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New Advance in Electronic Information Security

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: closed (30 September 2023) | Viewed by 4786

Special Issue Editor


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Guest Editor
School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
Interests: electronic security; side channel analysis; intelligent security
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the development of Internet technology and electronic technology, new products, new industries, and new systems in the field of electronic information have sprung up like mushrooms, changing people's lives and working methods. At the same time, the importance of information security in electronic information technology has become increasingly prominent.

Therefore, this Special Issue is intended for the presentation of new ideas and experimental results in the field of electronic information security from design, service, and theory to its practical use. 

Areas relevant to electronic information security include but are not limited to electromagnetic security, electronic system design and application, computation and data-intensive applications of electronic information security, novel concurrent algorithms and applications, large-scale computational science in security, artificial intelligence, machine learning, deep learning, and the processing of software and hardware, scientific experiments, sensor networks, medical instruments, and other sources of information security. Computer architecture, integrated circuits, distributed systems, and energy-aware computing are also topics of interest. 

This Special Issue will publish high-quality, original research papers, in the overlapping fields of:

  • Security design of electronic information systems;
  • Information network and social security;
  • Electromagnetic radiation information security;
  • Aerospace electromagnetic safety;
  • Side channel attack and side channel analysis;
  • E-commerce security;
  • Security strategy;
  • Information security organization;
  • Human resources security;
  • Physical and environmental security;
  • Communication and operational security;
  • Access control security;
  • System acquisition, development, and maintenance security;
  • Information security incident management;
  • Business continuity management.

Prof. Dr. Hongxin Zhang
Guest Editor

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. Applied Sciences is an international peer-reviewed open access semimonthly 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

  • electronic security
  • information security
  • side channel analysis
  • physical and environmental security
  • electromagnetic radiation information security
  • security strategy

Published Papers (4 papers)

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Research

17 pages, 1887 KiB  
Article
A Secret Key Classification Framework of Symmetric Encryption Algorithm Based on Deep Transfer Learning
by Xiaotong Cui, Hongxin Zhang, Xing Fang, Yuanzhen Wang, Danzhi Wang, Fan Fan and Lei Shu
Appl. Sci. 2023, 13(21), 12025; https://doi.org/10.3390/app132112025 - 3 Nov 2023
Cited by 1 | Viewed by 990
Abstract
The leakage signals, including electromagnetic, energy, time, and temperature, generated during the operation of password devices contain highly correlated key information, which leads to security vulnerabilities. In traditional encryption algorithms, the length of the key greatly affects the upper limit of its security [...] Read more.
The leakage signals, including electromagnetic, energy, time, and temperature, generated during the operation of password devices contain highly correlated key information, which leads to security vulnerabilities. In traditional encryption algorithms, the length of the key greatly affects the upper limit of its security against cracking. Regarding side-channel attacks on long-key algorithms, traditional template attack methods characterize the energy traces using multivariate Gaussian distribution during the template construction phase. The exhaustive key-guessing process is expected to consume a significant amount of time and computational resources. Therefore, to analyze the effectiveness of obtaining key values from the side information of password devices, we propose an innovative attack method based on a divide-and-conquer logical structure, targeting semi-bytes. We construct a collection of key classification submodules with symmetric correlations. By integrating a differential network model for byte-block sets and an end-to-end direct attack method, we form a holistic symmetric decision framework and propose a key classification structure based on deep transfer learning. This structure consists of three main parts: side information data acquisition, analysis of key-value effectiveness, and determination of attack positions. It employs multiple parallel symmetric subnetworks, effectively improving attack efficiency and reducing the key enumeration range. Experimental results show that the optimal attack accuracy of the network model can reach 91%, with an average attack accuracy of 78%. It overcomes overfitting issues under small sample dataset conditions. Full article
(This article belongs to the Special Issue New Advance in Electronic Information Security)
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20 pages, 2875 KiB  
Article
Technique for Searching Data in a Cryptographically Protected SQL Database
by Vitalii Yesin, Mikolaj Karpinski, Maryna Yesina, Vladyslav Vilihura, Ruslan Kozak and Ruslan Shevchuk
Appl. Sci. 2023, 13(20), 11525; https://doi.org/10.3390/app132011525 - 20 Oct 2023
Viewed by 1047
Abstract
The growing popularity of data outsourcing to third-party cloud servers has a downside, related to the serious concerns of data owners about their security due to possible leakage. The desire to reduce the risk of loss of data confidentiality has become a motivating [...] Read more.
The growing popularity of data outsourcing to third-party cloud servers has a downside, related to the serious concerns of data owners about their security due to possible leakage. The desire to reduce the risk of loss of data confidentiality has become a motivating start to developing mechanisms that provide the ability to effectively use encryption to protect data. However, the use of traditional encryption methods faces a problem. Namely, traditional encryption, by making it impossible for insiders and outsiders to access data without knowing the keys, excludes the possibility of searching. This paper presents a solution that provides a strong level of confidentiality when searching, inserting, modifying, and deleting the required sensitive data in a remote database whose data are encrypted. The proposed SQL query processing technique allows the DBMS server to perform search functions over encrypted data in the same way as in an unencrypted database. This is achieved through the organization of automatic decryption by specially developed secure software of the corresponding data required for search, without the possibility of viewing these data itself. At that, we guarantee the integrity of the stored procedures used and special tables that store encrypted modules of special software and decryption keys, the relevance and completeness of the results returned to the application. The results of the analysis of the feasibility and effectiveness of the proposed solution show that the proper privacy of the stored data can be achieved at a reasonable overhead. Full article
(This article belongs to the Special Issue New Advance in Electronic Information Security)
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15 pages, 2564 KiB  
Article
Locating Infectious Sources Using Bluetooth System of Smart Devices
by Hongli Qin, Tao Guo and Yunan Han
Appl. Sci. 2023, 13(12), 7218; https://doi.org/10.3390/app13127218 - 16 Jun 2023
Viewed by 1012
Abstract
Infectious diseases, such as COVID-19, may have a significant impact on human daily life and social activities. One effective method to prevent and control the spread of such diseases is to accurately locate the sources of infection and limit the possible exposure to [...] Read more.
Infectious diseases, such as COVID-19, may have a significant impact on human daily life and social activities. One effective method to prevent and control the spread of such diseases is to accurately locate the sources of infection and limit the possible exposure to the virus. This paper presents a method, system, big data storage and analysis to control the infection based on Bluetooth technology. GPS and Bluetooth positioning are combined to track the movement trajectory of each person with a smart device, locally store the location information and close contacts, as well as periodically update it on the cloud platform. Based on the related algorithms of big data, this method can provide personal and regional risk levels, providing an alarm function which can be triggered by being close enough to a high-risk area or if the infected person’s risk level is greater than the set threshold within the Bluetooth interconnection range. The system can provide a wealth of data on the location of infection sources and close contacts, offering valuable technical support for rapid and efficient epidemic prevention and control. Full article
(This article belongs to the Special Issue New Advance in Electronic Information Security)
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14 pages, 2418 KiB  
Article
Side-Channel Power Analysis Based on SA-SVM
by Ying Zhang, Pengfei He, Han Gan, Hongxin Zhang and Pengfei Fan
Appl. Sci. 2023, 13(9), 5671; https://doi.org/10.3390/app13095671 - 4 May 2023
Viewed by 1261
Abstract
Support vector machines (SVMs) have been widely used in side-channel power analysis. The selection of the penalty factor and kernel parameter heavily influences how well support vector machines work. Setting reasonable SVM hyperparameters is a key issue in side-channel power analysis. The novel [...] Read more.
Support vector machines (SVMs) have been widely used in side-channel power analysis. The selection of the penalty factor and kernel parameter heavily influences how well support vector machines work. Setting reasonable SVM hyperparameters is a key issue in side-channel power analysis. The novel side-channel power analysis method SA-SVM, which combines simulated annealing (SA) and support vector machines (SVMs) to analyze the power traces and crack the key, is proposed in this paper as a solution to this issue. This method differs from other approaches in that it integrates SA and SVMs, enabling us to more effectively explore the search space and produce superior results. In this paper, we conducted experiments on SA-SVM and SVM models from three different aspects: the selection of kernel functions, the number of parameters, and the number of eigenvalues. To compare our results with previous research, we performed experimental evaluations on open datasets. The results indicate that, compared with the SVM model, the SA-SVM model improved the accuracy by 0.25% to 3.25% and reduced the required time by 39.96% to 98.02% when the point of interest was 53, recovering the key using only three power traces. The SA-SVM model outperforms existing methods in terms of accuracy and computation time. Full article
(This article belongs to the Special Issue New Advance in Electronic Information Security)
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