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Electronics
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New Insights in Information Security and Data Privacy: Challenges and...
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New Insights in Information Security and Data Privacy: Challenges and Solutions

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: 31 January 2025 | Viewed by 1847

Special Issue Editors

Dr. Shancang Li

E-Mail Website
Guest Editor
Faulty of Engineering, Department of Civil Engineering, University of Bristol, University Walk, Clifton BS8, UK
Interests: Cyber Security; Data Privacy; Internet of Things; Artificial Intelligence
Special Issues, Collections and Topics in MDPI journals
Dr. Shanshan Zhao

E-Mail Website
Guest Editor
Engineering Modelling and Simulation (EMS) Research Group, University of the West of England, Bristol, UK
Interests: industry critical system; data protection; machine learning; AI

Special Issue Information

Dear Colleagues,

A surge in technological advancements has granted users unprecedented access to a wealth of data. While this brings numerous benefits, it also catapults cybersecurity and data privacy into the spotlight. Cutting-edge technologies such as AI, IoT, industry-critical systems, and generative AI, though offering transformative advantages, are now prime targets for cyber attackers. The landscape is evolving as cybercriminals adopt increasingly sophisticated tactics, harnessing advanced technologies to exploit vulnerabilities within information systems. This underscores the urgent need for robust cybersecurity measures to safeguard sensitive data and ensure the integrity of our interconnected digital ecosystem. The purpose of this Special Issue is to bring together the most recent research results on information security and data privacy, discuss and understand the challenges and opportunities, and find possible solutions.  The topics of interest of this Special Issue include (but are not limited to) the following:

Topics:

(1) Machine learning and AI in security;

(2) Data privacy and data quality assurance;

(3) Privacy enhancing technology;

(4) Security in smart technologies;

(5) IoT security;

(6) Cybersecurity awareness and training;

(7) Healthcare privacy;

(8) Vulnerability analysis in information system;

(9) Regulatory compliance;

(10) Advanced secure information processing.

Dr. Shancang Li
Dr. Shanshan Zhao
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

  • cyber security
  • IoT
  • AI
  • privacy preserving
  • data quality
  • incident response
  • threat intelligence

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Published Papers (2 papers)

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19 pages, 2027 KiB  
Article
T-Smade: A Two-Stage Smart Detector for Evasive Spectre Attacks Under Various Workloads
by Jiajia Jiao, Ran Wen and Yulian Li
Electronics 2024, 13(20), 4090; https://doi.org/10.3390/electronics13204090 - 17 Oct 2024
Viewed by 302
Abstract
Evasive Spectre attacks have used additional nop or memory delay instructions to make effective hardware performance counter based detectors with lower attack detection successful rate. Interestingly, the detection performance gets worse under different workloads. For example, the attack detection successful rate is only [...] Read more.
Evasive Spectre attacks have used additional nop or memory delay instructions to make effective hardware performance counter based detectors with lower attack detection successful rate. Interestingly, the detection performance gets worse under different workloads. For example, the attack detection successful rate is only 59.8% for realistic applications, while it is much lower 27.52% for memory stress test. Therefore, this paper proposes a two-stage smart detector T-Smade designed for evasive Spectre attacks (e.g., evasive Spectre nop and evasive Spectre memory) under various workloads. T-Smade uses the first-stage detector to identify the type of workloads and then selects the appropriate second-stage detector, which uses four hardware performance counter events to characterize the high cache miss rate and low branch miss rate of Spectre attacks. More importantly, the second stage detector adds one dimension of reusing cache miss rate and branch miss rate to exploit the characteristics of various workloads to detect evasive Spectre attacks effectively. Furthermore, to achieve the good generalization for more unseen evasive Spectre attacks, the proposed classification detector T-Smade is trained by the raw data of Spectre attacks and non-attacks in different workloads using simple Multi-Layer Perception models. The comprehensive results demonstrate that T-Smade makes the average attack detection successful rate of evasive Spectre nop under different workload return from 27.52% to 95.42%, and that of evasive Spectre memory from 59.8% up to 100%. Full article
(This article belongs to the Special Issue New Insights in Information Security and Data Privacy: Challenges and Solutions)
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24 pages, 313 KiB  
Systematic Review
A Comprehensive Literature Review on Volatile Memory Forensics
by Ishrag Hamid and M. M. Hafizur Rahman
Electronics 2024, 13(15), 3026; https://doi.org/10.3390/electronics13153026 - 31 Jul 2024
Viewed by 1046
Abstract
Through a systematic literature review, which is considered the most comprehensive way to analyze the field of memory forensics, this paper investigates its development through past and current methodologies, as well as future trends. This paper systematically starts with an introduction to the [...] Read more.
Through a systematic literature review, which is considered the most comprehensive way to analyze the field of memory forensics, this paper investigates its development through past and current methodologies, as well as future trends. This paper systematically starts with an introduction to the key issues and a notable agenda of the research questions. Appropriate inclusion and exclusion criteria were then developed, and a deliberate search strategy was adopted to identify primary research studies aligned with the research question. The paper goes into specific details of six different memory categories, notably volatile memory, interpreting their advantages and the tactics used to retrieve the data. A detailed comparison with existing reviews and other relevant papers is made, forming a broader and wider picture of the research. The discussion summarizes the main findings, particularly the rise of more complex and advanced cyber threats and the necessity of more effective forensic methods for their investigation. This review pinpoints the possibilities for future study with the purpose of staying ahead in the evolving technological landscape. This overview is undoubtedly an essential resource for professionals and researchers working in digital forensics. It allows them to stay competent and provides enough insight into the current trends while marking the future direction in digital forensics methodology. Full article
(This article belongs to the Special Issue New Insights in Information Security and Data Privacy: Challenges and Solutions)
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