Pub Date : 2023-09-01DOI: 10.1109/iotm.001.2300013
Amit Chougule, Kartik Agrawal, Vinay Chamola
In recent years, significant research has occurred on developing various protocols for communication within an autonomous vehicle. Due to the simplicity and trustworthiness of a Controller Area Network (CAN) bus, it has become trendy and widely employed for in-vehicle communication. However, research indicates numerous network-level threats are possible owing to the CAN bus's lack of defense mechanisms. Messages are prone to attacks from third-party sources threatening the correctness of the CAN bus messages. In the last few years, machine learning and deep learning algorithms have effectively improved CAN security and developed various misbehavior, intrusion prevention, and detection systems. However, a large amount of data is required to train these algorithms. There are currently very few CAN datasets available, which has become a major barrier for researchers when developing new CAN security algorithms. Also, the nature of the data in question is tedious to accumulate, especially if there is a need for specific features. In this work, we proposed SCAN-GAN (Synthetic CAN), a generative adversarial Network (GAN) based technique to generate data using existing collected data and presented a synthetic CAN dataset. We also compared the original and generated dataset based on various parameters as well as on well-known classification algorithms, showing that various previous models deliver improved results on the generated dataset over the original dataset. The results exhibit the efficiency of using GANs for data production, which is on par with real data. The results of this work also suggest the adaptability of the GAN to work with varied datasets.
{"title":"SCAN-GAN: Generative Adversarial Network Based Synthetic Data Generation Technique for Controller Area Network","authors":"Amit Chougule, Kartik Agrawal, Vinay Chamola","doi":"10.1109/iotm.001.2300013","DOIUrl":"https://doi.org/10.1109/iotm.001.2300013","url":null,"abstract":"In recent years, significant research has occurred on developing various protocols for communication within an autonomous vehicle. Due to the simplicity and trustworthiness of a Controller Area Network (CAN) bus, it has become trendy and widely employed for in-vehicle communication. However, research indicates numerous network-level threats are possible owing to the CAN bus's lack of defense mechanisms. Messages are prone to attacks from third-party sources threatening the correctness of the CAN bus messages. In the last few years, machine learning and deep learning algorithms have effectively improved CAN security and developed various misbehavior, intrusion prevention, and detection systems. However, a large amount of data is required to train these algorithms. There are currently very few CAN datasets available, which has become a major barrier for researchers when developing new CAN security algorithms. Also, the nature of the data in question is tedious to accumulate, especially if there is a need for specific features. In this work, we proposed SCAN-GAN (Synthetic CAN), a generative adversarial Network (GAN) based technique to generate data using existing collected data and presented a synthetic CAN dataset. We also compared the original and generated dataset based on various parameters as well as on well-known classification algorithms, showing that various previous models deliver improved results on the generated dataset over the original dataset. The results exhibit the efficiency of using GANs for data production, which is on par with real data. The results of this work also suggest the adaptability of the GAN to work with varied datasets.","PeriodicalId":235472,"journal":{"name":"IEEE Internet of Things Magazine","volume":"198 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135388231","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}
Pub Date : 2023-09-01DOI: 10.1109/miot.2023.10255778
{"title":"Cover 2","authors":"","doi":"10.1109/miot.2023.10255778","DOIUrl":"https://doi.org/10.1109/miot.2023.10255778","url":null,"abstract":"","PeriodicalId":235472,"journal":{"name":"IEEE Internet of Things Magazine","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135388389","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}
Pub Date : 2023-09-01DOI: 10.1109/miot.2023.10255725
{"title":"Cover 3","authors":"","doi":"10.1109/miot.2023.10255725","DOIUrl":"https://doi.org/10.1109/miot.2023.10255725","url":null,"abstract":"","PeriodicalId":235472,"journal":{"name":"IEEE Internet of Things Magazine","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135388596","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}
Pub Date : 2023-09-01DOI: 10.1109/iotm.001.22002358
Guan-Yu Lin, Chia-Hao Yu, Nathan Tenny, Alex C.-C. Hsu
A significant challenge to support throughput-hungry internet of thing (IoT) applications is to satisfy the requirement of high data rate using cost-efficient IoT devices in 5G cellular network. To address this challenge, we propose to deploy high-capability relay devices nearby cost-efficient IoT devices. By exploiting the higher transmission/reception capability of the relay device, IoT devices in cell edge can reach boosted throughput even though the relay device introduces additional latency for decode-and-forward. Moreover, we propose the multi-path scheme and uplink (UL)/SL resource sharing scheme to further boost throughput when SL resource is relatively insufficient, wherein SL resource is the resource for communications between IoT devices and their IoT Gateway. Simulation results show that the proposed scheme multiplies throughput for cell-edge IoT devices and can enhance throughput for cell-center IoT devices as well when the system traffic load is high.
{"title":"On Advanced Relay Schemes to Support Throughput-Hungry IoT Applications","authors":"Guan-Yu Lin, Chia-Hao Yu, Nathan Tenny, Alex C.-C. Hsu","doi":"10.1109/iotm.001.22002358","DOIUrl":"https://doi.org/10.1109/iotm.001.22002358","url":null,"abstract":"A significant challenge to support throughput-hungry internet of thing (IoT) applications is to satisfy the requirement of high data rate using cost-efficient IoT devices in 5G cellular network. To address this challenge, we propose to deploy high-capability relay devices nearby cost-efficient IoT devices. By exploiting the higher transmission/reception capability of the relay device, IoT devices in cell edge can reach boosted throughput even though the relay device introduces additional latency for decode-and-forward. Moreover, we propose the multi-path scheme and uplink (UL)/SL resource sharing scheme to further boost throughput when SL resource is relatively insufficient, wherein SL resource is the resource for communications between IoT devices and their IoT Gateway. Simulation results show that the proposed scheme multiplies throughput for cell-edge IoT devices and can enhance throughput for cell-center IoT devices as well when the system traffic load is high.","PeriodicalId":235472,"journal":{"name":"IEEE Internet of Things Magazine","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135388381","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}
Pub Date : 2023-09-01DOI: 10.1109/iotm.001.2300091
Chung G. Kang, Ameha Tsegaye Abebe, Jinho Choi
From a system-level point of view, a grant-free random access protocol for latency critical internet of thing (IoT) must be designed to trade resource efficiency and target performance in a scalable manner. To this end, its performance characteristics must be fully understood by identifying the underlying physical-layer structure and constraints. In this article, we present a comprehensive structure of contention transmission unit for grant-free random access that employs a multi-signature spreading to average out multi-user interference subject to non-or-thogonal multiple access (NOMA). This structure is shown to trade preamble collision and activity detection failure optimally to achieve a target performance with the given physical resources at a varying level of user activity. Furthermore, as spectral efficiency and delay requirements are mainly governed by reliability of random access, we will discuss multiple receiver antenna-based approaches that play a crucial role in improving the reliability and supporting massive connectivity. The scalable and reliable features in all these aspects will become a useful part of the design framework for low latency and massive connectivity of 6G IoT applications.
{"title":"NOMA-Based Grant-Free Massive Access for Latency-Critical Internet of Things: A Scalable and Reliable Framework","authors":"Chung G. Kang, Ameha Tsegaye Abebe, Jinho Choi","doi":"10.1109/iotm.001.2300091","DOIUrl":"https://doi.org/10.1109/iotm.001.2300091","url":null,"abstract":"From a system-level point of view, a grant-free random access protocol for latency critical internet of thing (IoT) must be designed to trade resource efficiency and target performance in a scalable manner. To this end, its performance characteristics must be fully understood by identifying the underlying physical-layer structure and constraints. In this article, we present a comprehensive structure of contention transmission unit for grant-free random access that employs a multi-signature spreading to average out multi-user interference subject to non-or-thogonal multiple access (NOMA). This structure is shown to trade preamble collision and activity detection failure optimally to achieve a target performance with the given physical resources at a varying level of user activity. Furthermore, as spectral efficiency and delay requirements are mainly governed by reliability of random access, we will discuss multiple receiver antenna-based approaches that play a crucial role in improving the reliability and supporting massive connectivity. The scalable and reliable features in all these aspects will become a useful part of the design framework for low latency and massive connectivity of 6G IoT applications.","PeriodicalId":235472,"journal":{"name":"IEEE Internet of Things Magazine","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135388383","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}
Ubiquitous intelligence empowered internet of vehicles (UIIoV) is an emerging paradigm where network entities such as mobile vehicles, edge/cloud servers, and intermediate nodes interact to achieve effective data sensing and make intelligent decisions based on artificial intelligence techniques. Unlike the conventional internet of vehicles, artificial intelligence is introduced to improve the ability of data processing and analysis, and further enhance the accuracy of decision-making. In this article, we study the architecture of UIIoV, and the security, privacy, and reliability challenges it confronts. To be specific, we start by describing the overall infrastructure, exploring the security, privacy, and reliability demands of UIIoV, and further give state-of-the-art solutions to enable security guarantees, privacy protection, and prediction reliability. Finally, this article presents several promising future research directions to hopefully attract more attention to this emergent field.
{"title":"Security, Privacy, and Reliability in Ubiquitous Intelligence Empowered Internet of Vehicles","authors":"Chuan Zhang, Chenfei Hu, Weiting Zhang, Haotian Liang, Dian Lei, Liehuang Zhu","doi":"10.1109/iotm.001.2300075","DOIUrl":"https://doi.org/10.1109/iotm.001.2300075","url":null,"abstract":"Ubiquitous intelligence empowered internet of vehicles (UIIoV) is an emerging paradigm where network entities such as mobile vehicles, edge/cloud servers, and intermediate nodes interact to achieve effective data sensing and make intelligent decisions based on artificial intelligence techniques. Unlike the conventional internet of vehicles, artificial intelligence is introduced to improve the ability of data processing and analysis, and further enhance the accuracy of decision-making. In this article, we study the architecture of UIIoV, and the security, privacy, and reliability challenges it confronts. To be specific, we start by describing the overall infrastructure, exploring the security, privacy, and reliability demands of UIIoV, and further give state-of-the-art solutions to enable security guarantees, privacy protection, and prediction reliability. Finally, this article presents several promising future research directions to hopefully attract more attention to this emergent field.","PeriodicalId":235472,"journal":{"name":"IEEE Internet of Things Magazine","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135388390","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}
Pub Date : 2023-09-01DOI: 10.1109/miot.2023.10255789
{"title":"IEEE App","authors":"","doi":"10.1109/miot.2023.10255789","DOIUrl":"https://doi.org/10.1109/miot.2023.10255789","url":null,"abstract":"","PeriodicalId":235472,"journal":{"name":"IEEE Internet of Things Magazine","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135388396","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}
Pub Date : 2023-09-01DOI: 10.1109/miot.2023.10255783
{"title":"Women in Engineering","authors":"","doi":"10.1109/miot.2023.10255783","DOIUrl":"https://doi.org/10.1109/miot.2023.10255783","url":null,"abstract":"","PeriodicalId":235472,"journal":{"name":"IEEE Internet of Things Magazine","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135388589","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}
Pub Date : 2023-09-01DOI: 10.1109/iotm.001.2300067
Yilong Hui, Yi Qiu, Zhou Su, Zhisheng Yin, Tom H. Luan, Khalid Aldubaikhy
With the rapid development of 6G, the intelligent space-air-ground integrated vehicular network (ISAGIVN) has been proposed to efficiently provide vehicles with ubiquitous services. Faced with the new features such as massive nodes, heterogeneous networks, and diverse data presented by the ISAGIVN, a new network architecture is urgently needed to enhance the flexibility of the network, the efficiency of decision-making and the orderliness of data management. In this article, we design a digital twin (DT)-enabled architecture to facilitate the practical deployment and application of ISAGIVN. We first review the conventional network architecture of ISAGIVN. Then, we discuss the challenges of combining DTs and ISAGIVN. On this basis, we design the framework of DT-enabled ISAGIVN, where the creation, deployment, update and migration of DTs in ISAGIVN are analyzed in detail. Finally, we conclude the article and discuss future research directions.
{"title":"Digital Twins for Intelligent Space-Air-Ground Integrated Vehicular Network: Challenges and Solutions","authors":"Yilong Hui, Yi Qiu, Zhou Su, Zhisheng Yin, Tom H. Luan, Khalid Aldubaikhy","doi":"10.1109/iotm.001.2300067","DOIUrl":"https://doi.org/10.1109/iotm.001.2300067","url":null,"abstract":"With the rapid development of 6G, the intelligent space-air-ground integrated vehicular network (ISAGIVN) has been proposed to efficiently provide vehicles with ubiquitous services. Faced with the new features such as massive nodes, heterogeneous networks, and diverse data presented by the ISAGIVN, a new network architecture is urgently needed to enhance the flexibility of the network, the efficiency of decision-making and the orderliness of data management. In this article, we design a digital twin (DT)-enabled architecture to facilitate the practical deployment and application of ISAGIVN. We first review the conventional network architecture of ISAGIVN. Then, we discuss the challenges of combining DTs and ISAGIVN. On this basis, we design the framework of DT-enabled ISAGIVN, where the creation, deployment, update and migration of DTs in ISAGIVN are analyzed in detail. Finally, we conclude the article and discuss future research directions.","PeriodicalId":235472,"journal":{"name":"IEEE Internet of Things Magazine","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135388593","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}
Pub Date : 2023-09-01DOI: 10.1109/iotm.001.2200272
Shih-Chun Lin, Chia-Hung Lin, Liang C. Chu, Shao-Yu Lien
Low earth orbit (LEO) mega-constellations, integrating government space systems and commercial practices, become enabling technologies for the sixth generation (6G) networks due to their excellent merits of global coverage and ubiquitous services for military and civilian use cases. However, convergent LEO-based satellite networking infrastructures lack leveraging the synergy of space and terrestrial systems. This paper extends conventional cloud platforms with serverless edge learning architectures for 6G satellite swarm ecosystems and provides a new distributed training design from a networking perspective. The proposed method dynamically orchestrates communications, computation functionalities, and resources among heterogeneous physical units to efficiently fulfill multi-agent deep reinforcement learning for service-level agreements. Innovative ecosystem enhancements, including ultra-broadband access, anti-jamming transmissions, resilient networking, and related open challenges, are investigated for end-to-end connectivity, communications, and learning performance.
{"title":"Enabling Resilient Access Equality for 6G LEO Satellite Swarm Networks","authors":"Shih-Chun Lin, Chia-Hung Lin, Liang C. Chu, Shao-Yu Lien","doi":"10.1109/iotm.001.2200272","DOIUrl":"https://doi.org/10.1109/iotm.001.2200272","url":null,"abstract":"Low earth orbit (LEO) mega-constellations, integrating government space systems and commercial practices, become enabling technologies for the sixth generation (6G) networks due to their excellent merits of global coverage and ubiquitous services for military and civilian use cases. However, convergent LEO-based satellite networking infrastructures lack leveraging the synergy of space and terrestrial systems. This paper extends conventional cloud platforms with serverless edge learning architectures for 6G satellite swarm ecosystems and provides a new distributed training design from a networking perspective. The proposed method dynamically orchestrates communications, computation functionalities, and resources among heterogeneous physical units to efficiently fulfill multi-agent deep reinforcement learning for service-level agreements. Innovative ecosystem enhancements, including ultra-broadband access, anti-jamming transmissions, resilient networking, and related open challenges, are investigated for end-to-end connectivity, communications, and learning performance.","PeriodicalId":235472,"journal":{"name":"IEEE Internet of Things Magazine","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135889564","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}
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