Trends in Information Systems and Security

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

Deadline for manuscript submissions: 20 November 2025 | Viewed by 1335

Special Issue Editor

Special Issue Information

Dear Colleagues,

We invite researchers, practitioners, and industry experts to submit their original research and innovative solutions for this Special Issue titled "Trends in Information Systems and Security". This Special Issue aims to innovative research in the field of information systems and security.  This Special Issue seeks to explore the latest advancements, emerging challenges, and opportunities within the dynamic field of information systems and security. Potential topics include but are not limited to the following research areas in information systems and security:

  • Artificial intelligence;
  • Machine learning;
  • Blockchain;
  • Internet of Things;
  • Cloud computing;
  • Big data analytics.

Dr. Namgi Kim
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. 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

  • information system
  • information security
  • information network
  • cyber security
  • internet of things

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (4 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

28 pages, 521 KiB  
Article
Provably Secure and Privacy-Preserving Authentication Scheme for IoT-Based Smart Farm Monitoring Environment
by Hyeonjung Jang, Jihye Choi, Seunghwan Son, Deokkyu Kwon and Youngho Park
Electronics 2025, 14(14), 2783; https://doi.org/10.3390/electronics14142783 - 10 Jul 2025
Viewed by 194
Abstract
Smart farming is an agricultural technology integrating advanced technology such as cloud computing, Artificial Intelligence (AI), the Internet of Things (IoT), and robots into traditional farming. Smart farming can help farmers by increasing agricultural production and managing resources efficiently. However, malicious attackers can [...] Read more.
Smart farming is an agricultural technology integrating advanced technology such as cloud computing, Artificial Intelligence (AI), the Internet of Things (IoT), and robots into traditional farming. Smart farming can help farmers by increasing agricultural production and managing resources efficiently. However, malicious attackers can attempt security attacks because communication in smart farming is conducted via public channels. Therefore, an authentication scheme is necessary to ensure security in smart farming. In 2024, Rahaman et al. proposed a privacy-centric authentication scheme for smart farm monitoring. However, we demonstrated that their scheme is vulnerable to stolen mobile device, impersonation, and ephemeral secret leakage attacks. This paper suggests a secure and privacy-preserving scheme to resolve the security defects of the scheme proposed by Rahaman et al. We also verified the security of our scheme through “the Burrows-Abadi-Needham (BAN) logic”, “Real-or-Random (RoR) model”, and “Automated Validation of Internet Security Protocols and Application (AVISPA) tool”. Furthermore, a performance analysis of the proposed scheme compared with related studies was conducted. The comparison result proves that our scheme was more efficient and secure than related studies in the smart farming environment. Full article
(This article belongs to the Special Issue Trends in Information Systems and Security)
Show Figures

Figure 1

24 pages, 1061 KiB  
Article
High- and Low-Rank Optimization of SNOVA on ARMv8: From High-Security Applications to IoT Efficiency
by Minwoo Lee, Minjoo Sim, Siwoo Eum and Hwajeong Seo
Electronics 2025, 14(13), 2696; https://doi.org/10.3390/electronics14132696 - 3 Jul 2025
Viewed by 305
Abstract
The increasing threat of quantum computing to traditional cryptographic systems has prompted intense research into post-quantum schemes. Despite SNOVA’s potential for lightweight and secure digital signatures, its performance on embedded devices (e.g., ARMv8 platforms) remains underexplored. This research addresses this gap by presenting [...] Read more.
The increasing threat of quantum computing to traditional cryptographic systems has prompted intense research into post-quantum schemes. Despite SNOVA’s potential for lightweight and secure digital signatures, its performance on embedded devices (e.g., ARMv8 platforms) remains underexplored. This research addresses this gap by presenting the optimal SNOVA implementations on embedded devices. This paper presents a performance-optimized implementation of the SNOVA post-quantum digital signature scheme on ARMv8 processors. SNOVA is a multivariate cryptographic algorithm under consideration in the NIST’s additional signature standardization. Our work targets the performance bottlenecks in the SNOVA scheme. Specifically, we employ matrix arithmetic over GF16 and AES-CTR-based pseudorandom number generation by exploiting the NEON SIMD extension and tailoring the computations to the matrix rank. At a low level, we develop rank-specific SIMD kernels for addition and multiplication. Rank 4 matrices (i.e., 16 bytes) are handled using fully vectorized instructions that align with 128-bit-wise registers, while rank 2 matrices (i.e., 4 bytes) are processed in batches of four to ensure full SIMD occupancy. At the high level, core routines such as key generation and signature evaluation are structurally refactored to provide aligned memory layouts for batched execution. This joint optimization across algorithmic layers reduces the overhead and enables seamless hardware acceleration. The resulting implementation supports 12 SNOVA parameter sets and demonstrates substantial efficiency improvements compared to the reference baseline. These results highlight that fine-grained SIMD adaptation is essential for the efficient deployment of multivariate cryptography on modern embedded platforms. Full article
(This article belongs to the Special Issue Trends in Information Systems and Security)
Show Figures

Figure 1

37 pages, 3962 KiB  
Article
Rebooting Procurement Processes: Leveraging the Synergy of RPA and BPM for Optimized Efficiency
by Simão Santos, Vitor Santos and Henrique S. Mamede
Electronics 2025, 14(13), 2694; https://doi.org/10.3390/electronics14132694 - 3 Jul 2025
Viewed by 271
Abstract
Efficient procurement processes are pivotal for strategic performance in digital organizations, requiring continuous refinement driven by automation, integration, and performance monitoring. This research investigates and demonstrates the potential for synergies between RPA and BPM in procurement processes. The primary objective is to analyze [...] Read more.
Efficient procurement processes are pivotal for strategic performance in digital organizations, requiring continuous refinement driven by automation, integration, and performance monitoring. This research investigates and demonstrates the potential for synergies between RPA and BPM in procurement processes. The primary objective is to analyze and evaluate a manual procurement-intensive process to enhance efficiency, reduce time-consuming interventions, and ultimately diminish costs and cycle time. Employing Design Science Research Methodology, this research yields a practical artifact designed to streamline procurement processes. An artifact was created using BPM methods and RPA tools. The RPA was developed after applying BPM Redesign Heuristics to the current process. A mixed-methods approach was employed for its evaluation, combining quantitative analysis on cycle time reduction with a qualitative Confirmatory Focus Group of department experts. The analysis revealed that the synergy between BPM and RPAs can leverage procurement processes, decreasing cycle times and workload on intensive manual tasks and allowing employees time to focus on other functions. This research contributes valuable insights for organizations seeking to harness automation technologies for enhanced procurement operations, with the findings suggesting promising enduring benefits for both efficiency and accuracy in the procurement lifecycle. Full article
(This article belongs to the Special Issue Trends in Information Systems and Security)
Show Figures

Figure 1

12 pages, 667 KiB  
Article
Non-IID Degree Aware Adaptive Federated Learning Procedure Selection Scheme for Edge-Enabled IoT Network
by Sanghui Lee and Jaewook Lee
Electronics 2025, 14(12), 2331; https://doi.org/10.3390/electronics14122331 - 7 Jun 2025
Viewed by 324
Abstract
Due to the independent, identically distributed (non-IID) nature of IoT device data, the traditional federated learning (FL) procedure, where IoT devices train the deep model in parallel, suffers from a degradation in learning accuracy. To mitigate this problem, a sequential FL procedure has [...] Read more.
Due to the independent, identically distributed (non-IID) nature of IoT device data, the traditional federated learning (FL) procedure, where IoT devices train the deep model in parallel, suffers from a degradation in learning accuracy. To mitigate this problem, a sequential FL procedure has been proposed, in which IoT devices train the deep model in a serialized manner via a parameter server. However, this approach experiences a longer convergence time due to the lack of parallelism. In this paper, we propose an adaptive FL procedure selection (AFLS) scheme that selects an appropriate FL scheme, either the traditional or the sequential FL procedures, based on the degree of non-IID among IoT devices to achieve both the required learning accuracy and low convergence time. To further reduce the convergence time of the sequential FL procedure, we also introduce a device-to-device (D2D)-based sequential FL procedure. The evaluation results demonstrate that AFLS can reduce convergence time by up to 16% compared to the sequential FL procedure and improve learning accuracy by up to 6∼26% compared to the traditional FL procedure. Full article
(This article belongs to the Special Issue Trends in Information Systems and Security)
Show Figures

Figure 1

Back to TopTop