Pub Date : 2025-09-03DOI: 10.1016/j.csi.2025.104069
Longjiao Li , Jianchang Lai , Liquan Chen , Zhen Zhao , Ge Wu , Xinyan Yang
IoHT is a specific application of IoT technology in the healthcare field, which enhances medical efficiency and quality. Ensuring secure data sharing among multiple parties is crucial in the IoHT, particularly for resource-constrained devices. As a Chinese national standard and an ISO/IEC standard, SM9 algorithm has been widely applied in IoT, finance, e-government and so on. Although existing SM9-based schemes can ensure data security during multi-party sharing, their high computational overhead makes them unsuitable for lightweight devices. To address this issue, this paper proposes an efficient distributed decryption scheme based on SM9. The proposed scheme achieves secure and efficient multi-party data sharing. And the proposed scheme is very friendly to lightweight devices, as it avoids computationally expensive operations such as bilinear pairing. Based on the -BDHI assumption, the proposed scheme is proven to be CCA-secure. Finally, we implement our scheme through experiments and the results show that when the number of users reaches 100, the decryption time on resource-constrained devices is about 6 ms, demonstrating that the proposed scheme is suitable for deployment in IoHT.
{"title":"SM9-based device-friendly distributed decryption scheme for IoHT","authors":"Longjiao Li , Jianchang Lai , Liquan Chen , Zhen Zhao , Ge Wu , Xinyan Yang","doi":"10.1016/j.csi.2025.104069","DOIUrl":"10.1016/j.csi.2025.104069","url":null,"abstract":"<div><div>IoHT is a specific application of IoT technology in the healthcare field, which enhances medical efficiency and quality. Ensuring secure data sharing among multiple parties is crucial in the IoHT, particularly for resource-constrained devices. As a Chinese national standard and an ISO/IEC standard, SM9 algorithm has been widely applied in IoT, finance, e-government and so on. Although existing SM9-based schemes can ensure data security during multi-party sharing, their high computational overhead makes them unsuitable for lightweight devices. To address this issue, this paper proposes an efficient distributed decryption scheme based on SM9. The proposed scheme achieves secure and efficient multi-party data sharing. And the proposed scheme is very friendly to lightweight devices, as it avoids computationally expensive operations such as bilinear pairing. Based on the <span><math><mi>q</mi></math></span>-BDHI assumption, the proposed scheme is proven to be CCA-secure. Finally, we implement our scheme through experiments and the results show that when the number of users reaches 100, the decryption time on resource-constrained devices is about 6 ms, demonstrating that the proposed scheme is suitable for deployment in IoHT.</div></div>","PeriodicalId":50635,"journal":{"name":"Computer Standards & Interfaces","volume":"96 ","pages":"Article 104069"},"PeriodicalIF":3.1,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145007771","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}
Pub Date : 2025-09-03DOI: 10.1016/j.csi.2025.104057
Pei Ren , Bo Yang , Yanwei Zhou , Tao Wang , Feng Zhu , Ru Meng
As a prominent area of research in the AI 2.0 era, crowdsourcing has garnered significant attention. Traditional crowdsourcing systems suffer from several drawbacks, including single points of failure, privacy breaches, and isolated resources. The development of decentralized, privacy-preserving federated crowdsourcing systems has consequently emerged as an inevitable trend. However, this shift also introduces new security challenges, such as ensuring participant privacy, enabling rational task recommendations, and establishing inter-system trust. To address these challenges, we propose ScaFedCrowd, a secure cross-system anonymous authentication and privacy-preserving task recommendation scheme for federated crowdsourcing. Our scheme utilizes blockchain with smart contracts as the underlying platform to manage the crowdsourcing process, facilitating secure inter-system collaboration. We propose an intra-system registration and authentication method that uses a trapdoor function and non-interactive zero-knowledge (NIZK) proofs to provide optional anonymity for users. Based on similarity measurement and ElGamal cryptography, our scheme achieves secure cross-system authentication and authorization between servers and workers. Furthermore, task recommendations based on simple hashing intersection technique provide a foundation for cross-system authentication, ensuring privacy while recommending the most suitable tasks for workers. Finally, a secure revocation and tracking mechanism ensures the protection of legitimate rights. Security analysis and simulation results demonstrate that ScaFedCrowd enhances effectiveness, security, and versatility.
{"title":"ScaFedCrowd: A secure cross-system anonymous authentication and privacy-preserving task recommendation scheme for federated crowdsourcing","authors":"Pei Ren , Bo Yang , Yanwei Zhou , Tao Wang , Feng Zhu , Ru Meng","doi":"10.1016/j.csi.2025.104057","DOIUrl":"10.1016/j.csi.2025.104057","url":null,"abstract":"<div><div>As a prominent area of research in the AI 2.0 era, crowdsourcing has garnered significant attention. Traditional crowdsourcing systems suffer from several drawbacks, including single points of failure, privacy breaches, and isolated resources. The development of decentralized, privacy-preserving federated crowdsourcing systems has consequently emerged as an inevitable trend. However, this shift also introduces new security challenges, such as ensuring participant privacy, enabling rational task recommendations, and establishing inter-system trust. To address these challenges, we propose ScaFedCrowd, a secure cross-system anonymous authentication and privacy-preserving task recommendation scheme for federated crowdsourcing. Our scheme utilizes blockchain with smart contracts as the underlying platform to manage the crowdsourcing process, facilitating secure inter-system collaboration. We propose an intra-system registration and authentication method that uses a trapdoor function and non-interactive zero-knowledge (NIZK) proofs to provide optional anonymity for users. Based on similarity measurement and ElGamal cryptography, our scheme achieves secure cross-system authentication and authorization between servers and workers. Furthermore, task recommendations based on simple hashing intersection technique provide a foundation for cross-system authentication, ensuring privacy while recommending the most suitable tasks for workers. Finally, a secure revocation and tracking mechanism ensures the protection of legitimate rights. Security analysis and simulation results demonstrate that ScaFedCrowd enhances effectiveness, security, and versatility.</div></div>","PeriodicalId":50635,"journal":{"name":"Computer Standards & Interfaces","volume":"96 ","pages":"Article 104057"},"PeriodicalIF":3.1,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145007729","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}
Pub Date : 2025-09-02DOI: 10.1016/j.csi.2025.104068
Xin Sun , Xinglong Yu , Qinlu Huang , Zhigang Wang , Jiahu Guo , Zhihao Huang , Fei Xie
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.
{"title":"Reliability techniques and architectures for blockchain-enabled internet of things: Current applications, systematic review, and future trends","authors":"Xin Sun , Xinglong Yu , Qinlu Huang , Zhigang Wang , Jiahu Guo , Zhihao Huang , 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":"2025-09-02","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}
Pub Date : 2025-09-01DOI: 10.1016/j.csi.2025.104067
Guoming Meng , Leyou Zhang
With the increasing emphasis on data circulation and value realization, privacy-preserving computation has become a critical enabler for cross-organizational data collaboration. This survey focuses on Private Set Intersection (PSI) techniques within the framework of Secure Multi-Party Computation (SMPC), systematically reviewing the theoretical foundations and technological evolution of PSI as a fundamental privacy-preserving protocol. We first construct a technical stack of PSI protocols, elucidating the cryptographic principles that enable efficient set operations while preserving data confidentiality. Furthermore, we explore the synergistic integration of PSI with blockchain and federated learning, highlighting innovative paradigms for addressing privacy challenges in decentralized environments. Notably, in response to emerging threats posed by quantum computing, this work analyzes the design of post-quantum PSI protocols based on pseudorandom quantum states. Through empirical studies in representative application scenarios – such as collaborative medical analytics, financial risk modeling, and government data sharing – this survey not only demonstrates the practical value of PSI but also underscores its pivotal role in building a trustworthy data collaboration ecosystem. As computational paradigms continue to evolve, PSI is poised to achieve breakthroughs in the multi-objective optimization of privacy, efficiency, and security, thereby offering robust privacy-preserving solutions across various industries.
{"title":"A survey on secure multi-party computation techniques based on private set intersection","authors":"Guoming Meng , Leyou Zhang","doi":"10.1016/j.csi.2025.104067","DOIUrl":"10.1016/j.csi.2025.104067","url":null,"abstract":"<div><div>With the increasing emphasis on data circulation and value realization, privacy-preserving computation has become a critical enabler for cross-organizational data collaboration. This survey focuses on Private Set Intersection (PSI) techniques within the framework of Secure Multi-Party Computation (SMPC), systematically reviewing the theoretical foundations and technological evolution of PSI as a fundamental privacy-preserving protocol. We first construct a technical stack of PSI protocols, elucidating the cryptographic principles that enable efficient set operations while preserving data confidentiality. Furthermore, we explore the synergistic integration of PSI with blockchain and federated learning, highlighting innovative paradigms for addressing privacy challenges in decentralized environments. Notably, in response to emerging threats posed by quantum computing, this work analyzes the design of post-quantum PSI protocols based on pseudorandom quantum states. Through empirical studies in representative application scenarios – such as collaborative medical analytics, financial risk modeling, and government data sharing – this survey not only demonstrates the practical value of PSI but also underscores its pivotal role in building a trustworthy data collaboration ecosystem. As computational paradigms continue to evolve, PSI is poised to achieve breakthroughs in the multi-objective optimization of privacy, efficiency, and security, thereby offering robust privacy-preserving solutions across various industries.</div></div>","PeriodicalId":50635,"journal":{"name":"Computer Standards & Interfaces","volume":"96 ","pages":"Article 104067"},"PeriodicalIF":3.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144933214","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}
Pub Date : 2025-08-30DOI: 10.1016/j.csi.2025.104066
Anna Melman, Kristina Dzhanashia, Oleg Evsutin
The cybersecurity problems remain extremely relevant in the modern world. Every year image steganography and watermarking schemes are proposed that solve the problems of hidden confidential data transfer and image authentication, respectively. The authors attempt to maximize the main embedding indicators, such as capacity, invisibility, and robustness. However, in practice, the time effectiveness of embedding schemes also becomes paramount. Some schemes can provide outstanding embedding quality according to the main embedding indicators but have unsuitable time complexity for real-world applications. Others, on the contrary, aim to satisfy the requirements of real applications, sacrificing the main indicators in the process. Some authors manage to achieve the trade-off between embedding efficiency and algorithm complexity using special measures. Yet, in many works, these solutions are not covered in detail. In this paper, an overview of relevant studies in image steganography and watermarking, the authors of which apply various techniques for speed improvement, is presented. Algorithmic, software, and hardware approaches to improving computation time are analyzed separately, and the most widespread solutions are highlighted. The overview ends with promising research directions for improving the performance of additional information embedding into digital images in the context of execution time.
{"title":"Overview of methods to improve execution time in image steganography and watermarking","authors":"Anna Melman, Kristina Dzhanashia, Oleg Evsutin","doi":"10.1016/j.csi.2025.104066","DOIUrl":"10.1016/j.csi.2025.104066","url":null,"abstract":"<div><div>The cybersecurity problems remain extremely relevant in the modern world. Every year image steganography and watermarking schemes are proposed that solve the problems of hidden confidential data transfer and image authentication, respectively. The authors attempt to maximize the main embedding indicators, such as capacity, invisibility, and robustness. However, in practice, the time effectiveness of embedding schemes also becomes paramount. Some schemes can provide outstanding embedding quality according to the main embedding indicators but have unsuitable time complexity for real-world applications. Others, on the contrary, aim to satisfy the requirements of real applications, sacrificing the main indicators in the process. Some authors manage to achieve the trade-off between embedding efficiency and algorithm complexity using special measures. Yet, in many works, these solutions are not covered in detail. In this paper, an overview of relevant studies in image steganography and watermarking, the authors of which apply various techniques for speed improvement, is presented. Algorithmic, software, and hardware approaches to improving computation time are analyzed separately, and the most widespread solutions are highlighted. The overview ends with promising research directions for improving the performance of additional information embedding into digital images in the context of execution time.</div></div>","PeriodicalId":50635,"journal":{"name":"Computer Standards & Interfaces","volume":"96 ","pages":"Article 104066"},"PeriodicalIF":3.1,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144933213","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}
Pub Date : 2025-08-29DOI: 10.1016/j.csi.2025.104055
Milton Campoverde-Molina , Sergio Luján-Mora
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.
人工智能（AI）的普及和新复兴激发了新的应用程序的创建，这些应用程序帮助开发人员提高网站的可访问性，使残疾和非残疾用户受益。因此，本研究提出了一个系统的地图研究（SMS），因为人工智能在网页可访问性方面已经获得了越来越多的兴趣，现在需要一个SMS来系统化和巩固文献。通过使用系统评价和荟萃分析首选报告项目（PRISMA）进行文献综述，从ACM数字图书馆、IEEE Xplore、Scopus和Web of Science中确定了53项研究纳入本综述。该SMS的主要成果是带有AI的api、带有AI的web应用程序和插件、带有AI的图像和语音识别、AI在web可访问性方面的限制和挑战、带有AI的web可访问性的校正和测试、带有AI的web可访问性的自动校正、带有AI的会话代理的web导航、带有AI的web和移动应用程序可访问性、用于AI的web可访问性的良好实践、带有AI的web表单和元素的可访问性。根据研究结果，在研究中，为网站的图像创建了替代文本，人工智能使用定义良好的提示帮助生成可访问的HTML代码，人工智能工具必须遵守Web内容可访问性指南（WCAG），机器学习是最常用的方法，最常用的语言模型是大型语言模型（LLM）和使用ChatGPT的可访问性障碍校正。本SMS的主要贡献在于分析了与网络可访问性相关的人工智能研究的现状，并确定了该研究领域的趋势和差距。本短信适用于研究人员、程序员和软件开发公司，他们可能会使用语言模型、人工智能工具或网络可访问性中的新兴技术来减轻网站可访问性障碍。
{"title":"Artificial intelligence in web accessibility: A systematic mapping study","authors":"Milton Campoverde-Molina , 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":"2025-08-29","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}
Pub Date : 2025-08-16DOI: 10.1016/j.csi.2025.104056
Mohamed Abdou , Hanan M. Amer , Abeer T. Khalil , Mohamed M. Abdelsalam
The use of wireless sensor networks (WSNs) has increased rapidly in recent years as almost everything around us is becoming smart. Many challenges are facing WSNs, and one of them is energy utilization. In most scenarios, sensor nodes (SNs) are battery-powered. Once the battery is exhausted, the SN is treated as a dead node and its coverage area is considered a blind region. Another problem is the mobility of SNs. In many applications, SNs are movable that creates a frequent change in the system’s topology, which may lead to a great reduction in the system’s performance. Building an appropriate routing protocol to handle these problems can significantly increase the system’s performance. An adaptive geometrical clustering routing protocol for mobile WSNs (AGCRP) is introduced. The protocol divides the network into grid cells, each cell has a forwarder cluster head (FCH), a collector cluster head (CCH), and a set of cluster members (CMs). The CCH collects the data from CMs in its cluster and sends it to the FCH. The FCH then sends the data to the main station (MS). The selection of FCHs and CCHs has been done considering parameters such as energy level, distance to the grid center, and average distance relative to CMs. The simulation results show that the suggested method increases the stabilization, lifetime, and throughput of the static environment by about 31%, 34%, and 41% respectively compared with EECRAIFA, and increases the stabilization, and lifetime for the dynamic environment by about 74% and 32% respectively compared with DTC-BR.
{"title":"An adaptive geometrical clustering routing protocol (AGCRP) for energy-efficient mobile wireless sensor networks in smart cities","authors":"Mohamed Abdou , Hanan M. Amer , Abeer T. Khalil , Mohamed M. Abdelsalam","doi":"10.1016/j.csi.2025.104056","DOIUrl":"10.1016/j.csi.2025.104056","url":null,"abstract":"<div><div>The use of wireless sensor networks (WSNs) has increased rapidly in recent years as almost everything around us is becoming smart. Many challenges are facing WSNs, and one of them is energy utilization. In most scenarios, sensor nodes (SNs) are battery-powered. Once the battery is exhausted, the SN is treated as a dead node and its coverage area is considered a blind region. Another problem is the mobility of SNs. In many applications, SNs are movable that creates a frequent change in the system’s topology, which may lead to a great reduction in the system’s performance. Building an appropriate routing protocol to handle these problems can significantly increase the system’s performance. An adaptive geometrical clustering routing protocol for mobile WSNs (AGCRP) is introduced. The protocol divides the network into grid cells, each cell has a forwarder cluster head (FCH), a collector cluster head (CCH), and a set of cluster members (CMs). The CCH collects the data from CMs in its cluster and sends it to the FCH. The FCH then sends the data to the main station (MS). The selection of FCHs and CCHs has been done considering parameters such as energy level, distance to the grid center, and average distance relative to CMs. The simulation results show that the suggested method increases the stabilization, lifetime, and throughput of the static environment by about 31%, 34%, and 41% respectively compared with EECRAIFA, and increases the stabilization, and lifetime for the dynamic environment by about 74% and 32% respectively compared with DTC-BR.</div></div>","PeriodicalId":50635,"journal":{"name":"Computer Standards & Interfaces","volume":"95 ","pages":"Article 104056"},"PeriodicalIF":3.1,"publicationDate":"2025-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144866521","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}
Pub Date : 2025-08-16DOI: 10.1016/j.csi.2025.104052
Samson O. Oruma , Mary Sánchez-Gordón , Vasileios Gkioulos
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.
{"title":"Enhancing security, privacy, and usability in social robots: A software development framework","authors":"Samson O. Oruma , Mary Sánchez-Gordón , 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":"2025-08-16","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}
The rapid development of Smart Home IoT (SH-IoT) technologies presents considerable challenges in information security and privacy protection, including recurrent data breaches and privacy violations. Addressing these issues, this study introduces a multi-image encryption algorithm utilizing a novel 3D discrete hyperchaotic map to strengthen SH-IoT security. The solution simultaneously encrypts multiple images by integrating compressive sensing, while novel encryption units disrupt pixel correlations through cross-plane permutation and ring chain diffusion. Demonstrating remarkable adaptability, the algorithm dynamically adjusts compression ratios according to device capabilities and application demands, optimizing the security-efficiency-quality balance. Experimental validation confirms exceptional performance: achieving 99.6095% NPCR and 33.4597% UACI, along with a 2481 kb/s encryption speed at 0.5 compression ratio—substantially outperforming non-compressed scenarios.
{"title":"A new multi-image encryption scheme for Smart Home IoT integrating hyperchaos and compressive sensing","authors":"Yuanmao Zhong, Qiang Lai, Chongkun Zhu, Minghong Qin","doi":"10.1016/j.csi.2025.104051","DOIUrl":"10.1016/j.csi.2025.104051","url":null,"abstract":"<div><div>The rapid development of Smart Home IoT (SH-IoT) technologies presents considerable challenges in information security and privacy protection, including recurrent data breaches and privacy violations. Addressing these issues, this study introduces a multi-image encryption algorithm utilizing a novel 3D discrete hyperchaotic map to strengthen SH-IoT security. The solution simultaneously encrypts multiple images by integrating compressive sensing, while novel encryption units disrupt pixel correlations through cross-plane permutation and ring chain diffusion. Demonstrating remarkable adaptability, the algorithm dynamically adjusts compression ratios according to device capabilities and application demands, optimizing the security-efficiency-quality balance. Experimental validation confirms exceptional performance: achieving 99.6095% NPCR and 33.4597% UACI, along with a 2481 kb/s encryption speed at 0.5 compression ratio—substantially outperforming non-compressed scenarios.</div></div>","PeriodicalId":50635,"journal":{"name":"Computer Standards & Interfaces","volume":"95 ","pages":"Article 104051"},"PeriodicalIF":3.1,"publicationDate":"2025-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144829124","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}
Pub Date : 2025-08-08DOI: 10.1016/j.csi.2025.104054
Ercüment Güvenç , Mevlüt Ersoy , Gürcan Çetin
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%.
{"title":"Deep learning-based automated segmentation of brain tumors using synthetic MR images generated with DCGAN","authors":"Ercüment Güvenç , Mevlüt Ersoy , 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":"2025-08-08","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}
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