Computer Standards & Interfaces最新文献

{"title":"An environment-aware Q-learning-based trust evaluation scheme in Underwater Acoustic Sensor Networks (UASNs)","authors":"Parisa Khoshvaght ,&nbsp;Musaed Alhussein ,&nbsp;Khursheed Aurangzeb ,&nbsp;Efat Yousefpoor ,&nbsp;Jan Lansky ,&nbsp;Mehdi Hosseinzadeh","doi":"10.1016/j.csi.2025.104087","DOIUrl":"10.1016/j.csi.2025.104087","url":null,"abstract":"<div><div>Underwater acoustic sensor networks (UASNs) have diverse applications in military and civilian domains but are vulnerable to various security threats due to their broadcast nature and challenging underwater environment. Trust mechanisms have emerged as effective solutions to enhance security and reliability in UASNs. However, existing trust models often lack efficient trust update mechanisms that can manage inevitable dynamic fluctuations in the underwater environment and various potential attacks. In this paper, an environment-aware Q-learning-based trust evaluation (EAQTE) scheme is presented in UASNs. EAQTE incorporates environmental features such as communication channel quality and node stability into the trust computation. Communication quality is assessed based on the variance in successful packet transmission probability, while node stability is measured through movement similarity. Each node collects three types of trust evidence — energy-based, data-based, and communication-based — by interacting with neighboring nodes. Energy-based evidence includes residual energy, current energy change rate, and the similarity of energy change sequences to normal patterns. Data-based evidence evaluates the consistency of collected data, and communication-based evidence considers successful and unsuccessful interactions. EAQTE uses a Q-learning algorithm with three trust states (belief, disbelief, uncertainty) to dynamically adapt trust levels. Simulation results demonstrate that EAQTE improves detection accuracy by 7.01% compared to TUMRL, ARTMM, and TMC based on simulation time. However, under attack mode switching scenarios, EAQTE’s detection accuracy is approximately 2.86% lower than TUMRL. Additionally, EAQTE reduces the false alarm rate by 19.65% relative to TUMRL when node speed varies, and by 11.8% compared to TUMRL under different node densities. Furthermore, EAQTE achieves higher energy efficiency and improves it by 5.19% over TUMRL when the percentage of compromised nodes increases, and by approximately 5.66% across varying node densities. These results indicate that EAQTE effectively balances adaptability, accuracy, and energy consumption in challenging underwater environments.</div></div>","PeriodicalId":50635,"journal":{"name":"Computer Standards & Interfaces","volume":"96 ","pages":"Article 104087"},"PeriodicalIF":3.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145415861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SPRING: Sign-then-prove ring signatures from lattices with compactness, extensibility, and efficiency","authors":"Ruiteng Zhang ,&nbsp;Pingbin Luo ,&nbsp;Qiong Huang","doi":"10.1016/j.csi.2025.104084","DOIUrl":"10.1016/j.csi.2025.104084","url":null,"abstract":"<div><div>Traditional constructions of compact ring signatures often rely on cryptographic tools like accumulators and zero-knowledge proofs, which usually depend on specific proof systems. In this work, we propose a more flexible and efficient construction of <u>ring</u> signatures based on module lattices, following the <em><u>s</u>ign-then-<u>p</u>rove</em> structure and we name it SPRING, which is derived from the extraction of core commonalities in SMILE (CRYPTO 2021). Our construction achieves two key advantages: first, it is no longer tied to any specific ZK proof system, and its modular architecture enhances both scalability and adaptability to diverse practical scenarios. For example, we explicitly demonstrate how to extend our base scheme to support accountable ring signatures—all without modifying the underlying core signature structure. Second, by combining these distilled core commonalities with optimized Gaussian sampling techniques, our construction achieves smaller signature sizes than prior works.</div></div>","PeriodicalId":50635,"journal":{"name":"Computer Standards & Interfaces","volume":"96 ","pages":"Article 104084"},"PeriodicalIF":3.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145415862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"BERE: Ensuring immutability and transparency with blockchain in real estate appraisal industry","authors":"Muruvvet Kalkan ,&nbsp;Murat Karakus","doi":"10.1016/j.csi.2025.104095","DOIUrl":"10.1016/j.csi.2025.104095","url":null,"abstract":"<div><div>Real estate appraisal plays a pivotal role in various financial transactions and regulatory processes, necessitating the assurance of unalterable and transparent Real Estate Appraisal rePorts (REA_Ps). Authorized appraisal experts employ diverse methodologies to ascertain the market value of real estate properties, contributing to critical decisions in property transactions, loans, taxation, insurance, financial reporting, and lease calculations. The standardized format and jurisdiction-compliant methodologies used in official REA_Ps emphasize the need for their preservation in an unaltered state. Despite the importance of official REA_Ps, the potential for unauthorized alterations poses a significant challenge when stored in centralized databases. With its inherent tamper-proof nature, Blockchain (BC) technology emerges as an ideal solution to safeguard integrity of the REA_Ps. This study proposes a Blockchain-Enhanced Real Estate appraisal management framework, <em>BERE</em>, to ensure the immutability of REA_Ps and enhance appraisal process transparency. The proposed <em>BERE</em> framework fosters trust among stakeholders in the real estate appraisal sector. By securely storing REA_Ps authored by on-field appraisal experts on the BC, the method prevents unauthorized modifications and ensures the confidentiality of private data. Simulations employ a variety of measures, such as BC size, transaction verification time, CPU usage, and message overhead on transaction generation, to assess system performance. The results indicate that the <em>BERE</em> framework successfully maintains the accuracy and reliability of REA_Ps. To the best of our knowledge, this is the first comprehensive study showcasing a practical application of BC technology to demonstrate its ability to transform the appraisal process and inspire trust in the accuracy of REA_Ps.</div></div>","PeriodicalId":50635,"journal":{"name":"Computer Standards & Interfaces","volume":"96 ","pages":"Article 104095"},"PeriodicalIF":3.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145578672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing decision-making in Industry 5.0 through adaptive human–machine interfaces: A systematic literature review","authors":"Salima Meftah ,&nbsp;M’hammed Sahnoun ,&nbsp;Mourad Messaadia ,&nbsp;Sidi-Mohamed Benslimane","doi":"10.1016/j.csi.2025.104091","DOIUrl":"10.1016/j.csi.2025.104091","url":null,"abstract":"<div><div>In the dynamic landscape of Industry 5.0, adaptive human–machine interface (HMI) plays a pivotal role in shaping decision-making processes. This study constitutes a systematic literature review focusing on adaptive HMI in Industry 5.0, exploring their applications and implications within the decision-making context. The research objectives are structured around key questions, addressing the manifestation of adaptive HMI in the context of Industry 5.0, the evolutionary trajectory of HMI across industrial revolutions, relevant studies on adaptive HMI, the discernible impact of contextual use on HMI adaptation, emerging challenges of the new generation of HMI within Industry 5.0, and the integration of advanced technologies in adaptive HMI. Our findings identify key factors shaping decision-making in adaptive HMI, including acceptance and trust, transparency and reliability, privacy and security, human-centric design, long-term usability effects, accessibility, and decision support capabilities. We also highlight the role of enabling technologies—such as the Internet of Things (IoT), Internet of Humans (IoH), Virtual and Augmented Reality (VR/AR), Artificial Intelligence (AI), the Internet of Everything (IoE), and their synergistic integration in advancing adaptive HMI capabilities. This research provides valuable insights for designing and developing the next generation of adaptive HMI, specifically aimed at enhancing decision-making operators’ productivity and improving the quality of their decisions in smart manufacturing environments within Industry 5.0.</div></div>","PeriodicalId":50635,"journal":{"name":"Computer Standards & Interfaces","volume":"96 ","pages":"Article 104091"},"PeriodicalIF":3.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145578671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reliability techniques and architectures for blockchain-enabled internet of things: Current applications, systematic review, and future trends","authors":"Xin Sun ,&nbsp;Xinglong Yu ,&nbsp;Qinlu Huang ,&nbsp;Zhigang Wang ,&nbsp;Jiahu Guo ,&nbsp;Zhihao Huang ,&nbsp;Fei Xie","doi":"10.1016/j.csi.2025.104068","DOIUrl":"10.1016/j.csi.2025.104068","url":null,"abstract":"<div><div>The rapid proliferation of Internet of Things (IoT) devices across diverse sectors has amplified concerns regarding security, scalability, and trust, particularly due to the reliance on centralized architectures. Blockchain, with its decentralized structure and cryptographic foundations, has emerged as a potential enabler of secure, scalable, and accountable IoT ecosystems. Despite increasing interest, limited attention has been paid to the reliability and dependability mechanisms in blockchain-enabled IoT networks, especially in resource-constrained or developing regions. This study presents a systematic review of key publications, categorizing them into five principal groups: consensus mechanisms, fault-tolerant designs, data integrity techniques, multi-tier-based mechanisms, and lightweight blockchain-based mechanisms. By employing this taxonomy, the review investigates how different technical approaches ranging from advanced cryptography methods to symmetry-based architectural designs contribute to trust management, operational resilience, and data protection in IoT ecosystems. The findings suggest that although blockchain integration holds substantial potential for overcoming existing limitations in IoT infrastructures, it also presents new engineering and architectural challenges. Nevertheless, the diverse techniques identified in the literature demonstrate tangible progress in improving efficiency, reducing latency, and enhancing the overall reliability and security of decentralized IoT networks.</div></div>","PeriodicalId":50635,"journal":{"name":"Computer Standards & Interfaces","volume":"96 ","pages":"Article 104068"},"PeriodicalIF":3.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145105313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From manual to automated systematic review: Key attributes influencing the duration of systematic reviews in software engineering","authors":"Diana Kalibatiene ,&nbsp;Jolanta Miliauskaitė","doi":"10.1016/j.csi.2025.104073","DOIUrl":"10.1016/j.csi.2025.104073","url":null,"abstract":"<div><h3>Context</h3><div>It is widely accepted that a systematic literature review (SLR) is an effective, comprehensive, repeatable, less biased, and transparent method for gathering and condensing knowledge from existing scientific publications. The SLR method facilitates the identification of gaps for new research opportunities, fostering decision-making based on evidence. At the same time, SLR is a time and effort-consuming task that is threatened by the increasing volume of publications. However, there is a lack of comprehension about which factors directly impact manually conducted SLR performance, limiting researchers to better plan and optimize their processes.</div></div><div><h3>Objective</h3><div>To enhance the understanding of the attributes that directly influence the SLR process in terms of time consumption.</div></div><div><h3>Methods</h3><div>We performed a tertiary study that (i) identified 138 secondary studies, (ii) mapped the possible influential attributes for SLR performance, (iii) extracted data from SLR reports and metadata, synthesized and analysed their influence, providing an overview of core trends related to those attributes over time.</div></div><div><h3>Results</h3><div>Our SLR mapped four main attributes influencing the performance time of the SLR process – number of authors, number of initially retrieved papers from databases, number of included papers for data synthesis, and usage of the snowballing techniques. We noticed a trend for smaller research groups (2–5 persons) using 4–6 different databases and processing to process a large number of studies, and an increasing adoption of the snowballing technique.</div></div><div><h3>Conclusion</h3><div>This paper reveals a bottleneck in manually conducted SLR, reinforcing the need for evolving automation. Mapping the attributes is only the first step to making the SLR process more measurable regarding its resource consumption. We contribute by providing recommendations to assist scientists and practitioners in planning their future SLRs and IT projects, including SLRs, particularly in the evolving landscape of digital transformation and innovations.</div></div>","PeriodicalId":50635,"journal":{"name":"Computer Standards & Interfaces","volume":"96 ","pages":"Article 104073"},"PeriodicalIF":3.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145105866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep learning-based automated segmentation of brain tumors using synthetic MR images generated with DCGAN","authors":"Ercüment Güvenç ,&nbsp;Mevlüt Ersoy ,&nbsp;Gürcan Çetin","doi":"10.1016/j.csi.2025.104054","DOIUrl":"10.1016/j.csi.2025.104054","url":null,"abstract":"<div><div>Early detection of a brain tumor significantly increases the likelihood that treatment will begin in a timely manner. Because it is difficult to detect tumor tissue with visual inspection, the magnetic resonance (MR) imaging method was developed. The analysis of MR images largely dependent on the radiologist's experience and visual interpretation. The primary reason for this is that brain tumors can vary in form and size. Deep learning (DL)-based techniques have accelerated medical image segmentation research thanks to their self-learning capabilities. When large amounts of training data are presented, these methods can achieve high success rates. ImageNet, CIFAR10/100, PASCAL VOC, MS COCO, and BRaTS benchmark datasets are extensively used for brain tumor segmentation. However, the limited amount of data in these datasets restricts the performance of DL models. The outstanding performance of Generative Adversarial Networks (GAN) in the field of medical image generation has attracted the interest of academics in recent years. In the study, we present a deep learning model that creates synthetic brain MR images using a Deep Convolutional GAN (DCGAN). The BRaTS2018 dataset's FLAIR sequence training data has been utilized as input. After a certain number of epochs, the learning model generated realistic and high-quality brain MR images. The FID score was used to evaluate the performance of the GAN model. Tumor regions on the generated MR images have been segmented automatically using the K-means algorithm and produced a high-dimensional dataset of 782 images. The study examined to what extent synthetic MR images enhanced the tumor region segmentation performance of the UNet, ResUNet, ResNet50, VGG16, and VGG19 models. According to the findings of the study, the ResNet50 model outperformed the other DL models. In terms of model performance, accuracy improved from 98.99% to 99.26%, the dice coefficient score moved from 57.33% to 81.32%, and the IoU increased from 40.89% to 66.86%.</div></div>","PeriodicalId":50635,"journal":{"name":"Computer Standards & Interfaces","volume":"96 ","pages":"Article 104054"},"PeriodicalIF":3.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144902953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Guest editorial: Special issue on “human factors in cyber security”","authors":"Sabarathinam Chockalingam ,&nbsp;Ricardo Colomo-Palacios ,&nbsp;Eunkyoung Jee ,&nbsp;Nathan Lau","doi":"10.1016/j.csi.2025.104080","DOIUrl":"10.1016/j.csi.2025.104080","url":null,"abstract":"","PeriodicalId":50635,"journal":{"name":"Computer Standards & Interfaces","volume":"96 ","pages":"Article 104080"},"PeriodicalIF":3.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145623565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing security, privacy, and usability in social robots: A software development framework","authors":"Samson O. Oruma ,&nbsp;Mary Sánchez-Gordón ,&nbsp;Vasileios Gkioulos","doi":"10.1016/j.csi.2025.104052","DOIUrl":"10.1016/j.csi.2025.104052","url":null,"abstract":"<div><div>The field of social robotics is witnessing a transformative shift in public interaction and service provision with the advent of Social Robots in Public Spaces (SRPS). However, this progress brings forth significant software security challenges. Developers and stakeholders struggle with designing secure SRPS software without specific standards and frameworks. Existing Secure Software Development Life Cycles fall short in addressing the intricate security needs of SRPS, often prioritizing functionality over security. Integrating various technologies within SRPS and the dynamic nature of public spaces compounds the challenge of ensuring security and user acceptance. To bridge this gap, this study proposes SecuRoPS, a framework designed specifically to address the unique security, safety, and usability requirements of SRPS throughout the software development lifecycle by emphasizing stakeholder engagement, regulatory compliance, and continuous iterative improvements. Built on a robust technology transfer model, the framework is validated through expert interviews, real-world use cases, and laboratory testing, ensuring practical applicability and adaptability to evolving threats. This iterative framework aims to guide various stakeholders, including software developers, organizations, researchers, and end-users, fostering wider acceptance and facilitating the safe integration of social robots into everyday life.</div></div>","PeriodicalId":50635,"journal":{"name":"Computer Standards & Interfaces","volume":"96 ","pages":"Article 104052"},"PeriodicalIF":3.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144886894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence in web accessibility: A systematic mapping study","authors":"Milton Campoverde-Molina ,&nbsp;Sergio Luján-Mora","doi":"10.1016/j.csi.2025.104055","DOIUrl":"10.1016/j.csi.2025.104055","url":null,"abstract":"<div><div>The popularization and new renaissance of artificial intelligence (AI) have inspired the creation of new applications that help developers improve website accessibility that benefits users with and without disabilities. Therefore, this research presents a systematic mapping study (SMS) because AI in web accessibility has been gaining more interest nowadays with the exposure of works that require an SMS to systematize and consolidate the literature. Through a literature review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), 53 studies from ACM Digital Library, IEEE Xplore, Scopus, and Web of Science were identified for inclusion in this review. The main results of this SMS are APIs with AI, web applications and plugins with AI, image and voice recognition with AI, limitations and challenges of AI in web accessibility, correction and testing of web accessibility with AI, automatic correction of web accessibility with AI, web navigation with conversational agents with AI, web and mobile application accessibility with AI, good practices in web accessibility for AI, accessibility of web forms and elements with AI. According to the results, in the studies, alternative texts were created for the images of the websites, AI helped generate accessible HTML code using well-defined prompts, AI tools must comply with Web Content Accessibility Guidelines (WCAG), machine learning was the most used approach, the most used language models were large language models (LLM) and accessibility barrier correction using ChatGPT. The primary contribution of this SMS lies in its analysis of the current state of AI research related to web accessibility and the identification of trends and gaps in this research area. This SMS is intended for researchers, programmers, and software development companies that may use language models, AI tools, or emerging technologies in web accessibility to mitigate website accessibility barriers.</div></div>","PeriodicalId":50635,"journal":{"name":"Computer Standards & Interfaces","volume":"96 ","pages":"Article 104055"},"PeriodicalIF":3.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144933212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}