Benedict Djouboussi^1,*, Elie Fute Tagne^1,2

Journal of Cyber Security, Vol.8, pp. 171-187, 2026, DOI:10.32604/jcs.2026.079617 - 15 April 2026

Abstract The Distributed Network Protocol 3 (DNP3) is widely deployed in SCADA-based microgrids; however, it was not originally designed to meet the cybersecurity requirements of modern decentralized energy infrastructures. Although DNP3 Secure Authentication (DNP3-SA) introduces HMAC-based session-level protection, it does not ensure fragment-level integrity, leaving the protocol vulnerable to fragmentation disruption, replay attacks, and sequence manipulation. Such vulnerabilities can cause desynchronization between master and outstation devices, compromising the operational reliability of distributed energy resources. This paper proposes DNP3Chain, a blockchain-enabled framework that provides real-time fragment-level validation and enforces end-to-end message integrity in DNP3 communications. An OpenDNP3-based… More >

Waqar Ali¹, May Altulyan², Ghulam Farooque³, Siyuan Li⁴, Jie Shao^4,5,*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.078599 - 09 April 2026

Abstract Federated recommender systems (FedRS) enable collaborative model training while preserving user privacy, yet they remain vulnerable to adversarial attacks, unreliable client updates, and misaligned incentives in decentralized environments. Existing approaches struggle to jointly preserve personalization, robustness, and trust when user data are highly non-IID and recommendation quality is governed by ranking-oriented objectives. To address these challenges, we propose a Trustworthy Federated Recommender System (T-FedRS) that extends federated neural collaborative filtering by integrating a ranking-aware reputation mechanism and a lightweight blockchain layer for transparent incentive allocation. Personalization is preserved through locally maintained user embeddings, while item parameters… More >

Tsu-Yang Wu¹, Yehai Xue¹, Haonan Li², Saru Kumari³, Lip Yee Por^2,*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.077332 - 09 April 2026

Abstract Blockchain technology, characterized by decentralization, transparency, and immutability, has been widely applied in areas such as supply chain tracking, medical data management, and the Internet of Things. However, single blockchain systems suffer from limitations in performance, scalability, and cross-chain interoperability, giving rise to the issue of “blockchain silos.” To address the challenges of data and asset circulation among heterogeneous blockchain networks, both academia and industry have proposed multi-blockchain architectures. In this paper, we categorize current multi-blockchain systems from a network topology perspective into four types: parallel architecture, hierarchical architecture, hybrid architecture, and multi-blockchain networks. We… More >

Jun Qi^1,*, Chao Yang², Xinliu Wang², Junyou Yang¹, Haixin Wang¹, Huaqin Chen^2,3, Zhenyan Li³

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.076511 - 09 April 2026

Abstract With the diversification of electricity trading forms driven by distributed energy technologies, the continuous growth of blockchain’s chained data structure poses dual challenges to traditional B+ tree indexes in terms of query efficiency and storage costs. This paper proposes a sliding window-based learned index construction method (SW-LI). The method consists of two key components. First, block timestamp–height samples are selected using a sliding window and used to train a linear regression model that captures the timestamp-to-height mapping. Second, an adaptive window adjustment mechanism is introduced: when the prediction error within a window exceeds a threshold,… More >

Ruida Liu, Dan Wang^*, Jiaming Chen, Meng Xu

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.074554 - 09 April 2026

Abstract Accurate prediction of shoulder joint angles based on surface electromyography (sEMG) signals is critical in human–machine interaction and rehabilitation engineering. However, due to the shoulder joint’s complex degrees of freedom, dynamically varying muscle coordination patterns, and the susceptibility of sEMG signals to cross-talk and noise interference, achieving high-precision prediction remains challenging. In this study, LASENet (BiLSTM–Attention–SE Network) is proposed as an end-to-end deep learning framework that integrates a bidirectional long short-term memory network (BiLSTM), a multi-head self-attention (MHSA) mechanism, and a squeeze-and-excitation (SE) block to predict shoulder joint angles across three degrees of freedom directly More >

Shahab Ali Khan¹, Tehseen Mazhar^2,3,*, Syed Faisal Abbas Shah⁴, Wasim Ahmad¹, Sunawar Khan², Afsha BiBi⁵, Usama Shah¹, Habib Hamam^6,7,8,9

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.3, 2026, DOI:10.32604/cmes.2026.075882 - 30 March 2026

Abstract The convergence of Artificial Intelligence (AI) and the Internet of Things (IoT) has enabled Artificial Intelligence of Things (AIoT) systems that support intelligent and responsive smart societies, but it also introduces major security and privacy concerns across domains such as healthcare, transportation, and smart cities. This Systemic Literature Review (SLR) addresses three research questions: identifying major threats and challenges in AIoT ecosystems, reviewing state-of-the-art security and privacy techniques, and evaluating their effectiveness. An SLR covering the period from 2020 to 2025 was conducted using major academic digital libraries, including IEEE Xplore, ACM Digital Library, ScienceDirect, More >

Zichang Meng, Na Chen, Qi Li, Qingyi Liu, Hongfei Jiang^*

Energy Engineering, Vol.123, No.4, 2026, DOI:10.32604/ee.2025.072848 - 27 March 2026

Abstract Heliostat field design for tower solar thermal plants must jointly address solar geometry, optical losses, and layout optimization under engineering constraints. We develop an end-to-end workflow that (i) adopts a consistent East–North–Up (ENU) convention for all plant- and sun-related vectors; (ii) integrates cosine efficiency, projection-based shading and blocking (SB), atmospheric transmittance, and an HFLCAL (heliostat field local calculation) truncation model into a single optical chain; and (iii) couples an Eliminate-Blocking (EB) layout prior with an improved “Cheetah” metaheuristic to search ring topology, mirror sizes, and heights while enforcing spacing, kinematics, and rated-power requirements. Projection-based SB… More >

Yuji Sang¹, Lijun Liu^1,*, Long Lv^1,*, Husheng Wu², Hemin Yin¹

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2025.073837 - 12 March 2026

Abstract Aiming at the challenges of low throughput, excessive consensus latency and high communication complexity in the Practical Byzantine Fault Tolerance (PBFT) algorithm in blockchain networks, its application in identity verification for distributed networking of a drone cluster is limited. Therefore, a lightweight blockchain-based identity authentication model for UAV swarms is designed, and a Credit-score and Grouping-mechanism Practical Byzantine Fault Tolerance (CG-PBFT) algorithm is proposed. CG-PBFT introduces a reputation score evaluation mechanism, classifies the reputation levels of nodes in the network, and optimizes the consensus process based on grouping consensus and BLS aggregate signature technology. Experimental More >

Mekhled Alharbi^1,*, Khalid Haseeb², Mamoona Humayun^3,*

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2025.073832 - 12 March 2026

Abstract The Internet of Things (IoT) and cloud computing have significantly contributed to the development of smart cities, enabling real-time monitoring, intelligent decision-making, and efficient resource management. These systems, particularly in IoT networks, rely on numerous interconnected devices that handle time-sensitive data for critical applications. In related approaches, trusted communication and reliable device interaction have been overlooked, thereby lowering security when sharing sensitive IoT data. Moreover, it incurs additional energy consumption and overhead while addressing potential threats in the dynamic environment. In this research, an Artificial Intelligence (AI) recommended fault-tolerant framework is proposed that leverages blockchain More >

Arvind Panwar¹, Urvashi Sugandh², Achin Jain^3,*, Arun Kumar Dubey³, Sarita Yadav³

Journal of Blockchain and Intelligent Computing, Vol.2, pp. 1-26, 2026, DOI:10.32604/jbic.2026.077106 - 11 March 2026

Abstract This study conducts a systematic bibliometric investigation of scholarly research on game-theoretic applications in blockchain ecosystems over the period 2014–2024, based on 554 publications retrieved from the Web of Science and Scopus databases. Using citation analysis, co-citation analysis, bibliographic coupling, and keyword co-occurrence mapping implemented through VOSviewer, the study quantitatively reveals the intellectual structure, thematic evolution, and collaborative architecture of this interdisciplinary research domain. The results demonstrate an exponential growth in publications after 2020, corresponding with the rapid expansion of decentralized finance (DeFi) and Web3 ecosystems. Five dominant research clusters are identified: consensus mechanisms, token… More >