosen original image attacks, similar to chosen plain text attacks. We show that the existing schemes are not secure against all attacks and propose a new scheme that is secure against such attacks and useful for a practical watermarking service.

This paper presents an authentication scheme for a JPEG 2000 image codestream, which is obtained by using JPEG 2000 Interactive Protocol (JPIP). JPIP allows a client to request a JPEG 2000 image that has a different representation from the original image. The client-requested image codestream is a portion of the original JPEG 2000 codestream and its structure differs for each client request. To verify the authenticity of the image requested by the client, a scalable verification mechanism is required. Hence, we propose a new scalable authentication scheme using an aggregate signature. The proposed scheme allows the scalable generation of digital signatures for any client-requested image. Simulation results show the effectiveness of the proposed scheme.

This brief contribution proposes a new class of systolic-arrays to perform Binary Reed-Solomon (RS) decoding procedures including erasure correction. Such RS decoder is suitable for VLSI implementation since the arrays consist of simple processing elements of the same type.>