Zhi Li¹, Yufei Zhao², Yueming Ji², Hanwen Gu², Zaibin Jiao^2,*

Energy Engineering, Vol.121, No.12, pp. 3899-3927, 2024, DOI:10.32604/ee.2024.055899 - 22 November 2024

Abstract By integrating advanced digital technologies such as cloud computing and the Internet of Things in sensor measurement, information communication, and other fields, the digital DC distribution network can efficiently and reliably access Distributed Generator (DG) and Energy Storage Systems (ESS), exhibiting significant advantages in terms of controllability and meeting requirements of Plug-and-Play (PnP) operations. However, during device plug-in and -out processes, improper system parameters may lead to small-signal stability issues. Therefore, before executing PnP operations, conducting stability analysis and adjusting parameters swiftly is crucial. This study introduces a four-stage strategy for parameter optimization to enhance… More >

Zainatul Yushaniza Mohamed Yusoff¹, Mohamad Khairi Ishak^2,*, Lukman A. B. Rahim³, Mohd Shahrimie Mohd Asaari¹

Computer Systems Science and Engineering, Vol.48, No.6, pp. 1669-1697, 2024, DOI:10.32604/csse.2024.056741 - 22 November 2024

Abstract The rapid adoption of Internet of Things (IoT) technologies has introduced significant security challenges across the physical, network, and application layers, particularly with the widespread use of the Message Queue Telemetry Transport (MQTT) protocol, which, while efficient in bandwidth consumption, lacks inherent security features, making it vulnerable to various cyber threats. This research addresses these challenges by presenting a secure, lightweight communication proxy that enhances the scalability and security of MQTT-based Internet of Things (IoT) networks. The proposed solution builds upon the Dang-Scheme, a mutual authentication protocol designed explicitly for resource-constrained environments and enhances it… More >

Deema Alsekait¹, Mohammed Zakariah², Syed Umar Amin^3,*, Zafar Iqbal Khan³, Jehad Saad Alqurni⁴

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2395-2436, 2024, DOI:10.32604/cmc.2024.055469 - 18 November 2024

Abstract The widespread adoption of Internet of Things (IoT) devices has resulted in notable progress in different fields, improving operational effectiveness while also raising concerns about privacy due to their vulnerability to virus attacks. Further, the study suggests using an advanced approach that utilizes machine learning, specifically the Wide Residual Network (WRN), to identify hidden malware in IoT systems. The research intends to improve privacy protection by accurately identifying malicious software that undermines the security of IoT devices, using the MalMemAnalysis dataset. Moreover, thorough experimentation provides evidence for the effectiveness of the WRN-based strategy, resulting in… More >

Ying Wang¹, Jie Dang¹, Cangbi Ding^2,*, Chenyi Zheng², Yi Tang²

Energy Engineering, Vol.121, No.11, pp. 3331-3353, 2024, DOI:10.32604/ee.2024.052066 - 21 October 2024

Abstract As the large-scale development of wind farms (WFs) progresses, the connection of WFs to the regional power grid is evolving from the conventional receiving power grid to the sending power grid with a high proportion of wind power (WP). Due to the randomness of WP output, higher requirements are put forward for the voltage stability of each node of the regional power grid, and various reactive power compensation devices (RPCDs) need to be rationally configured to meet the stable operation requirements of the system. This paper proposes an optimal configuration method for multi-type RPCDs in More >

Arkan Kh Shakr Sabonchi^*

Journal on Artificial Intelligence, Vol.6, pp. 261-282, 2024, DOI:10.32604/jai.2024.056552 - 18 October 2024

Abstract The phenomenal increase in device connectivity is making the signaling and resource-based operational integrity of networks at the node level increasingly prone to distributed denial of service (DDoS) attacks. The current growth rate in the number of Internet of Things (IoT) attacks executed at the time of exchanging data over the Internet represents massive security hazards to IoT devices. In this regard, the present study proposes a new hybrid optimization technique that combines the firefly optimization algorithm with global searches for use in attack detection on IoT devices. We preprocessed two datasets, CICIDS and UNSW-NB15,… More >

Manh-Tuyen Vi¹, Duc-Nghia Tran², Vu Thi Thuong^3,4, Nguyen Ngoc Linh^5,*, Duc-Tan Tran^1,*

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1729-1756, 2024, DOI:10.32604/cmc.2024.055511 - 15 October 2024

Abstract Analyzing physical activities through wearable devices is a promising research area for improving health assessment. This research focuses on the development of an affordable and real-time Human Activity Recognition (HAR) system designed to operate on low-performance microcontrollers. The system utilizes data from a body-worn accelerometer to recognize and classify human activities, providing a cost-effective, easy-to-use, and highly accurate solution. A key challenge addressed in this study is the execution of efficient motion recognition within a resource-constrained environment. The system employs a Random Forest (RF) classifier, which outperforms Gradient Boosting Decision Trees (GBDT), Support Vector Machines… More >

NOELIA L. D´ELĺA^1,2, A. NOEL GRAVINA^1,2, LUCIANO A. BENEDINI^2,3,*, PAULA V. MESSINA^1,2

BIOCELL, Vol.48, No.10, pp. 1401-1403, 2024, DOI:10.32604/biocell.2024.055512 - 02 October 2024

Abstract This work shows relevant interactions between cells and drug-delivery systems based on vesicles crucial for therapeutic activity. This interplay drives strategies for the design of new drug-carry. Among the described systems are found liposomes, extracellular vesicles, and hybrid systems. The text details their properties, advantages, and constraints, and eventually, a perspective about the future of these formulations is proposed. More >

GyuHyun Jeon¹, Hojun Jin¹, Ju Hyeon Lee¹, Seungho Jeon², Jung Taek Seo^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1575-1622, 2024, DOI:10.32604/cmes.2024.053465 - 27 September 2024

Abstract The Internet of Wearable Things (IoWT) or Wearable Internet of Things (WIoT) is a new paradigm that combines IoT and wearable technology. Advances in IoT technology have enabled the miniaturization of sensors embedded in wearable devices and the ability to communicate data and access real-time information over low-power mobile networks. IoWT devices are highly interdependent with mobile devices. However, due to their limited processing power and bandwidth, IoWT devices are vulnerable to cyberattacks due to their low level of security. Threat modeling and frameworks for analyzing cyber threats against existing IoT or low-power protocols have… More >

Seung-Ju Han, Seong-Su Yoon, Ieck-Chae Euom^*

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1495-1518, 2024, DOI:10.32604/cmes.2024.053457 - 27 September 2024

Abstract The rapid proliferation of Internet of Things (IoT) technology has facilitated automation across various sectors. Nevertheless, this advancement has also resulted in a notable surge in cyberattacks, notably botnets. As a result, research on network analysis has become vital. Machine learning-based techniques for network analysis provide a more extensive and adaptable approach in comparison to traditional rule-based methods. In this paper, we propose a framework for analyzing communications between IoT devices using supervised learning and ensemble techniques and present experimental results that validate the efficacy of the proposed framework. The results indicate that using the More >

Yangrong Chen^1,2, June Li^3,*, Yu Xia³, Ruiwen Zhang³, Lingling Li^1,2, Xiaoyu Li^1,2, Lin Ge^1,2

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2579-2609, 2024, DOI:10.32604/cmc.2024.053230 - 15 August 2024

Abstract Intelligent electronic devices (IEDs) are interconnected via communication networks and play pivotal roles in transmitting grid-related operational data and executing control instructions. In the context of the heightened security challenges within smart grids, IEDs pose significant risks due to inherent hardware and software vulnerabilities, as well as the openness and vulnerability of communication protocols. Smart grid security, distinct from traditional internet security, mainly relies on monitoring network security events at the platform layer, lacking an effective assessment mechanism for IEDs. Hence, we incorporate considerations for both cyber-attacks and physical faults, presenting security assessment indicators and… More > Graphic Abstract