We focus on the construction of the digital signature scheme for local broadcast, which allows the devices with limited resources to securely transmit broadcast message. A multi-group authentication scheme that enables a node to authenticate its membership in multi verifiers by the sum of the secret keys has been proposed for limited resources. This paper presents a transformation which converts a multi-group authentication into a multi-group signature scheme. We show that the multi-group signature scheme converted by our transformation is existentially unforgeable against chosen message attacks (EUF-CMA secure) in the random oracle model if the multi-group authentication scheme is secure against impersonation under passive attacks (IMP-PA secure). In the multi-group signature scheme, a sender can sign a message by the secret keys which multiple certification authorities issue and the signature can validate the authenticity and integrity of the message to multiple verifiers. As a specific configuration example, we show the example in which the multi-group signature scheme by converting an error correcting code-based multi-group authentication scheme.

Recently, IoT compatible products have been popular, and various kinds of things are IoT compliant products. In these devices, cryptosystems and authentication are not treated properly, and security measures for IoT devices are not sufficient. Requirements of authentication for IoT devices are power saving and one-to-many communication. In this paper, we propose a zero-knowledge identification scheme using LDPC codes. In the proposed scheme, the zero-knowledge identification scheme that relies on the binary syndrome decoding problem is improved and the computational cost of identification is reduced by using the sparse parity-check matrix of the LDPC codes. In addition, the security level, computational cost and safety of the proposed scheme are discussed in detail.

In the case of drive-by download attacks, most malicious web sites identify the software environment of the clients and change their behavior. Then we cannot always obtain sufficient information appropriate to the client organization by automatic dynamic analysis in open services. It is required to prepare for expected incidents caused by re-accessing same malicious web sites from the other client in the organization. To authors' knowledge, there is no study of utilizing analysis results of malicious web sites for digital forensic on the incident and hedging the risk of expected incident in the organization. In this paper, we propose a system for evaluating the impact of accessing malicious web sites by using the results of multi-environment analysis. Furthermore, we report the results of evaluating malicious web sites by the multi-environment analysis system, and show how to utilize analysis results for forensic analysis and risk hedge based on actual cases of analyzing malicious web sites.

The Topics over Time (TOT) model allows users to be aware of changes in certain topics over time. The proposed method inputs the divided dataset of security blog posts based on a fixed period using an overlap period to the TOT. The results suggest the extraction of topics that include malware and attack campaign names that are appropriate for the multi-labeling of cyber threat intelligence reports.

Low-density parity-check (LDPC) codes are linear block codes defined by sparse parity-check matrices. The codes exhibit excellent performance under iterative decoding, and the weight distribution is used to analyze lower error probability of their decoding performance. In this paper, we propose a probabilistic method for computing the weight distribution of LDPC codes. The proposed method efficiently finds low-weight codewords in a given LDPC code by using Stern's algorithm, and stochastically computes the low part of the weight distribution from the frequency of the found codewords. It is based on a relation between the number of codewords with a given weight and the rate of generating the codewords in Stern's algorithm. In the numerical results for LDPC codes of length 504, 1008 and 4896, we could compute the weight distribution by the proposed method with greater accuracy than by conventional methods.

In the analysis of maximum-likelihood decoding performance of low-density parity-check (LDPC) codes, the weight distribution is an important factor. We presented a probabilistic method for computing the weight distribution of LDPC codes, and showed results of computing the weight distribution of several LDPC codes. In this paper, we improve our previously presented method and propose a probabilistic computation method with reliability for the weight distribution of LDPC codes. Using the proposed method, we can determine the weight distribution with small failure probability.

Ciphertext-Policy Attribute-Based Encryption (CP-ABE) is suitable for data access control on cloud storage systems. In ABE, to revoke users' attributes, it is necessary to make them unable to decrypt ciphertexts. Some CP-ABE schemes for efficient attribute revocation have been proposed. However, they have not been given a formal security proof against a revoked user, that is, whether they satisfy forward secrecy has not been shown or they just do not achieve fine-grained access control of shared data. We propose an attribute revocable attribute-based encryption with the forward secrecy for fine-grained access control of shared data. The proposed scheme can use both “AND” and “OR” policy and is IND-CPA secure under the Decisional Parallel Bilinear Diffie-Hellman Exponent assumption in the standard model.

Internet of Things (IoT) has been widely applied in various fields. IoT data can also be put to cloud, but there are still concerns regarding security and privacy. Ciphertext-Policy Attribute-Based Encryption (CP-ABE) is attracted attention in cloud storage as a suitable encryption scheme for confidential data share and transmission. In CP-ABE, the secret key of a user is associated with a set of attributes; when attributes satisfy the access structure, the ciphertext is able to be decrypted. It is necessary that multiple authorities issue and manage secret keys independently. Authorities that generate the secret key can be regarded as managing the attributes of a user in CP-ABE. CP-ABE schemes that have multiple authorities have been proposed. The other hand, it should consider that a user's operation at the terminals is not necessary when a user drop an attribute and key is updated and the design of the communication system is a simple. In this paper, we propose CP-ABE scheme that have multiple key authorities and can revoke attribute immediately with no updating user's secret key for attribute revocation. In addition, the length of ciphertext is fixed. The proposed scheme is IND-CPA secure in DBDH assumption under the standard model. We compare the proposed scheme and the other CP-ABE schemes and show that the proposed scheme is more suitable for cloud storage.

The application of Intelligent Transport Systems (ITS) transmits data with road-to-vehicle communication (RVC) and inter-vehicle communication (IVC). Digital signature is essential to provide security for RVC and IVC. The public key certificate is used to verify that a public key belongs to an individual prover such as user or terminal. A certificate revocation list (CRL) is used for verifying validity of the public key certificate. A certificate authority (CA) publishes a CRL and distributes it to vehicles. CRL distribution traffic disturbs ITS application traffic because of sharing wireless channel between them. To distribute it on low bit rate will help to ease the disturbance. Although multiplex transmitting is effective in reliable communication, a duplication of received packets is waste of bandwidth as a consequence. This paper proposes a CRL distribution scheme based on random network coding which can reduce duplicate packets. The simulation results show that the number of duplicate packets of the proposed scheme is less than that of a simple error correction (EC)-based scheme and the proposed one can distribute CRL to more vehicles than EC-based ones.

Dedicated Short Range Communication (DSRC) is currently standardized as a leading technology for the implementation of Vehicular Networks. Non-safety application in DSRC is emerging beyond the initial safety application. However, it suffers from a typical issue of low data delivery ratio in urban environments, where static and moving obstacles block or attenuate the radio propagation, as well as other technical issues such as temporal-spatial restriction, capital cost for infrastructure deployments and limited radio coverage range. On the other hand, Content-Centric Networking (CCN) advocates ubiquitous in-network caching to enhance content distribution. The major characteristics of CCN are compatible with the requirements of vehicular networks so that CCN could be available by vehicular networks. In this paper, we propose a CCN-based vehicle-to-vehicle (V2V) communication scheme on the top of DSRC standard for content dissemination, while demonstrate its feasibility by analyzing the frame format of Beacon and WAVE service advertisement (WSA) messages of DSRC specifications. The simulation-based validations derived from our software platform with OMNeT++, Veins and SUMO in realistic traffic environments are supplied to evaluate the proposed scheme. We expect our research could provide references for future more substantial revision of DSRC standardization for CCN-based V2V communication.

In the context of Cyber-Physical System (CPS), analyzing the real world data accumulated in cyberspace would improve the efficiency and productivity of various social systems. Towards establishing data-driven society, it is desired to share data safely and smoothly among multiple services. In this paper, we propose a scheme that services authenticate users using information registered on a blockchain. We show that the proposed scheme has resistance to tampering and a spoofing attack.

System administrators and security officials of an organization need to deal with vulnerable IT assets, especially those with severe vulnerabilities, to minimize the risk of these vulnerabilities being exploited. The Common Vulnerability Scoring System (CVSS) can be used as a means to calculate the severity score of vulnerabilities, but it currently requires human operators to choose input values. A word-level Convolutional Neural Network (CNN) has been proposed to estimate the input parameters of CVSS and derive the severity score of vulnerability notes, but its accuracy needs to be improved further. In this paper, we propose a character-level CNN for estimating the severity scores. Experiments show that the proposed scheme outperforms conventional one in terms of accuracy and how errors occur.

Epidemic cyber incidents are caused by malicious websites using exploit kits. The exploit kit facilitate attackers to perform the drive-by download (DBD) attack. However, it is reported that malicious websites using an exploit kit have similarity in their website structure (WS)-trees. Hence, malicious website identification techniques leveraging WS-trees have been studied, where the WS-trees can be estimated from HTTP traffic data. Nevertheless, the defensive component of the exploit kit prevents us from capturing the WS-tree perfectly. This paper shows, hence, a new WS-tree construction procedure by using the fact that a DBD attack happens in a certain duration. This paper proposes, moreover, a new malicious website identification technique by clustering the WS-tree of the exploit kits. Experiment results assuming the D3M dataset verify that the proposed technique identifies exploit kits with a reasonable accuracy even when HTTP traffic from the malicious sites are partially lost.

New good convolutional codes with optimal free distance are tabulated for the number of memories M 22 and rate R=1/2, which were selected based on the criterion of minimizing the decoding error rate and bit error rate. Furthermore, for R=1/3, 1/4 and M 13, we give the new good codes and make clear the existance of the codes with minimum free distance which achieve to Heller's upper bound for M 16.

The proliferation of coronavirus disease (COVID-19) has prompted changes in business models. To ensure a successful transition to non-face-to-face and electronic communication, the authenticity of data and the trustworthiness of communication partners are essential. Trust services provide a mechanism for preventing data falsification and spoofing. To develop a trust service, the characteristics of the service and the scope of its use need to be determined, and the relevant legal systems must be investigated. Preparing a document to meet trust service provider requirements may incur significant expenses. This study focuses on electronic signatures, proposes criteria for classification, classifies actual documents based on these criteria, and opens a discussion. A case study illustrates how trusted service providers search a document highlighting areas that require approval. The classification table in this paper may prove advantageous at the outset when business decisions are uncertain, and there is no clear starting point.

A method is presented for determining the minimum weight of cyclic codes. It is a probabilistic algorithm. This algorithm is used to find, the minimum weight of codes far too large to be treated by any known algorithm. It is based on a probabilistic algorithm for determining the minimum weight of linear code by Jeffrey S. Leon. By using this method, the minimum weight of cyclic codes is computed efficiently.

Cyber attacks targeting specific victims use multiple intrusion routes and various attack methods. In order to combat such diversified cyber attacks, Threat Intelligence is attracting attention. Attack activities, vulnerability information and other threat information are gathered, analyzed and organized in threat intelligence and it enables organizations to understand their risks. Integrated analysis of the threat information is needed to compose the threat intelligence. Threat information can be found in incident reports published by security vendors. However, it is difficult to analyze and compare their reports because they are described in various formats defined by each vendor. Therefore, in this paper, we apply a modeling framework for analyzing and deriving the relevance of the reports from the views of similarity and relation between the models. This paper presents the procedures of modeling incident information described in the reports. Moreover, as case studies, we apply the modeling method to some actual incident reports and compare their models.

TPM-embedded devices can be used as authentication tokens by issuing certificates to signing keys generated by TPM. TPM generates Attestation Identity Key (AIK) and Binding Key (BK) that are RSA keys. AIK is used to identify TPM. BK is used to encrypt data so that specific TPM can decrypt it. TPM can use for device authentication by linking a SSL client certificate to TPM. This paper proposes a method of an AIK certificate issuance with OpenID and a method of the SSL client certificate issuance to specific TPM using AIK and BK. In addition, the paper shows how to implement device authentication system using the SSL client certificate related to TPM.