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Electronics
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Recent Advances in Computer Security and Online Privacy
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Recent Advances in Computer Security and Online Privacy

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".

Deadline for manuscript submissions: closed (15 October 2023) | Viewed by 3444

Special Issue Editors

Dr. Manjit Kaur

E-Mail Website
Guest Editor
School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju 61005, Korea
Interests: information security; blockchain; machine learning; deep learning; computer vision
Special Issues, Collections and Topics in MDPI journals
Dr. Simar Preet Singh

E-Mail Website
Guest Editor
School of Computer Science Engineering and Technology (SCSET), Bennett University, Greater Noida 201310, Uttar Pradesh, India
Interests: cloud computing; fog computing; machine learning; internet of things (IoT)
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Heung-No Lee

E-Mail Website
Guest Editor
School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju 61005, Republic of Korea
Interests: intelligent sensors; smart city projects
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the digital world of numerous technologies, continuous data flows on the Internet. Even in a small fraction of a second, this flow of data on the Internet is tremendously large. This data flow comprises sensitive information, non-sensitive information, and confidential information as well as non-confidential information. To refine the data and for fast processing on the ongoing data over the Internet, numerous technologies such as artificial intelligence, machine learning, deep learning, cloud computing, edge computing, osmotic computing, the Internet of Things (IoT), etc., have rapidly emerged. Computer security and online privacy play a vital role in all technologies. Computer security is enhancing the assurance of access to the data in the digital mode only by the authorized person. Online privacy is to protect the data during transmission from an unauthenticated user. To achieve computer security and online privacy, multiple technologies such as blockchain along with multiple algorithms and approaches such as cryptographic algorithms, verifiable random functions, etc., are being widely considered. Securing blockchain by using verifiable random functions is the best approach considering emerging technologies in present times.  

Many different solutions in computer security and online privacy have been proposed to address the issues and challenges in emerging technologies and to overcome the battle of networks, optimization in distributed environments, distributed learning, and other aspects using numerous technologies. However, they are not properly designed to address the emerging needs of the society. Many service parameters remain uncovered, which need to be focused on for the enhancement of the quality of service such as secure migration of data and the issues involved in data migration, security issues arising during the allocation of resources and their scheduling, and issues of authentication and authorization in accessing information in online mode. Therefore, the use of computer security and online privacy for emerging technologies is the key factor. We solicit original contributions on novel computer security and online privacy approaches and their recent trends, recent advances related to security and privacy, the use of blockchain, and applications of verifiable random functions for effective data transfer in emerging technologies. To meet the requirements of present technologies, blockchain and verifiable random functions should be an efficient and safe way to achieve computer security and online privacy over the network. This Special Issue seeks to bring researchers, scholars, and participators towards computer security and online privacy for emerging technologies as well as to address challenges and present effective solutions and recent advancements in the direction of computer security and online privacy considering the growing technological era.

Dr. Manjit Kaur
Dr. Simar Preet Singh
Prof. Dr. Heung-No Lee
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. Electronics 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

  • computer security
  • online privacy
  • blockchain
  • verifiable random functions
  • authentication
  • authorization

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Published Papers (2 papers)

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Research

22 pages, 2166 KiB  
Article
Design Methodology and Metrics for Robust and Highly Qualified Security Modules in Trusted Environments
by Luca Crocetti, Pietro Nannipieri, Stefano Di Matteo and Sergio Saponara
Electronics 2023, 12(23), 4843; https://doi.org/10.3390/electronics12234843 - 30 Nov 2023
Viewed by 1098
Abstract
Cyberattacks and cybercriminal activities constitute one of the biggest threats in the modern digital era, and the frequency, efficiency, and severity of attacks have grown over the years. Designers and producers of digital systems try to counteract such issues by exploiting increasingly robust [...] Read more.
Cyberattacks and cybercriminal activities constitute one of the biggest threats in the modern digital era, and the frequency, efficiency, and severity of attacks have grown over the years. Designers and producers of digital systems try to counteract such issues by exploiting increasingly robust and advanced security mechanisms to provide secure execution environments aimed at preventing cyberattacks or, in the worst case, at containing intrusions by isolation. One of the most significative examples comes from General Purpose Processor (GPP) manufacturers such as Intel, AMD, and ARM, which in the last years adopted the integration of dedicated resources to provide Trusted Execution Environments (TEEs) or secure zones. TEEs are built layer by layer on top of an implicitly trusted component, the Root-of-Trust (RoT). Since each security chain is only as strong as its weakest link, each element involved in the construction of a TEE starting from the RoT must be bulletproof as much as possible. In this work, we revise and propose a design methodology to implement in both hardware (HW) and software (SW) highly featured and robust security blocks by highlighting the key points that designers should take care of, and the key metrics that should be used to evaluate the security level of the developed modules. We also include an analysis of the state of the art concerning RoT-based TEEs, and we illustrate a case study that documents the implementation of a cryptographic coprocessor for the secure subsystem of the Rhea GPP from the European Processor Initiative (EPI) project, according to the presented methodology. This work can be used by HW/SW security module designers as a cutting-edge guideline. Full article
(This article belongs to the Special Issue Recent Advances in Computer Security and Online Privacy)
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12 pages, 1134 KiB  
Article
Supervised Character Resemble Substitution Personality Adversarial Method
by Xiujuan Wang, Siwei Cao, Kangfeng Zheng, Xu Guo and Yutong Shi
Electronics 2023, 12(4), 869; https://doi.org/10.3390/electronics12040869 - 8 Feb 2023
Cited by 1 | Viewed by 1534
Abstract
With the development of science and computer technology, social networks are changing our daily lives. However, this leads to new, often hidden dangers in areas such as cybersecurity. Of these, the most complex and harmful is the Advanced Persistent Threat attack (APT attack). [...] Read more.
With the development of science and computer technology, social networks are changing our daily lives. However, this leads to new, often hidden dangers in areas such as cybersecurity. Of these, the most complex and harmful is the Advanced Persistent Threat attack (APT attack). The development of personality analysis and prediction technology provides the APT attack a good opportunity to infiltrate personality privacy. Malicious people can exploit existing personality classifiers to attack social texts and steal users’ personal information. Therefore, it is of high importance to hide personal privacy information in social texts. Based on the personality privacy protection technology of adversarial examples, we proposed a Supervised Character Resemble Substitution personality adversarial method (SCRS) in this paper, which hides personality information in social texts through adversarial examples to realize personality privacy protection. The adversarial examples should be capable of successfully disturbing the personality classifier while maintaining the original semantics without reducing human readability. Therefore, this paper proposes a measure index of “label contribution” to select the words that are important to the label. At the same time, in order to maintain higher readability, this paper uses character-level resemble substitution to generate adversarial examples. Experimental validation shows that our method is able to generate adversarial examples with good attack effect and high readability. Full article
(This article belongs to the Special Issue Recent Advances in Computer Security and Online Privacy)
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