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Symmetry
Special Issues
Symmetry and Asymmetry in Securing Data Sharing
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Symmetry and Asymmetry in Securing Data Sharing

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".

Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 9990

Special Issue Editors

Dr. Zhe Xia

E-Mail Website
Guest Editor
School of Computer Science, Wuhan University of Technology, Wuhan 430070, China
Interests: cryptographic protocols; provable security; electronic voting
Special Issues, Collections and Topics in MDPI journals
Dr. Yanwei Zhou

E-Mail Website
Guest Editor
School of Computer Science, Shaanxi Normal University, Xi’an 710062, China
Interests: cryptography; information security
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Yining Liu

E-Mail Website
Guest Editor
School of Computer and Information Security, Guilin University of Electronic Technology, Guilin 541004, China
Interests: information security and cryptography; privacy preserving protocols

Special Issue Information

Dear Colleagues,

Data sharing can promote information exchange and help people to gain better insights into the world around us. It has become an increasingly important topic in both academia and the business world. For example, on November 25th 2021, the Shanghai Data Exchange opened for trading, aiming to find new economic growth in the big data era. However, security mechanisms are indispensable for guaranteeing effective data sharing, e.g., secure transmission, fine grained access control, data authentication, privacy preserving computations, etc.

This Special Issue aims to publish a collection of papers on recent developments in data sharing using symmetric and asymmetric techniques. The topics of interest for publication include, but are not limited to, symmetric and asymmetric ciphers, privacy preserving, verifiable computations, authenticated key exchanges, database security, big data security, cloud computing security, security in social networks, digital forensics, and security architectures.

All interested researchers are kindly invited to contribute to this Special Issue. All submitted papers should be within the general scope of Symmetry.

Dr. Zhe Xia
Dr. Yanwei Zhou
Prof. Dr. Yining Liu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • symmetric and asymmetric ciphers
  • fine grained access control
  • authenticated key exchange
  • privacy preserving computations
  • verifiable computations
  • adversary machine learning
  • database security
  • secure data deletion
  • big data security
  • cloud computing security
  • security in social networks
  • security in cyber physical systems
  • digital forensics
  • operation system security
  • software security
  • security architecture

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Published Papers (4 papers)

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Research

25 pages, 3043 KiB  
Article
A Novel Integrated Method for Harmonic Suppression and Reactive Power Compensation in Distribution Network
by Yifei Wang, Kaiyang Yin, Huikang Liu and Youxin Yuan
Symmetry 2022, 14(7), 1347; https://doi.org/10.3390/sym14071347 - 29 Jun 2022
Cited by 6 | Viewed by 1832
Abstract
Aiming at the serious harmonic pollution and the low power factor in the distribution network of industrial enterprises, this paper develops an integrated method for harmonic suppression and reactive power compensation suitable for the distribution network of industrial enterprises. The integrated method realizes [...] Read more.
Aiming at the serious harmonic pollution and the low power factor in the distribution network of industrial enterprises, this paper develops an integrated method for harmonic suppression and reactive power compensation suitable for the distribution network of industrial enterprises. The integrated method realizes the dual functions of harmonic filtering and reactive power compensation, and filters out the harmonic current to get a symmetrical current waveform while ensuring safe operation of the power compensator. In addition, it solves the problems of high harmonic content, small power factor in the distribution network, and device burnout caused by direct input of reactive power compensator. The main contributions of this paper are as follows: (1) According to the demand for the integration of harmonic suppression and reactive power compensation, the steps of integrated method for harmonic suppression and reactive power compensationare proposed, and then the methods for harmonic filtering and reactive power compensation are investigated; (2) a method for designing the capacity of a filter capacitor and the rated parameter of an electromagnetic coupling reactance converter is proposed, and an optimization simulation system is constructed to design the parameters of the filter; (3) a simulation system is developed, followed by parameter design and simulation analysis of harmonic filtering subsystem (HFSS), reactive power compensation subsystem (RPCSS) and the integrated system of harmonic suppression and reactive power compensation. Simulation results verify that the HFSS is put into operation first and then switched off later to ensure the normal operation of other equipment in the distribution network. After the treatment, the power factor, harmonic current content and total distortion rate all meet the national standards. The integrated method can dynamically track harmonics and reactive power changes, filter out harmonics, improve power factor and the symmetry level of the power source, and ensure the normal operation of other equipment in the distribution network. The research results lay a certain theoretical and technical foundation for the harmonic filtering and reactive power compensation theory, technology and its device innovation to achieve effective suppression of power harmonics and reactive power compensation. Full article
(This article belongs to the Special Issue Symmetry and Asymmetry in Securing Data Sharing)
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17 pages, 837 KiB  
Article
TPM-Based Conditional Privacy-Preserving Authentication Protocol in VANETs
by Mingwu Zhang, Boyao Zhu, Yumei Li and Yuntao Wang
Symmetry 2022, 14(6), 1123; https://doi.org/10.3390/sym14061123 - 30 May 2022
Cited by 8 | Viewed by 2375
Abstract
With the establishment of intelligent transportation systems (ITS), research on vehicle ad-hoc networks (VANETs) has played an irreplaceable role in improving traffic safety and efficiency. However, because the deployment of devices based on the IoV is in an open field, the IoV is [...] Read more.
With the establishment of intelligent transportation systems (ITS), research on vehicle ad-hoc networks (VANETs) has played an irreplaceable role in improving traffic safety and efficiency. However, because the deployment of devices based on the IoV is in an open field, the IoV is extremely vulnerable to various attacks without security protection, e.g., remote intrusion, control, trajectory tracking, etc. In order to avoid the above-mentioned attacks and resource abuses, provably secure cryptography primitives are generally considered to guarantee and realize the security of VANETs. This paper proposes a TPM-based conditional privacy-preserving authentication protocol (T-CPPA) which achieves both the integrity and the authenticity of the message/instruct content. The vehicle’s privacy is protected by embedding the system master private key into the trust platform module (TPM) which is responsible for generating pseudonyms and signature keys. The authenticity of message content is ensured by calculating message similarity in a cluster-based model. We give the concrete construction of our T-CPPA authentication scheme in symmetric bilinear groups and design a batch validation algorithm to improve efficiency. Security analysis shows that our scheme can resist various traditional attacks in VANETs, and the experimental results indicate that our scheme is efficient and useful in practice. Full article
(This article belongs to the Special Issue Symmetry and Asymmetry in Securing Data Sharing)
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15 pages, 582 KiB  
Article
Privacy Preserving Data Aggregation for Smart Grid with User Anonymity and Designated Recipients
by Liang Wu, Wenzheng Zhang and Wei Zhao
Symmetry 2022, 14(5), 847; https://doi.org/10.3390/sym14050847 - 19 Apr 2022
Cited by 7 | Viewed by 2538
Abstract
Smart grids integrate modern Internet of Things technologies with the traditional grid systems, aiming to achieve effective and reliable electricity distribution as well as promote clean energy development. Nowadays, it is an indispensable infrastructure for smart homes, wisdom medical, intelligent transportation, and various [...] Read more.
Smart grids integrate modern Internet of Things technologies with the traditional grid systems, aiming to achieve effective and reliable electricity distribution as well as promote clean energy development. Nowadays, it is an indispensable infrastructure for smart homes, wisdom medical, intelligent transportation, and various other services. However, when smart meters transmit users’ power consumption data to the control center, sensitive information may be leaked or tampered. Moreover, distributed architecture, fine-grained access control, and user anonymity are also desirable in real-world applications. In this paper, we propose a privacy-preserving data aggregation scheme for a smart grid with user anonymity and designated recipients. Smart meters collect users’ power consumption data, encrypt it using homomorphic re-encryption, and then transmit the ciphertexts anonymously. Afterward, proxies re-encrypt the aggregated data in a distributed fashion so that only the designated recipients can decrypt it. Therefore, our proposed scheme provides a more secure and flexible solution for privacy-preserving data aggregation in smart grids. Security analyses prove that our scheme achieves all the above-mentioned security requirements, and efficiency analyses demonstrate that it is efficient and suitable for real-world applications. Full article
(This article belongs to the Special Issue Symmetry and Asymmetry in Securing Data Sharing)
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18 pages, 1052 KiB  
Article
A Distributed and Privacy-Preserving Random Forest Evaluation Scheme with Fine Grained Access Control
by Yang Zhou, Hua Shen and Mingwu Zhang
Symmetry 2022, 14(2), 415; https://doi.org/10.3390/sym14020415 - 19 Feb 2022
Cited by 2 | Viewed by 2307
Abstract
Random forest is a simple and effective model for ensemble learning with wide potential applications. Implementation of random forest evaluations while preserving privacy for the source data is demanding but also challenging. In this paper, we propose a practical and fault-tolerant privacy-preserving random [...] Read more.
Random forest is a simple and effective model for ensemble learning with wide potential applications. Implementation of random forest evaluations while preserving privacy for the source data is demanding but also challenging. In this paper, we propose a practical and fault-tolerant privacy-preserving random forest evaluation scheme based on asymmetric encryption. The user can use asymmetric encryption to encrypt the data outsourced to the cloud platform and specify who can access the final evaluation results. After receiving the encrypted inputs from the user, the cloud platform evaluates via a random forest model and outputs the aggregated results where only the designated recipient can decrypt them. Threat analyses prove that the proposed scheme achieves the desirable security properties, such as correctness, confidentiality and robustness. Moreover, efficiency analyses demonstrate that the scheme is practical for real-world applications. Full article
(This article belongs to the Special Issue Symmetry and Asymmetry in Securing Data Sharing)
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