Transactions on Emerging Telecommunications Technologies最新文献

{"title":"Gazelle-Dingo Optimization and Ensemble Classification: A Hybrid Approach for Intrusion Detection in Fog Computing","authors":"Aravind Karrothu,&nbsp;G. V. Sriramakrishnan,&nbsp;V. Ragavi","doi":"10.1002/ett.70084","DOIUrl":"https://doi.org/10.1002/ett.70084","url":null,"abstract":"<div>\u0000 \u0000 <p>Fog computing is a system that expands the cloud services to the network to manipulate the inherent issues of the cloud. An intrusion detection system (IDS) is a network security tool for monitoring a computer network for malicious activities that include potential threats, abnormal activities, and unauthorized access to fog networks. It is a key component of fog network security that provides quality of service in data communication. In this research, the intrusion is detected using the Ensemble classifier in the fog layer by utilizing the proposed gazelle dingo optimization (GDO). Here, three layers are considered for the entire process, including the endpoint layer, cloud layer, and fog layer. Initially, the physical process is done in the endpoint layer for connecting and exchanging the information. Then, at the cloud layer, various processes like data transformation, feature selection, and ensemble classification are carried out. The data transformation process utilizes Yeo-Johnson transformation, followed by feature selection that is done by Kulczynski similarity. Afterward, the selected features are fed toward ensemble classifiers such as deep residual network (DRN), deep belief network (DBN), and Zeiler-Fergus network (ZF-Net) for the classification, where the ensemble classifier is tuned by GDO. Finally, the fog layer detects the intrusion using an ensemble classifier tuned by GDO. The GDO is formed by combining the gazelle optimization algorithm (GOA) and dingo optimization algorithm (DOA). Here, the proposed GDO-Ensemble Classifier attained the superior values of precision, recall, and F-measure of 0.922, 0.935, and 0.918.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 3","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143554731","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":"CNN-Based Local Quantized Hybrid Precoding for Low Complexity and Overhead","authors":"Fulai Liu,&nbsp;Huiyang Shi,&nbsp;Ruiyan Du","doi":"10.1002/ett.70093","DOIUrl":"https://doi.org/10.1002/ett.70093","url":null,"abstract":"<div>\u0000 \u0000 <p>Hybrid precoding is one of the promising technologies for millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems. Traditional hybrid precoding algorithms often suffer from high computational costs because the massive MIMO systems have a large number of antennas. For this purpose, this paper proposes a convolutional neural network (CNN)-based local quantized hybrid precoding for low complexity and overhead. Firstly, a local quantized hybrid precoding approach is proposed to construct a label of the CNN framework under the lower complexity and feedback overhead. The proposed local quantized approach locally quantizes the feasible sets of the analog precoders to reduce feedback overhead according to the sparsity of the mmWave channel in the angular domain. Secondly, a new spectral efficiency-feedback overhead is defined to determine the range of local quantization bits <span></span><math></math>, so that the unnecessary feedback overhead can be avoided effectively while the spectral efficiency (SE) of the label is guaranteed. Finally, in order to further reduce complexity and feedback overhead, as well as make full use of the sparsity of the channel, a new CNN framework is built to enhance the spectrum efficiency of the system. Specifically, the mmWave channel and the label are used as the input-output pairs of the CNN framework, convolutional layers are employed to capture certain sparse characteristics from the angular domain of the channel. Due to the establishment of the input-output pairs of the CNN framework, the complexity of the CNN is effectively reduced. Compared with the previous works, the presented method enjoys less training time-consuming, lower feedback overhead, and higher precision. The simulation results are presented verifying the effectiveness of the proposed method.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 3","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143554412","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":"Cluster Based Lion Optimization Routing Protocol for Internet of Vehicles (CLORP)","authors":"Farhana Ajaz,&nbsp;Mohd Naseem,&nbsp;Janjhyam Venkata Naga Ramesh,&nbsp;Mohammad Shabaz,&nbsp;Gulfam Ahamad","doi":"10.1002/ett.70089","DOIUrl":"https://doi.org/10.1002/ett.70089","url":null,"abstract":"<div>\u0000 \u0000 <p>In view of the vast range of applications and advantages the Internet of Vehicles (IoV) offers, such as better passenger safety, entertainment, and traffic efficiency, the IoV has been the subject of substantial research. Information is sent directly or indirectly between nodes in the IoV. In the IoV, information interchange between people, vehicles, and roadside equipment is prioritized, and routing is a crucial stage in this process. Data transfer from the starting node to the destination node offers a routing challenge due to the network's dynamic nature. Routing issues arise from the need to consider a number of factors, like the throughput latency, packet delivery ratio, and routing overhead. A topology-based routing protocol that is most popular is called Ad-hoc On-Demand Distance Vector (AODV), although during route discovery, it produces a lot of unnecessary paths between source and destination nodes. In this article, a novel protocol named Cluster-based Lion Optimization Routing Protocol (CLORP) is proposed to lower the network load which is the main reason behind the problem of inefficient network performance. CLORP is centered around cluster formation and choosing the CH using the lion algorithm. It strengthens AODV protocol with the use of gateway nodes and cluster heads for routing while forming stable clusters. The main goal of CLORP is to decrease the amount of control messages sent by employing the clustering idea and choosing the best cluster head using the Lion optimization algorithm that enhances network performance. To examine the protocol's efficiency, its output is compared with that of AODV, Improved AODV, CACOIOV, AODV-DATRLD, ACO-DATRLD, DMCNF, and EHCP.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 3","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143554703","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":"AES-8: A Lightweight AES for Resource-Constrained IoT Devices","authors":"Sumit Singh Dhanda,&nbsp;Brahmjit Singh,&nbsp;Poonam Jindal,&nbsp;Vinod Kumar,&nbsp;Sachin Kumar Gupta","doi":"10.1002/ett.70094","DOIUrl":"https://doi.org/10.1002/ett.70094","url":null,"abstract":"<div>\u0000 \u0000 <p>Internet of Things (IoT) is marked by resource-constrained devices. Information security is the main challenge that arises due to the wireless transmission of data by ubiquitous sensors. In this work, we have presented a lightweight advance encryption scheme (AES) that can be used in small IoT devices. Galois field arithmetic has been used to minimize the size of the S-box. Slice consumption and throughput are two contradictory parameters in AES design. The design tries to achieve a tradeoff between these two parameters. With a separate S-box for the key expansion, a high throughput in the range of 52–163 Mbps has been achieved on different FPGAs. In terms of throughput, it matches the latest lightweight designs and outperforms older ones. It occupies 73 slices on an Artix-7 FPGA. When compared to existing AES designs, the design achieves area savings in the range of 4%–78.33%. In slice consumption, it is on par with most of the lightweight ciphers designed for IoT. The most remarkable feature of the design is its efficiency. It outperforms existing lightweight AES variants with a typical throughput per slice of 210 kbps/slice to 1.409 Mbps/slice. On Virtex-5, AES-8 has outperformed lightweight ciphers like Shadow-64, LEA-128, DULBC-80/128, and QARMA. A 24%–67% resource reduction has been achieved from these ciphers. It makes the proposed cipher suitable for application in IoT security.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 3","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143554704","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":"Hybrid AI-Driven Bio-Inspired Wearable Sensors With Aquasense AI Technology for Multimodal Health Monitoring and Rehabilitation in Dynamic Environments","authors":"J. Poongodi,&nbsp;K. Kavitha,&nbsp;S. Sathish,&nbsp;R. Lakshmana Kumar","doi":"10.1002/ett.70081","DOIUrl":"https://doi.org/10.1002/ett.70081","url":null,"abstract":"<div>\u0000 \u0000 <p>AquaSense AI is a bio-inspired, wearable sensor system that enables a paradigmatic shift in healthcare and physiotherapy, emulating nature's sensory capabilities of aquatic animals. Flexible, waterproof sensors are used to detect human motion, balance, and posture on land and in water. AquaSense AI is perfect for application in swimming pools and hydrotherapy sessions. AquaSense AI delivers real-time, high-precision feedback to enable effective rehabilitation, fall prevention, and fitness monitoring. In Under water, these sensors follow a person's posture and the coordination of their limbs through the detection of pressure changes, while on land, they monitor gait, posture, and balance. The sophisticated AI algorithms within the system, including Hierarchical Adaptive Neural Network (HANN) and Multimodal Self-Learning Framework, adjust sensor sensitivity to the environment and provide personalized feedback over time, continuously adapting to the movements and rehabilitation progress of the user. The bio-inspired design, adaptive AI, and real-time predictive analytics can provide dual functionality at clinical and fitness applications, improving safety, rehabilitation outcomes, and general health monitoring in diverse environments.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 3","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143513855","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":"A Comparison of 163-Bit Hybrid Karatsuba Multiplier and Word-Serial Multipliers for ECC Processors","authors":"Sumit Singh Dhanda,&nbsp;Vinod Kumar,&nbsp;Sachin Kumar Gupta,&nbsp;Deepak Panwar,&nbsp;Pardeep Singh","doi":"10.1002/ett.70074","DOIUrl":"https://doi.org/10.1002/ett.70074","url":null,"abstract":"<div>\u0000 \u0000 <p>Elliptic Curve Processors (ECP) are used for high performance in hardware implementation. The finite field multiplier, which occupies the maximum area in the ECP structure, plays an essential role in deciding its size and performance. The resource-constrained IoT devices employed in real-time applications demand the design of a compact yet fast multiplier. In this paper, a Hybrid Karatsuba Multiplier (HKMul) for GF (2¹⁶³) is proposed for use in Elliptic Curve Cryptography (ECC). It is a sub-quadratic multiplier. A Word-Serial Multiplier (WSMul) for the same ECP is also re-implemented in this work. Both multipliers are synthesized using Xilinx PlanAhead software. A detailed comparison has been presented using different Xilinx Field Programmable Gate Arrays (FPGAs) for detailed comparison. The HKMul nearly matches the WSMul in resource consumption and outperforms it in performance. HKMul outperforms WSMul in two instances, on Spartan-3 and Virtex-7, with very small differences of 3.3% and 1.6%, respectively. As the WSMul has a very small delay, it uses 4 clock cycles to generate the multiplication. Hence, HKMul comes out 1.01 to 1.63 times faster than WSMul.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 3","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143513858","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":"Blockchain-Integrated Secure Healthcare Information Sharing via Advanced Blowfish Encryption Standard With Optimal Key Generation","authors":"Jundale Poonam Abasaheb,&nbsp;Sujata V. Mallapur","doi":"10.1002/ett.70077","DOIUrl":"https://doi.org/10.1002/ett.70077","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Problem&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;There are serious worries about the security and privacy of sensitive patient data as a result of the growing digitization of healthcare systems, particularly when sharing data across platforms. Conventional data-sharing techniques frequently depend on centralized systems, which are susceptible to illegal access and data breaches. Existing encryption techniques, such as Blowfish, lack sufficient robustness and scalability for modern healthcare applications. Additionally, managing encryption keys securely across distributed systems remains a complex challenge.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Aim&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;This work proposes a blockchain-integrated technology with enhanced encryption and optimal key generation to address these gaps, ensuring secure, scalable, and efficient healthcare data sharing.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;In the proposed model, data sharing initiates with partitioning the healthcare data into manageable blocks, followed by encryption using an enhanced version of the Blowfish algorithm. The Improved Blowfish algorithm incorporates bitwise operations and conditional transformations to strengthen data security and flexibility in handling encrypted data. Also, the proposed work implements the Improved Pelican Optimization Algorithm (IPOA) for optimal key generation. IPOA optimizes encryption keys based on the minimizing correlation between original and encrypted data, thereby ensuring robust data protection. A blockchain is used to store encrypted data and keys, taking use of its decentralized and unchangeable structure to guard against manipulation and unwanted changes. Furthermore, the proxy re-encryption technique is employed to securely manage and distribute decryption capabilities without exposing sensitive information.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Results&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Finally, the comparative analyses highlight the superiority of the proposed approach in terms of security, efficiency, and scalability over existing methods. With a correlation coefficient of 0.203887, the Improved Blowfish approach exhibits the strongest resistance, demonstrating its resilience to Fault Injection Attack (FIA).&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Conclusion&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The suggested model's efficacy is confirmed, showing that it can improve data security, simplify access management, and reduce the hazards connected to conventional healthcare data-sharing procedures. Thus, the integration of blockchain, advanced encryption standards, and optimized key generation algorithms offers a comprehensive solution for secure healthcare i","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 3","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143513648","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":"Energy-Efficient Long Range Repair Connectivity Policy for Maritime Wireless Sensor Networks","authors":"Xiaoyan Lu,&nbsp;Zhibin Xie,&nbsp;Peiyu Yan","doi":"10.1002/ett.70086","DOIUrl":"https://doi.org/10.1002/ett.70086","url":null,"abstract":"<div>\u0000 \u0000 <p>Maritime wireless sensor network (MWSN) is integral to current communication networks, but its topology is vulnerable to environmental disruptions, leading to an unreliable and unstable communication link. In response to this challenge, we propose a connectivity repair algorithm to construct the connectivity path, which comprehensively considers the deployment location and the moving distance of mobile nodes. The proposed algorithm can achieve the purpose of connectivity repair under optimal energy consumption and mainly includes three steps. First, the Lagrangian tracking approach is used to locate the positions of drifting nodes, which are caused by wind, waves, and currents. Second, according to the location information of the drifting nodes, the length of the connectivity repair path is determined for preparing link establishment. Third, based on the energy consumption of the connectivity repair process, the closed-form solution is derived for calculating the optimal deployment distance, which is between the nodes waiting for deployment on the connectivity repair path. Furthermore, the optimal number of mobile nodes is obtained under the minimum energy consumption, and the optimal deployment of mobile nodes and connectivity repair is finally achieved. The simulations demonstrate the effectiveness and ability of the proposed algorithm in extending the lifespan of MWSN.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 3","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143496997","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":"Enhancing Agricultural Supply Chain Management With Blockchain Technology and DSA-TabNet: A PBFT-Driven Approach","authors":"Esakki Muthu Santhanam,&nbsp;Kartheeban Kamatchi","doi":"10.1002/ett.70085","DOIUrl":"https://doi.org/10.1002/ett.70085","url":null,"abstract":"<div>\u0000 \u0000 <p>Agriculture is a vital sector that must operate efficiently to meet daily dietary needs, manage logistics, and enhance food production. However, it faces significant challenges, particularly concerning product safety within supply chain management. Addressing these issues requires the adoption of advanced technologies to ensure transparency, traceability, and sustainability in agricultural supply chains. Moreover, maximizing value and maintaining consumer trust are crucial in modern agricultural practices. Existing methods often struggle to provide transparent information to stakeholders, ensure consumer trust, and accurately trace product origins. To overcome these challenges, this study proposes an innovative approach that integrates blockchain technology with a novel Dilated Self-Attention-based TabNet (DSA-TabNet) algorithm for agricultural supply chain management. The DSA-TabNet algorithm is utilized for quality assessment, leveraging blockchain to create a transparent and tamper-proof record of transactions and product data. This allows stakeholders to track the flow of agricultural products and access critical information, including storage conditions, transportation details, and harvesting and cultivation practices. To ensure data integrity and secure transactions, the Practical Byzantine Fault Tolerance (PBFT) consensus algorithm is employed. PBFT enhances the system's reliability by preventing fraudulent activities within the supply chain. The DSA-TabNet algorithm also detects patterns related to product quality, enabling early identification of issues such as adulteration, spoilage, and contamination. By learning from historical data, stakeholders receive timely notifications, ensuring that consumers receive high-quality and safe products, thereby increasing efficiency and reducing losses. The effectiveness of the proposed approach is evaluated using key performance indicators, including precision, specificity, F1-score, accuracy, recall, throughput, and latency. The results demonstrate that the integration of DSA-TabNet with blockchain technology significantly enhances the reliability, transparency, and efficiency of agricultural supply chain management.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 3","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143496998","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":"An Efficient Cyber Security Attack Detection With Encryption Using Capsule Convolutional Polymorphic Graph Attention","authors":"P. J. Sathish Kumar,&nbsp;B. R. Tapas Bapu,&nbsp;S. Sridhar,&nbsp;V. Nagaraju","doi":"10.1002/ett.70069","DOIUrl":"https://doi.org/10.1002/ett.70069","url":null,"abstract":"<div>\u0000 \u0000 <p>As digitalization permeates all aspects of life, the Internet has become a critical platform for communication across various domains. Workstations within organizations often handle sensitive and private data, underscoring the need for encryption to safeguard information and prevent unauthorized access. Despite advances in system security, challenges remain in the form of system vulnerabilities and evolving cyber threats. Intrusion detection using deep learning (DL), which serves as the second line of defense after firewalls, has progressed rapidly, yet still faces issues such as misclassification, false positives, and delayed or inadequate responses to attacks. These ongoing problems necessitate continuous improvement in system security screening and intrusion detection to protect networks effectively. Therefore, in this research, a novel DL framework called capsule convolutional polymorphic graph attention neural network with tyrannosaurus optimization algorithm (CCPGANN-TOA) is utilized for attack detection due to its advanced feature representation, graph attention for focusing on key data points, polymorphic graphs for adaptability, and TOA for performance optimization. Normal data are then encrypted using the digital signature algorithm based on elliptic curve cryptography (DSA-ECC) because it provides strong security with smaller key sizes, resulting in faster computations and efficient resource utilization. The proposed method outperforms traditional approaches in terms of 99.98% accuracy of data set I, 99.9% accuracy of data set II, and 900 Kbps higher throughput with low delay.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 3","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143489760","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}