Jiawen Qiao, Na Wang, Junsong Fu, Lunzhi Deng, Jingjing Wang, Jianwei Liu
{"title":"A Lightweight CP-ABE Scheme for EHR Over Cloud Based on Blockchain and Secure Multi-Party Computation","authors":"Jiawen Qiao, Na Wang, Junsong Fu, Lunzhi Deng, Jingjing Wang, Jianwei Liu","doi":"10.1002/ett.70053","DOIUrl":"https://doi.org/10.1002/ett.70053","url":null,"abstract":"<div>\u0000 \u0000 <p>With the growth of cloud computing and the popularity of electronic health records (EHR), more and more patients and hospitals are uploading EHR to the cloud for storage, retrieval and organization. Due to the privacy of EHR, cloud-based EHR systems need to protect data security and provide access control, and attribute-based encryption (ABE) is the appropriate technology. Nevertheless, traditional single-center ABE schemes do not conform to the collaborative scenario of electronic health care, and some of them do not support real-time attribute update. Consequently, this paper proposes a lightweight CP-ABE scheme for EHR over cloud based on blockchain and secure multi-party computation (LCBS). First, we introduce the model of multi-authority and innovatively apply secure multi-party computation to initialize the system, which maintains normal system operation while the power is decentralized. Second, we deploy a blockchain suitable for EHR systems to record the users' key information, assisting multiple entities to verify the key at different stages and protecting the EHR from illegal acquisition. In addition, our scheme supports lightweight attribute update, which requires small amount of computational overhead to achieve instant attribute update. Finally, through formal security analysis and simulation experiments of the LCBS system, it is shown that our scheme guarantees data security and improves computing efficiency.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 2","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143121216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"There is Mathematics for That!: A Formal Verification of Privacy and Simulative Analysis of Consumer-Centric Content Delivery in Iot","authors":"Shikhar Bhardwaj, Sandeep Harit, Shilpa Verma","doi":"10.1002/ett.70059","DOIUrl":"https://doi.org/10.1002/ett.70059","url":null,"abstract":"<div>\u0000 \u0000 <p>The inherent complexity and the critical nature of data privacy in IoT networks necessitate rigorous validation of privacy mechanisms to preempt vulnerabilities and ensure compliance with security standards. This research article extends the concept of the SDN-enabled Consumer-Centric Content Delivery Network (CCDN) model for the IoT by introducing a rigorous mathematical framework to formalize the dialogues integral to user privacy and data integrity. With the help of a comprehensive mathematical formulation, the research captures the dynamics of credential exchange and user interactions within the CCDN architecture. To ensure the robustness of the proposed model, this research employs formal verification techniques to validate the correctness and security properties of the mathematical formulation. Furthermore, the research conducts an extensive simulative analysis to evaluate the performance of the CCDN architecture under various operational conditions. This analysis encompasses aggregate analysis, amortized analysis, and scalability analysis, focusing on critical performance metrics such as latency, packet loss ratio, and throughput. The results demonstrate that the implemented CCDN model maintains user privacy and personalization for content delivery in scalable IoT environments. This work lays the groundwork for future research in secure and efficient content delivery systems, addressing the growing demands of IoT applications while ensuring user-centric privacy and data protection.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 2","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143121214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Khaled M. Matrouk, Punithavathi Rasappan, Priyanka Bhutani, Shikha Mittal, A. Sahaya Anselin Nisha, Reddy Madhavi Konduru
{"title":"Development of Heuristic Strategy With Hybrid Encryption for Energy Efficient and Secure Data Storage Scheme in Blockchain-Based Mobile Edge Computing","authors":"Khaled M. Matrouk, Punithavathi Rasappan, Priyanka Bhutani, Shikha Mittal, A. Sahaya Anselin Nisha, Reddy Madhavi Konduru","doi":"10.1002/ett.70057","DOIUrl":"https://doi.org/10.1002/ett.70057","url":null,"abstract":"<div>\u0000 \u0000 <p>Internet of Things (IoT) devices is extensively employed to collect physiological health data and provide diverse services to end-users. Nevertheless, in recent applications, cloud computing-based IoT proves beneficial for standard data storage and ensuring high-security information sharing. Due to limitations in battery capacity, storage, and computing power, IoT devices are often considered resource-constrained. Consequently, data signing by IoT devices, aimed at ensuring data integrity and authentication, typically demands significant computational resources. Unsafe data storage and high latency are considered as the major issues in the IoT-based data storage mechanism for duplicating and misusing the information while it is stored in the cloud database. Hence, blockchain technologies are needed to provide high security over the stored data. Hence, the research aimed to implement an efficient blockchain-based data storage system in mobile edge computing, safeguarding data from unauthorized access. In this approach, it contains four layers that are cloud layer, the entity layer, the block-chain layer, and the edge computing layer. The user's data are stored in the optimal location in the entity layer, where the data storing location is find out using the proposed Hybrid Battle Royale with Archimedes Optimization Algorithm (HBRAOA). In the edge computing layer, an optimal key-based homomorphic encryption algorithm using Elliptic Curve Cryptography (ECC) is introduced to encrypt data with the most optimal key, ensuring secure storage. This encryption method leverages the same HBRAOA to enhance the efficiency. Next, the digital signature is demonstrated to give the authorization of the user, and it is distributed to the blockchain layer. Thus, the indexes of the shared data are stored in the blockchain layer to avoid fault tolerance and tamper-proofing. Finally, the cloud layer receives the valuable encrypted data, and the authenticated users with known encrypted keys are able to access the data by decrypting them. The result analysis shows that the performance of the developed model, which attains 27%, 98%, 35%, and 18% enhanced than Particle Swarm Optimization (PSO)-ECC, Black Widow Optimization (BWO)-ECC, Battle Royale Optimization (BRO)-ECC and Archimedes Optimization Algorithm (AOA)-ECC. The efficiency of the proposed blockchain-based mobile edge computing scheme with the optimization strategy is validated by conducting several similarity measures over the conventional methods.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 2","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143118776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Secured DDoS Attack Detection in SDN Using TS-RBDM With MDPP-Streebog Based User Authentication","authors":"Monika Dandotiya, Rajni Ranjan Singh Makwana","doi":"10.1002/ett.70052","DOIUrl":"https://doi.org/10.1002/ett.70052","url":null,"abstract":"<div>\u0000 \u0000 <p>In a Distributed Denial of Service (DDoS) attack, the attacker aims to render a network resource unavailable to its intended users. A novel Software Defined Networking (SDN)-centered secured DDoS attack detection system is presented in this paper by utilizing TanhSoftmax-Restricted Boltzmann Dense Machines (TS-RBDM) with a Mean Difference of Public key and Private key based Streebog (MDPP-Streebog) user authentication algorithm. Primarily, in the registration phase, the users have registered their device details. The two-stage login process is performed after successful registration. Then, in the network layer, the nodes are initialized, and via the Gate/Router, the sensed data is transmitted to the SDN controller to enhance network energy efficiency. Later, by using the CIC DDoS 2019 dataset, the DDoS detection system is trained. This dataset undergoes preprocessing, and features are extracted from it. By employing the Adaptive Synthetic (ADASYN) technique, data balancing is achieved. Lastly, by using the TS-RBDM technique, the data is trained. The sensed data is categorized as either attacked or non-attacked data within this trained DDoS detection system. By employing the Entropy Binomial probability-based Shanon-Fano-Elias (EB-SFE) technique, the non-attacked data will be encoded and transmitted to the receiving terminal. Lastly, the experiential assessment illustrated that the proposed DDoS detection system attained 98% accuracy with 37 485 ms minimal training time, thus outperforming all state-of-the-art methods.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 2","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143118658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Karunkuzhali, S. Pradeep, Akey Sungheetha, T. S. Ghouse Basha
{"title":"Data-Aggregation-Aware Energy-Efficient in Wireless Sensor Networks Using Multi-Stream General Adversarial Network","authors":"D. Karunkuzhali, S. Pradeep, Akey Sungheetha, T. S. Ghouse Basha","doi":"10.1002/ett.70017","DOIUrl":"https://doi.org/10.1002/ett.70017","url":null,"abstract":"<div>\u0000 \u0000 <p>The lifetime of a wireless sensor network (WSN) can be impacted by the energy consumption of the routing protocol, because small sensor nodes are typically hard to recharge after deployment. Generally, data aggregation is employed to decrease the data redundancy and save energy at each node in a WSN. Traditional routing protocols frequently fall short of handling the complexities of data aggregation while getting energy efficient. In this paper, Optimized Multi-Stream General Adversarial Network espoused Data-Aggregation-Aware Energy-Efficient Routing Protocol for WSN (MSGAN-RPOA-DAA-EERP) is proposed. Here, Multi-Stream General Adversarial Network (MSGAN) is used for routing protocol. Then the Red Panda Optimization algorithm (RPOA) is proposed to optimize the MSGAN to increase the network lifetime of WSN. The proposed model is used to maximize the parameters such as data aggregation, communication energy and node residual energy. The proposed MSGAN-RPOA-DAA-EERP method attains 20.28%, 27.91% and 17.53% lower energy consumption when compared to the existing methods, like Energy-efficient cross-layer-basis opportunistic routing protocol and partially informed sparse autoencoder for data transfer in WSN (EECOP-PIAS-WSN), Improved buffalo optimized deep feed forward neural learning dependent multiple path routing for energy efficient data accumulation (IBO-DFFNL-EEDA), Effective communication in WSN utilizing optimized energy efficient engroove leach clustering protocol (EC-WSN-EEELCP) respectively.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 2","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143118192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Exploring Illumination and Communication: A Comprehensive Analysis of LED Lighting in Modern Interior Architectural Designs, Enhanced by Weighted Sum Model and Cluster Analysis for Informed Lighting Selection","authors":"Keerthana Sathiamoorthy, Indumathi Ganesan","doi":"10.1002/ett.70036","DOIUrl":"https://doi.org/10.1002/ett.70036","url":null,"abstract":"<div>\u0000 \u0000 <p>The study of light is crucial in modern interiors, as it dispels darkness and enhances both functionality and aesthetics. From the primal flicker of flames in ancient caves to the advanced light emitting diode (LED) systems of today, lighting has been pivotal in shaping our surroundings and experiences. In contemporary interior architectural designs, lighting fulfills not only functional roles but also greatly influences the aesthetics and atmosphere of a space. Light has been an integral element in sleek interior architecture. With the advancements in LED technology, the approach to illuminating spaces has been transformed providing energy-efficient solutions. This paper explores the role of LED lighting in modern interior architectural designs focusing on its impact on illumination and communication. Using a weighted sum model and cluster analysis, the various LED lighting configurations are evaluated for their suitability in different spaces. Performance metrics such as illuminance levels, uniformity, adherence to standards, signal-to-noise ratio (SNR) and bit error rate (BER) are analyzed. By varying the configurations of LED array per position from 10 × 10 to 100 × 100 the performance across different scales is assessed. The results offer insights for selecting LED lighting options that optimize functionality, aesthetics and energy efficiency in modern interior spaces.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143114242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
G Johncy, R S Shaji, T M Angelin Monisha Sharean, U Hubert
{"title":"Enhancing Smart Grid Security Using BLS Privacy Blockchain With Siamese Bi-LSTM for Electricity Theft Detection","authors":"G Johncy, R S Shaji, T M Angelin Monisha Sharean, U Hubert","doi":"10.1002/ett.70033","DOIUrl":"https://doi.org/10.1002/ett.70033","url":null,"abstract":"<div>\u0000 \u0000 <p>Energy management inside a blockchain framework developed for smart grids is primarily concerned with improving intrusion detection to protect data privacy. The emphasis is on real-time detection of cyberattacks and preemptive forecasting of possible risks, especially in the realm of electricity theft within smart grid systems. Existing Electricity Theft Detection techniques for smart grids have obstacles such as class imbalance, which leads to poor generalization, increased complexity due to large EC data aspects, and a high false positive rate in supervised models, resulting in incorrect classification of regular customers as abnormal. To provide security in the smart grid, a novel BLS Privacy Blockchain with Siamese Bi-LSTM is proposed. Initially, the privacy-preserving Boneh-Lynn-Shacham blockchain technique is built on BLS Short signature and hash algorithms, which mitigate misclassification rates and false positives in the detection of smart grid attacks. Then, a hybrid framework employs an intrusion detection algorithm based on Siamese Bidirectional Long Short-Term Memory to semantically distinguish between harmful and authentic behaviors, thereby improving data quality and predictive capabilities. Furthermore, a Recurrent Neural Network-Generative Adversarial Network is presented for detecting electricity fraud, which addresses the issue of class imbalance. This uses both supervised and unsupervised loss functions to produce synthetic theft samples that closely resemble actual theft incidents. From the experiment, it is showing that the proposed models perform with high accuracy and low error rates. The proposed model from the outcomes when compared to other existing models achieves high accuracy, detection rate, recall, and low computation time.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143112973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
K. Ravikumar, M. Mathivanan, A. Muruganandham, L. Raja
{"title":"Attentive Dual Residual Generative Adversarial Network for Energy-Aware Routing Through Golden Search Optimization Algorithm in Wireless Sensor Network Utilizing Cluster Head Selection","authors":"K. Ravikumar, M. Mathivanan, A. Muruganandham, L. Raja","doi":"10.1002/ett.70035","DOIUrl":"https://doi.org/10.1002/ett.70035","url":null,"abstract":"<div>\u0000 \u0000 <p>Wireless Sensor Networks (WSNs) are extensively used in event monitoring and tracking, particularly in scenarios that require minimal human intervention. However, a key challenge in WSNs is the short lifespan of sensor nodes (SN), as continuous sensing leads to rapid battery depletion. In high-traffic areas, sensors located near the sink node exhaust their energy quickly, creating an energy-hole issue. As a result, optimizing energy usage is a significant challenge for WSN-assisted applications. To address this, this paper proposes an Energy-aware Routing and Cluster Head Selection in Wireless Sensor Network through an Attentive Dual Residual Generative Adversarial Network for Golden Search Optimization Algorithm in Wireless Sensor Network (EAR-WSN-ADRGAN-GSOA). This method involves selecting the Cluster Head (CH) using Attentive Dual Residual Generative Adversarial Network (ADRGAN), minimizing energy consumption, and reducing a number of dead sensor nodes. Subsequently, Golden Search Optimization Algorithm (GSOA) is employed to determine an optimal path for data transmission to the sink node, maximizing energy efficiency, and elongating sensor node lifespan. The proposed EAR-WSN-ADRGAN-GSOA method is simulated in MATLAB. The performance metrics, such as network lifetime, number of alive nodes, number of dead nodes, throughput, energy consumption, and packet delivery ratio is examined. The proposed EAR-WSN-ADRGAN-GSOA demonstrates improved performance, achieving a higher average throughput of 0.93 Mbps, and lower average energy consumption of 0.39 mJ compared with the existing methods. These improvements have significant real-world implications for enhancing the efficiency and longevity of WSNs in applications, such as environmental monitoring, smart cities, and industrial automation.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143112449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kavitha Dhanushkodi, Kiruthika Venkataramani, Naghul Pranav K R, Ravikumar Sethuraman
{"title":"BGHO-E2EB Model: Enhancing IoT Security With Gaussian Artificial Hummingbird Optimization and Blockchain Technology","authors":"Kavitha Dhanushkodi, Kiruthika Venkataramani, Naghul Pranav K R, Ravikumar Sethuraman","doi":"10.1002/ett.70037","DOIUrl":"https://doi.org/10.1002/ett.70037","url":null,"abstract":"<div>\u0000 \u0000 <p>The Internet of Things (IoT) is transforming numerous sectors but also presents unique security challenges due to its interconnected and resource-constrained devices. This study introduces the Bidirectional Gaussian Hummingbird Optimized End-to-End Blockchain (BGHO-E2EB) model, designed to detect and classify cyberattacks within IoT environments. Unlike preventive approaches, the developed model focuses on real-time detection and categorization of attacks, enabling timely responses to emerging threats. The proposed model integrates blockchain technology through Ethereum-based smart contracts to enhance the security and integrity of data exchanges within IoT networks. Additionally, a Gaussian Artificial Hummingbird Algorithm is employed for optimal feature selection, minimizing data dimensionality and computational load. A Bidirectional Long Short-Term Memory (Bi-LSTM) network further improves the model's capability by accurately detecting and categorizing cyber threats based on selected features. The Adam optimizer is used for efficient parameter tuning within the Bi-LSTM network, ensuring high-performance cyberattack detection. The proposed model was evaluated using established IoT security benchmarks, including the UNSW-NB15, BOT-IoT, and NSL-KDD datasets, accomplishing an accuracy of 98.7%, precision of 96.3%, and security level of 99.5%, significantly outperforming traditional methods. These results demonstrate the effectiveness of BGHO-E2EB as a robust tool for detecting and classifying cyberattacks in IoT networks, making it suitable for real-world deployment in dynamic IoT environments where security is paramount.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143112741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Absalom E. Ezugwu, Olutosin Taiwo, Ojonukpe S. Egwuche, Laith Abualigah, Annette Van Der Merwe, Jayanta Pal, Apu K. Saha, Ahmed Ibrahim Alzahrani, Fahad Alblehai, Japie Greeff, Micheal O. Olusanya
{"title":"Smart Homes of the Future","authors":"Absalom E. Ezugwu, Olutosin Taiwo, Ojonukpe S. Egwuche, Laith Abualigah, Annette Van Der Merwe, Jayanta Pal, Apu K. Saha, Ahmed Ibrahim Alzahrani, Fahad Alblehai, Japie Greeff, Micheal O. Olusanya","doi":"10.1002/ett.70041","DOIUrl":"https://doi.org/10.1002/ett.70041","url":null,"abstract":"<p>The advent of the Internet of Things (IoT) has transformed the concept of smart home automation, thereby allowing users to remotely interact with their houses and control home appliances for resource efficiency. This technological development has significantly improved convenience, safety, and overall lifestyles for homeowners. The impact of smart home automation systems (SHAS) extends beyond individual households, positively influencing the global economy in various aspects. While research in smart home automation has proposed solutions to wireless control and monitoring issues, there are still challenges hindering the widespread deployment of these systems. This paper conducts a detailed systematic analysis of state-of-the-art SHAS, covering topics such as the concept of smart home automation, its application domains, architectural framework, enabling technologies, as well as the challenges involved. Furthermore, this paper provides reviews and discussions on the latest essential components, technologies, and protocols employed in designing and developing SHAS. By offering an in-depth examination of the current scenery, this study aims to provide readers with a comprehensive understanding of smart home automation, its significance, and future research directions. Through addressing the challenges and presenting potential solutions, this research contributes to adopting wider acceptance and successful deployment of SHAS.</p>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ett.70041","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143112450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}