J. Sens. Actuator Networks最新文献

{"title":"Practical Challenges of Attack Detection in Microgrids Using Machine Learning","authors":"Daniel T. Ramotsoela, G. Hancke, A. Abu-Mahfouz","doi":"10.3390/jsan12010007","DOIUrl":"https://doi.org/10.3390/jsan12010007","url":null,"abstract":"The move towards renewable energy and technological advancements in the generation, distribution and transmission of electricity have increased the popularity of microgrids. The popularity of these decentralised applications has coincided with advancements in the field of telecommunications allowing for the efficient implementation of these applications. This convenience has, however, also coincided with an increase in the attack surface of these systems, resulting in an increase in the number of cyber-attacks against them. Preventative network security mechanisms alone are not enough to protect these systems as a critical design feature is system resilience, so intrusion detection and prevention system are required. The practical consideration for the implementation of the proposed schemes in practice is, however, neglected in the literature. This paper attempts to address this by generalising these considerations and using the lessons learned from water distribution systems as a case study. It was found that the considerations are similar irrespective of the application environment even though context-specific information is a requirement for effective deployment.","PeriodicalId":288992,"journal":{"name":"J. Sens. Actuator Networks","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133533590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial of the MDPI JSAN Special Issue on Wireless Technologies Applied to Connected and Automated Vehicles","authors":"A. Bazzi","doi":"10.3390/jsan12010006","DOIUrl":"https://doi.org/10.3390/jsan12010006","url":null,"abstract":"Connectivity and automation are two aspects that, together, will revolutionize the transport system [...]","PeriodicalId":288992,"journal":{"name":"J. Sens. Actuator Networks","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116274395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Acknowledgment to the Reviewers of JSAN in 2022","authors":"Jsan Editorial Office","doi":"10.3390/jsan12010008","DOIUrl":"https://doi.org/10.3390/jsan12010008","url":null,"abstract":"High-quality academic publishing is built on rigorous peer review [...]","PeriodicalId":288992,"journal":{"name":"J. Sens. Actuator Networks","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129179064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effective One-Class Classifier Model for Memory Dump Malware Detection","authors":"Mahmoud Al-Qudah, Zein Ashi, Mohammad M. Alnabhan, Q. Abu Al-haija","doi":"10.3390/jsan12010005","DOIUrl":"https://doi.org/10.3390/jsan12010005","url":null,"abstract":"Malware complexity is rapidly increasing, causing catastrophic impacts on computer systems. Memory dump malware is gaining increased attention due to its ability to expose plaintext passwords or key encryption files. This paper presents an enhanced classification model based on One class SVM (OCSVM) classifier that can identify any deviation from the normal memory dump file patterns and detect it as malware. The proposed model integrates OCSVM and Principal Component Analysis (PCA) for increased model sensitivity and efficiency. An up-to-date dataset known as “MALMEMANALYSIS-2022” was utilized during the evaluation phase of this study. The accuracy achieved by the traditional one-class classification (TOCC) model was 55%, compared to 99.4% in the one-class classification with the PCA (OCC-PCA) model. Such results have confirmed the improved performance achieved by the proposed model.","PeriodicalId":288992,"journal":{"name":"J. Sens. Actuator Networks","volume":"485 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133880620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-Based Techniques for Ad Click Fraud Detection and Prevention: Review and Research Directions","authors":"Reem A Alzahrani, M. Aljabri","doi":"10.3390/jsan12010004","DOIUrl":"https://doi.org/10.3390/jsan12010004","url":null,"abstract":"Online advertising is a marketing approach that uses numerous online channels to target potential customers for businesses, brands, and organizations. One of the most serious threats in today’s marketing industry is the widespread attack known as click fraud. Traffic statistics for online advertisements are artificially inflated in click fraud. Typical pay-per-click advertisements charge a fee for each click, assuming that a potential customer was drawn to the ad. Click fraud attackers create the illusion that a significant number of possible customers have clicked on an advertiser’s link by an automated script, a computer program, or a human. Nevertheless, advertisers are unlikely to profit from these clicks. Fraudulent clicks may be involved to boost the revenues of an ad hosting site or to spoil an advertiser’s budget. Several notable attempts to detect and prevent this form of fraud have been undertaken. This study examined all methods developed and published in the previous 10 years that primarily used artificial intelligence (AI), including machine learning (ML) and deep learning (DL), for the detection and prevention of click fraud. Features that served as input to train models for classifying ad clicks as benign or fraudulent, as well as those that were deemed obvious and with critical evidence of click fraud, were identified, and investigated. Corresponding insights and recommendations regarding click fraud detection using AI approaches were provided.","PeriodicalId":288992,"journal":{"name":"J. Sens. Actuator Networks","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122059894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Hierarchical Deep Learning-Based Intrusion Detection Architecture for Clustered Internet of Things","authors":"Rania A. Elsayed, Reem A. Hamada, M. Hammoudeh, Mahmoud Abdalla, S. Elsaid","doi":"10.3390/jsan12010003","DOIUrl":"https://doi.org/10.3390/jsan12010003","url":null,"abstract":"The Internet of Things (IoT) system’s ever-expanding attack surface calls for a new intrusion detection system (IDS). These systems may include thousands of wireless devices that need to be protected from cyberattacks. Recent research efforts used machine learning to analyze and identify various attacks and abnormal behavior on IoT systems. Most of these techniques are characterized by low accuracy and they do not scale to today’s IoT-enabled smart cities applications. This article proposes a secure automatic two-levels intrusion detection system (SATIDS) which utilizes the minimum redundancy maximum relevance (MRMR) feature selection technique and an enhanced version of long short-term memory (LSTM) based on an artificial recurrent neural network (RNN) to enhance the IDS performance. SATIDS aims at detecting traffic anomalies with greater accuracy while also reducing the time it takes to perform this task. The proposed algorithm was trained and evaluated using two of the most recent datasets based on realistic data: ToN-IoT and InSDN datasets. The performance analysis of the proposed system proves that it can differentiate between attacks and normal traffic, identify the attack category, and finally define the type of sub-attack with high accuracy. Comparing the performance of the proposed system with the existing IDSs reveals that it outperforms its best rivals from the literature in detecting many types of attacks. It improves accuracy, detection rates, F1-score, and precision. Using 500 hidden and two LSTM layers achieves accuracy of 97.5%, precision of 98.4%, detection rate of 97.9%, and F1-score of 98.05% on ToN-IoT dataset, and precision of 99%, detection rate of 99.6%, and F1-score of 99.3% on InSDN dataset. Finally, SATIDS was applied to an IoT network which utilizes the energy harvesting real-time routing protocol (EHRT). EHRT optimizes the low-energy adaptive clustering hierarchy (LEACH) routing technique using a modified artificial fish swarm algorithm. The integration between the optimized LEACH and the proposed IDS enhances the network lifetime, energy consumption, and security.","PeriodicalId":288992,"journal":{"name":"J. Sens. Actuator Networks","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121567338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating Edge Computing and Compression for Remote Cuff-Less Blood Pressure Monitoring","authors":"Ward Goossens, Dino Mustefa, Detlef Scholle, H. Fotouhi, J. Denil","doi":"10.3390/jsan12010002","DOIUrl":"https://doi.org/10.3390/jsan12010002","url":null,"abstract":"Remote health monitoring systems play an important role in the healthcare sector. Edge computing is a key enabler for realizing these systems, where it is required to collect big data while providing real-time guarantees. In this study, we focus on remote cuff-less blood pressure (BP) monitoring through electrocardiogram (ECG) as a case study to evaluate the benefits of edge computing and compression. First, we investigate the state-of-the-art algorithms for BP estimation and ECG compression. Second, we develop a system to measure the ECG, estimate the BP, and store the results in the cloud with three different configurations: (i) estimation in the edge, (ii) estimation in the cloud, and (iii) estimation in the cloud with compressed transmission. Third, we evaluate the three approaches in terms of application latency, transmitted data volume, and power usage. In experiments with batches of 64 ECG samples, the edge computing approach has reduced average application latency by 15%, average power usage by 19%, and total transmitted volume by 85%, confirming that edge computing improves system performance significantly. Compressed transmission proved to be an alternative when network bandwidth is limited and edge computing is impractical.","PeriodicalId":288992,"journal":{"name":"J. Sens. Actuator Networks","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131796846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Antenna Delay-Independent Simultaneous Ranging for UWB-Based RTLSs","authors":"Shashi Shah, Sushank Chaudhary, Rizwan Ullah, Amir Parnianifard, Muhammad Zain Siddiqi, P. Vanichchanunt, W. Santipach, L. Wuttisittikulkij","doi":"10.3390/jsan12010001","DOIUrl":"https://doi.org/10.3390/jsan12010001","url":null,"abstract":"The ultra-wideband (UWB)-based real-time localization system (RTLS) is a promising technology for locating and tracking assets and personnel in real-time within a defined indoor environment since it provides high-ranging accuracy. However, its performance can be affected by the underlying antenna delays of UWB nodes, which act as a source of error during range estimations. Usually, measurement of the antenna delays is performed separately as a dedicated standalone procedure. Such an additional measurement procedure makes the UWB-based RTLS more tedious with manual interventions. Moreover, the air-time occupancy during the transmission and reception of signaling messages for range estimations between UWB node pairs also limits the serviceable capability of these networks. In this regard, we present a novel simultaneous ranging scheme that requires limited air-time occupancy during range estimations between UWB node pairs and also compensates for the error from the antenna delays. This paper provides a detailed mathematical modeling, system design, and implementation procedure of the proposed scheme. The effectiveness of the proposed scheme for locating a mobile node in an indoor environment is validated through experimental analysis. The results show that, compared to the state-of-the-art two-way ranging (TWR) method, the proposed scheme eliminates the requirement of dedicated standalone antenna delay measurement procedures of the nodes, increases air efficiency through the provision of simultaneous ranging, and provides relative root-mean-square errors (RMSEs) improvement for range and position estimations of approximately 54.52% and 39.96%, respectively.","PeriodicalId":288992,"journal":{"name":"J. Sens. Actuator Networks","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114257984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enabling LPWANs for Coexistence and Diverse IoT Applications in Smart Cities Using Lightweight Heterogenous Multihomed Network Model","authors":"Emmanuel U. Ogbodo, A. Abu-Mahfouz, A. Kurien","doi":"10.3390/jsan11040087","DOIUrl":"https://doi.org/10.3390/jsan11040087","url":null,"abstract":"Smart cities have been envisioned to provide smartness in managing internet of things (IoT) application domains, such as transport and mobility, health care, natural resources, electricity and energy, homes and buildings, commerce and retail, society and workplace, industry, agriculture, and the environment. The growth trajectory in usage of these IoT domains has led to a heterogeneous dense network in a smart city environment. The heterogeneous dense network in smart cities has led to challenges, such as difficulties in the management of LPWAN coexistence, interference, spectrum insufficiency, QoS, and scalability issues. The existing LPWAN technologies cannot support the heterogeneous dense network challenges in smart cities. Further, it cannot support diverse IoT, including medium- to high-bandwidth applications, due to the power, complexity, and resource constraints of the LPWAN devices. Hence, this paper addresses high data rate IoT applications and heterogeneous dense networks. This paper proposes a lightweight heterogenous multihomed network (LHM-N) model for diverse smart city applications that will address dense heterogeneity network challenges in a smart city. The work aims to advocate and integrate a manageable license-free LPWAN that will coexist with 5G private and public cellular networks in the LHM-N model. This will help to provide a cost-effective solution model in a heterogeneous dense smart city environment. Further, a secured lightweight energy-efficient packet-size forwarding engine (PSFE) algorithm is presented using the discrete event simulation (DES) methodological approach in MATLAB for complexity evaluation. In addition, a 5G reduced capability (RedCap) IoT device is integrated into the (LHM-N) model to support smart city. Finally, the results show that the LHM-N model outperforms the conventional quadrature amplitude modulation (QAM) protocol scheme in terms of error rate, latency, and data throughput with reduced energy costs for medium- to high-bandwidth industrial IoT applications. This validates the suitability of the LHM-N model for high data rate IoT applications.","PeriodicalId":288992,"journal":{"name":"J. Sens. Actuator Networks","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128386899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Review of Research on Privacy Protection of Internet of Vehicles Based on Blockchain","authors":"Wendong Chen, Haiqin Wu, Xiao Chen, Jinfu Chen","doi":"10.3390/jsan11040086","DOIUrl":"https://doi.org/10.3390/jsan11040086","url":null,"abstract":"Numerous academic and industrial fields, such as healthcare, banking, and supply chain management, are rapidly adopting and relying on blockchain technology. It has also been suggested for application in the internet of vehicles (IoV) ecosystem as a way to improve service availability and reliability. Blockchain offers decentralized, distributed and tamper-proof solutions that bring innovation to data sharing and management, but do not themselves protect privacy and data confidentiality. Therefore, solutions using blockchain technology must take user privacy concerns into account. This article reviews the proposed solutions that use blockchain technology to provide different vehicle services while overcoming the privacy leakage problem which inherently exists in blockchain and vehicle services. We analyze the key features and attributes of prior schemes and identify their contributions to provide a comprehensive and critical overview. In addition, we highlight prospective future research topics and present research problems.","PeriodicalId":288992,"journal":{"name":"J. Sens. Actuator Networks","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121747684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}