{"title":"Bibliometric Analysis of Blockchain in the Healthcare Domain","authors":"Shilpi Garg;Rajesh Kumar Kaushal;Naveen Kumar;Anshul Verma","doi":"10.23919/ICN.2023.0025","DOIUrl":"https://doi.org/10.23919/ICN.2023.0025","url":null,"abstract":"As an innovation, Blockchain has transformed numerous industries and sparked the interest of the research community due to its abundance of benefits, opening up diverse research routes in the healthcare sector in the last decade. With Health 4.0 becoming ubiquitous in the healthcare industry, end-user transactions are being carried out on a decentralized network, making Blockchain profitable to meet the demands of the modern healthcare sector. Therefore, a detailed analysis of Blockchain is very crucial. This study emphasizes the evolution of science and the preliminary research of Blockchain in healthcare through bibliometric analysis. All the data are extracted from the Scopus database, and the VOSviewer tool is used for analysis. A total of 1152 Scopus articles published between 2018 and 2022 are examined. Results reveal that in 2022, the field of Blockchain experienced a notable increment in the number of publications and a significant growth rate. IEEE Access became well known in this field and had a large number of citations. It is observed that China and India are the leading countries in terms of publications on Blockchain. This study offers a number of recommendations that amateur and professional researchers can use as a benchmark before commencing a Blockchain investigation in the future.","PeriodicalId":100681,"journal":{"name":"Intelligent and Converged Networks","volume":"4 4","pages":"305-312"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10379048","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139081287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Relay-assisted wireless energy harvesting for multihop clustered IoT network","authors":"B. Pavani;K. Venkata Subbareddy;L. Nirmala Devi","doi":"10.23919/ICN.2023.0018","DOIUrl":"https://doi.org/10.23919/ICN.2023.0018","url":null,"abstract":"In large-scale networks such as the Internet of Things (IoT), devices seek multihop communication for long-distance communications, which considerably impacts their power exhaustion. Hence, this study proposes an energy harvesting-enabled, relay-based communication in multihop clustered IoT networks in a bid to conserve the battery power in multihop IoT networks. Initially, this study proposes an efficient, hierarchical clustering mechanism in which entire IoT devices are clustered into two types: the closest cluster (CC) and remote clusters (RCs). Additionally, Euclidean distance is employed for the CC and fuzzy c-means for the RCs. Next, for cluster head (CH) selection, this study models a fitness function based on two metrics, namely residual energy and distance (device-to-device distance and device-to-sink distance). After CH selection, the entire clustered network is partitioned into several layers, after which a relay selection mechanism is applied. For every CH of the upper layer, we assign a few lower-layer CHs to function as relays. The relay selection mechanism is applied only for the devices in the RCs, while for devices in the CC, the CH functions as a relay. Finally, several simulation experiments are conducted to validate the proposed method's performance. The results show the method's superiority in terms of energy efficiency and optimal number of relays in comparison with the state-of-the-art methods.","PeriodicalId":100681,"journal":{"name":"Intelligent and Converged Networks","volume":"4 3","pages":"206-224"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9195266/10286548/10286549.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49979476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multi-resolution network based image steganalysis model","authors":"Zimiao Wang;Jinsong Wu","doi":"10.23919/ICN.2023.0010","DOIUrl":"https://doi.org/10.23919/ICN.2023.0010","url":null,"abstract":"Recently, many steganalysis approaches improve their feature extraction ability through adding convolutional layers. However, it often leads to a decrease of resolution in the feature map during downsampling, which makes it challenging to extract weak steganographic signals accurately. To address this issue, this paper proposes a multi-resolution steganalysis net (MRS-Net). MRS-Net adopts a multi-resolution network to extract global image information, fusing the output feature map to ensure high-dimensional semantic information and supplementing low-level detail information. Furthermore, the model incorporates an attention module which can analyze image sensitivity based on different channel and spatial information, thus effectively focusing on areas with rich steganographic signals. Multiple benchmark experiments on the BOSSBase 1.01 dataset demonstrate that the accuracy of MRS-Net significantly improves by 9.9% and 3.3% compared with YeNet and SRNet, respectively, demonstrating its exceptional steganalysis capability.","PeriodicalId":100681,"journal":{"name":"Intelligent and Converged Networks","volume":"4 3","pages":"198-205"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9195266/10286548/10286550.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49979475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"BDGOA: A bot detection approach for GitHub OAuth Apps","authors":"Zhifang Liao;Xuechun Huang;Bolin Zhang;Jinsong Wu;Yu Cheng","doi":"10.23919/ICN.2023.0006","DOIUrl":"https://doi.org/10.23919/ICN.2023.0006","url":null,"abstract":"As various software bots are widely used in open source software repositories, some drawbacks are coming to light, such as giving newcomers non-positive feedback and misleading empirical studies of software engineering researchers. Several techniques have been proposed by researchers to perform bot detection, but most of them are limited to identifying bots performing specific activities, let alone distinguishing between GitHub App and OAuth App. In this paper, we propose a bot detection technique for OAuth App, named BDGOA. 24 features are used in BDGOA, which can be divided into three dimensions: account information, account activity, and text similarity. To better explore the behavioral features, we define a fine-grained classification of behavioral events and introduce self-similarity to quantify the repeatability of behavioral sequence. We leverage five machine learning classifiers on the benchmark dataset to conduct bot detection, and finally choose random forest as the classifier, which achieves the highest F1-score of 95.83%. The experimental results comparing with the state-of-the-art approaches also demonstrate the superiority of BDGOA.","PeriodicalId":100681,"journal":{"name":"Intelligent and Converged Networks","volume":"4 3","pages":"181-197"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9195266/10286548/10286551.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49979474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Integrated sensing and communication based outdoor multi-target detection, tracking, and localization in practical 5G Networks","authors":"Ruiqi Liu;Mengnan Jian;Dawei Chen;Xu Lin;Yichao Cheng;Wei Cheng;Shijun Chen","doi":"10.23919/ICN.2023.0021","DOIUrl":"https://doi.org/10.23919/ICN.2023.0021","url":null,"abstract":"The 6th generation (6G) wireless networks will likely to support a variety of capabilities beyond communication, such as sensing and localization, through the use of communication networks empowered by advanced technologies. Integrated sensing and communication (ISAC) has been recognized as a critical technology as well as a usage scenario for 6G, as widely agreed by leading global standardization bodies. ISAC utilizes communication infrastructure and devices to provide the capability of sensing the environment with high resolution, as well as tracking and localizing moving objects nearby. Meeting both the requirements for communication and sensing simultaneously, ISAC-based approaches celebrate the advantages of higher spectral and energy efficiency compared to two separate systems to serve two purposes, and potentially lower costs and easy deployment. A key step towards the standardization and commercialization of ISAC is to carry out comprehensive field trials in practical networks, such as the 5th generation (5G) networks, to demonstrate its true capacities in practical scenarios. In this paper, an ISAC-based outdoor multi-target detection, tracking and localization approach is proposed and validated in 5G networks. The proposed system comprises of 5G base stations (BSs) which serve nearby mobile users normally, while accomplishing the task of detecting, tracking, and localizing drones, vehicles, and pedestrians simultaneously. Comprehensive trial results demonstrate the relatively high accuracy of the proposed method in practical outdoor environment when tracking and localizing single targets and multiple targets.","PeriodicalId":100681,"journal":{"name":"Intelligent and Converged Networks","volume":"4 3","pages":"261-272"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9195266/10286548/10286534.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49992381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Han Sun;Wei Shao;Tao Li;Jiayu Zhao;Weitao Xu;Linqi Song
{"title":"A pruning-then-quantization model compression framework for facial emotion recognition","authors":"Han Sun;Wei Shao;Tao Li;Jiayu Zhao;Weitao Xu;Linqi Song","doi":"10.23919/ICN.2023.0020","DOIUrl":"https://doi.org/10.23919/ICN.2023.0020","url":null,"abstract":"Facial emotion recognition achieves great success with the help of large neural models but also fails to be applied in practical situations due to the large model size of neural methods. To bridge this gap, in this paper, we combine two mainstream model compression methods (pruning and quantization) together, and propose a pruning-then-quantization framework to compress the neural models for facial emotion recognition tasks. Experiments on three datasets show that our model could achieve a high model compression ratio and maintain the model's high performance well. Besides, We analyze the layer-wise compression performance of our proposed framework to explore its effect and adaptability in fine-grained modules.","PeriodicalId":100681,"journal":{"name":"Intelligent and Converged Networks","volume":"4 3","pages":"225-236"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9195266/10286548/10286552.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49979477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Performance evaluation of DHRR-RIS based HP design using machine learning algorithms","authors":"Girish Kumar N G;Sree Ranga Raju M N","doi":"10.23919/ICN.2023.0019","DOIUrl":"https://doi.org/10.23919/ICN.2023.0019","url":null,"abstract":"Reconfigurable Intelligent Surfaces (RIS) have emerged as a promising technology for improving the reliability of massive MIMO communication networks. However, conventional RIS suffer from poor Spectral Efficiency (SE) and high energy consumption, leading to complex Hybrid Precoding (HP) designs. To address these issues, we propose a new low-complexity HP model, named Dynamic Hybrid Relay Reflecting RIS based Hybrid Precoding (DHRR-RIS-HP). Our approach combines active and passive elements to cancel out the downsides of both conventional designs. We first design a DHRR-RIS and optimize the pilot and Channel State Information (CSI) estimation using an adaptive threshold method and Adaptive Back Propagation Neural Network (ABPNN) algorithm, respectively, to reduce the Bit Error Rate (BER) and energy consumption. To optimize the data stream, we cluster them into private and public streams using Enhanced Fuzzy C-Means (EFCM) algorithm, and schedule them based on priority and emergency level. To maximize the sum rate and SE, we perform digital precoder optimization at the Base Station (BS) side using Deep Deterministic Policy Gradient (DDPG) algorithm and analog precoder optimization at the DHRR-RIS using Fire Hawk Optimization (FHO) algorithm. We implement our proposed work using MATLAB R2020a and compare it with existing works using several validation metrics. Our results show that our proposed work outperforms existing works in terms of SE, Weighted Sum Rate (WSR), and BER.","PeriodicalId":100681,"journal":{"name":"Intelligent and Converged Networks","volume":"4 3","pages":"237-260"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9195266/10286548/10286533.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49992380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xin Chen;Jixiang Cheng;Luanjuan Jiang;Qianmu Li;Ting Wang;Dafang Li
{"title":"Q-learning based strategy analysis of cyber-physical systems considering unequal cost","authors":"Xin Chen;Jixiang Cheng;Luanjuan Jiang;Qianmu Li;Ting Wang;Dafang Li","doi":"10.23919/ICN.2023.0012","DOIUrl":"10.23919/ICN.2023.0012","url":null,"abstract":"This paper proposes a cyber security strategy for cyber-physical systems (CPS) based on Q-learning under unequal cost to obtain a more efficient and low-cost cyber security defense strategy with misclassification interference. The system loss caused by strategy selection errors in the cyber security of CPS is often considered equal. However, sometimes the cost associated with different errors in strategy selection may not always be the same due to the severity of the consequences of misclassification. Therefore, unequal costs referring to the fact that different strategy selection errors may result in different levels of system losses can significantly affect the overall performance of the strategy selection process. By introducing a weight parameter that adjusts the unequal cost associated with different types of misclassification errors, a modified Q-learning algorithm is proposed to develop a defense strategy that minimizes system loss in CPS with misclassification interference, and the objective of the algorithm is shifted towards minimizing the overall cost. Finally, simulations are conducted to compare the proposed approach with the standard Q-learning based cyber security strategy method, which assumes equal costs for all types of misclassification errors. The results demonstrate the effectiveness and feasibility of the proposed research.","PeriodicalId":100681,"journal":{"name":"Intelligent and Converged Networks","volume":"4 2","pages":"116-126"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9195266/10207889/10208204.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44038871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Design of improved PBFT algorithm based on aggregate signature and node reputation","authors":"Jinhua Fu;Wenhui Zhou;Jie Xu","doi":"10.23919/ICN.2023.0016","DOIUrl":"10.23919/ICN.2023.0016","url":null,"abstract":"The alliance chain system is a distributed ledger system based on blockchain technology, which can realize data sharing and collaboration among multiple parties while ensuring data security and reliability. The Practical Byzantine Fault Tolerance (PBFT) consensus algorithm is the most popular consensus protocol in the alliance chain, but the algorithm has problems such as high complexity and too simple election of the master node, which will make PBFT unable to be applied in scenarios with too many nodes. At the same time, there are certain security issues. In order to solve these problems, this paper proposes an improved Byzantine consensus algorithm, Polymerization Signature and Reputation Value PBFT (P-V PBFT). Firstly, the consistency protocol process is improved based on the aggregate signature technology. The simulation results show that the P-V PBFT algorithm can effectively reduce the overhead of network transmission, and the time complexity of the algorithm decreases exponentially, which improves the efficiency of the consensus process. Secondly, the node reputation election mechanism is introduced to elect the primary node, and the security analysis is carried out to verify the fairness and security of the primary node election of the P-V PBFT algorithm. Therefore, as a feasible improvement of the blockchain consensus protocol, the P-V PBFT algorithm can provide more efficient and secure guarantee for the blockchain system in practical application.","PeriodicalId":100681,"journal":{"name":"Intelligent and Converged Networks","volume":"4 2","pages":"158-167"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9195266/10207889/10208086.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45188279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}