Biblio

Filters: Author is Zhang, Yiwei  [Clear All Filters]
2023-04-28
Yang, Hongna, Zhang, Yiwei.  2022.  On an extremal problem of regular graphs related to fractional repetition codes. 2022 IEEE International Symposium on Information Theory (ISIT). :1566–1571.
Fractional repetition (FR) codes are a special family of regenerating codes with the repair-by-transfer property. The constructions of FR codes are naturally related to combinatorial designs, graphs, and hypergraphs. Given the file size of an FR code, it is desirable to determine the minimum number of storage nodes needed. The problem is related to an extremal graph theory problem, which asks for the minimum number of vertices of an α-regular graph such that any subgraph with k vertices has at most δ edges. In this paper, we present a class of regular graphs for this problem to give the bounds for the minimum number of storage nodes for the FR codes.
ISSN: 2157-8117
2022-12-01
Zhao, Jian, Lin, Zexuan, Huang, Xiaoxiao, Zhang, Yiwei, Xiang, Shaohua.  2020.  TrustCA: Achieving Certificate Transparency Through Smart Contract in Blockchain Platforms. 2020 International Conference on High Performance Big Data and Intelligent Systems (HPBD&IS). :1–6.
Certificate Authorities (CAs) are important components for digital certificate issuances in Public Key Infrastructure(PKI). However, current CAs have some intrinsic weaknesses due to the CA-centric implementation. And when browser and operating system vendors contain a CA in the software, they place complete trust in the CA. In this paper, we utilize natural characteristics of tamper-proof and transparency of smart contracts in blockchain platforms to design an independent entity, named the CA proxy, to manage life cycle of digital certificates. This management will achieve the certificate transparency. We propose a new system architecture easy to integrate the CA proxy with current CAs through applying the blockchain oracle service. In this architecture, the CA proxy, CAs, and even professional identity verification parties can accomplish life cycle management of certificates, signature of certificates, identity verification for certificates correspondingly. The achievement of the certificate transparency through life cycle management of digital certificates in blockchain platforms, when compared with traditional CAs, solves traditional CAs' trust model weaknesses and improve the security.
2020-10-16
Zhang, Yiwei, Deng, Sanhong, Zhang, Yue, Kong, Jia.  2019.  Research on Government Information Sharing Model Using Blockchain Technology. 2019 10th International Conference on Information Technology in Medicine and Education (ITME). :726—729.

Research Purpose: The distributed, traceable and security of blockchain technology are applicable to the construction of new government information resource models, which could eliminate the barn effect and trust in government information sharing, as well as promoting the transformation of government affairs from management to service, it is also of great significance to the sharing of government information and construction of service-oriented e-government. Propose Methods: By analyzing the current problems of government information sharing, combined with literature research, this paper proposes the theoretical framework and advantages of blockchain technology applied to government information management and sharing, expounds the blockchain-based solution, it also constructs a government information sharing model based on blockchain, and gives implementation strategies at the technical and management levels. Results and Conclusion: The government information sharing model based on the blockchain solution and the transparency of government information can be used as a research framework for information interaction analysis between the government and users. It can also promote the construction and development of information sharing for Chinese government, as well as providing unified information sharing solution at the departmental and regional levels for e-government.

2019-02-08
Zhang, Yiwei, Zhang, Weiming, Chen, Kejiang, Liu, Jiayang, Liu, Yujia, Yu, Nenghai.  2018.  Adversarial Examples Against Deep Neural Network Based Steganalysis. Proceedings of the 6th ACM Workshop on Information Hiding and Multimedia Security. :67-72.

Deep neural network based steganalysis has developed rapidly in recent years, which poses a challenge to the security of steganography. However, there is no steganography method that can effectively resist the neural networks for steganalysis at present. In this paper, we propose a new strategy that constructs enhanced covers against neural networks with the technique of adversarial examples. The enhanced covers and their corresponding stegos are most likely to be judged as covers by the networks. Besides, we use both deep neural network based steganalysis and high-dimensional feature classifiers to evaluate the performance of steganography and propose a new comprehensive security criterion. We also make a tradeoff between the two analysis systems and improve the comprehensive security. The effectiveness of the proposed scheme is verified with the evidence obtained from the experiments on the BOSSbase using the steganography algorithm of WOW and popular steganalyzers with rich models and three state-of-the-art neural networks.