Article
Computer Science, Artificial Intelligence
Xianyu Zhang, Xinguo Ming
Summary: With the advancement of various technologies, the industrial internet has evolved through different stages. However, there is a lack of a comprehensive research framework for studying the top-level planning of the Industrial Internet Platform (IIP). Additionally, there are few studies on the specific path and steps for implementing IIP in specific industries and enterprises.
ADVANCED ENGINEERING INFORMATICS
(2022)
Article
Computer Science, Information Systems
Yawen Tan, Jiadai Wang, Jiajia Liu, Nei Kato
Summary: Blockchain technology can assist in addressing communication security issues for industrial drones, providing distributed and lightweight authentication services to ensure trustworthy communication. The scheme is resistant to various attacks while maintaining low computation and communication costs.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Automation & Control Systems
Geetanjali Rathee, Farhan Ahmad, Naveen Jaglan, Charalambos Konstantinou
Summary: The Industrial Internet-of-Things (IIoT) is a powerful application that revolutionizes the growth of industries by enabling transparent communication among various entities. Data science techniques are introduced to enhance the analysis of collected data in IIoT, addressing the limitations of current distributed architectures. The article tackles the security risks posed by network anomalies/attackers in IIoT through the election of a coordinator IoT device and the integration of a blockchain-based data model, thus increasing network security.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Computer Science, Information Systems
Kai Fan, Zeyu Shi, Ruidan Su, Yuhan Bai, Pei Huang, Kuan Zhang, Hui Li, Yintang Yang
Summary: With the rapid development of IoT, time synchronization in IoT systems has become crucial. This paper proposes a distributed and verifiable time synchronization scheme based on NTP, trust management, and blockchain. It utilizes a public and verifiable blockchain to identify incorrect time synchronization and employs a consensus mechanism based on trust management to resist Byzantine nodes.
PEER-TO-PEER NETWORKING AND APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Mohammad Mehedi Hassan, Md Rafiul Hassan, Shamsul Huda, Victor Hugo C. de Albuquerque
Summary: The article addresses the challenging problem of trust-boundary protection in Industrial Internet of Things environments and proposes a cooperative data generator based on a downsampler-encoder to better capture the distribution of attack models. Experimental results demonstrate that this approach outperforms conventional deep learning and other ML techniques in terms of robustness against adversarial/noisy examples in the IIoT environment.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Xingwei Zhang, Hu Tian, Xiaolong Zheng, Daniel Dajun Zeng
Summary: The robustness of machine learning models in Industrial Internet of Things (IIoT) has gained attention as specific attacks can disturb IIoT monitors designed using ML architectures. Traditional detection methods can fail to prevent attacks, so general robust mechanisms are needed. We designed a robust condition monitor using adversarial training technique called robust temporal convolutional network (RTCN), with a novel false data injection (FDI) attack-generating method that disrupts well-trained monitors. Adversarial training effectively improves the reliability of ML-based IIoT monitors against strong FDI attacks.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Interdisciplinary Applications
Xianyu Zhang, Xinguo Ming
Summary: With the development of industrial Internet environment and intelligent technology, enterprises are focusing more on system platform, information sharing, network collaboration, personalized customization and service recommendation in designing, implementing and operating Industrial Internet Platforms (IIP). However, there is a lack of a comprehensive framework for studying the high-level planning of IIP implementation and few studies on the detailed path and steps of IIP implementation in specific industries. The research aims to study the general model, reference architecture, service evaluation index system, implementation path and application verification for IIP to provide guidance for government and industry in planning, designing, implementing and promoting IIP.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Information Systems
Yinxue Yi, Yangfanyu Yang, Kefei Cheng, Yu Wu, Xiaokang Wang
Summary: This article analyzes a novel information dissemination process with a service-oriented incentive mechanism in IIoT, depicting the dynamic interactions of IIoT devices and verifying the dynamic behaviors of information dissemination through theoretical and simulation results. The service-oriented incentive mechanism drives the participation of IIoT devices and expands information diffusion further.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Zonghang Li, Yihong He, Hongfang Yu, Jiawen Kang, Xiaoping Li, Zenglin Xu, Dusit Niyato
Summary: The Industrial Internet of Things plays a crucial role in industrial intelligence, presenting new challenges for industrial data protection. This article introduces FEDGS, a hierarchical cloud-edge-end FL framework based on 5G, which utilizes clustered devices and synchronization protocols to enhance industrial FL performance on non-i.i.d. data.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Automation & Control Systems
Farva Rafique, Mohammad S. Obaidat, Khalid Mahmood, Muhammad Faizan Ayub, Javed Ferzund, Shehzad Ashraf Chaudhry
Summary: This article introduces a secure multifactor authenticated key agreement scheme for data transmission in the IoT environment. The scheme is resource-efficient and secure, using simple cryptographic operations like XOR and hashing to provide security for legitimate entities.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Automation & Control Systems
Guangyong Gao, Min Wang, Bin Wu
Summary: In this article, an efficient and robust reversible watermarking scheme based on ZMs and integer wavelet transform is proposed for copyright protection of industrial images. The experimental results show that the proposed method has strong ability to restore the original image and robustness against various attacks.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Automation & Control Systems
Jiale Zhang, Chunpeng Ge, Feng Hu, Bing Chen
Summary: This article proposes a robust federated learning method named RobustFL to defend against poisoning attacks in Industrial Internet of Things (IIoT) systems. The method builds a predictive model and trains the federated model using adversarial training to mitigate the influence of malicious participants.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Engineering, Electrical & Electronic
Made Adi Paramartha Putra, Ade Pitra Hermawan, Dong-Seong Kim, Jae-Min Lee
Summary: This article presents an energy-efficient IIoT architecture that minimizes data transmission based on sensor data prediction. The proposed DC-MLP model successfully reduces energy consumption by up to 33% compared with traditional data transmission, while achieving an 81% faster prediction time than existing DL models.
IEEE SENSORS JOURNAL
(2023)
Article
Automation & Control Systems
Wenliang Mao, Zhiwei Zhao, Zheng Chang, Geyong Min, Weifeng Gao
Summary: This article presents a comprehensive survey on energy-efficient communications and computation mechanisms in IIoT systems, categorizing, reviewing, discussing, and comparing existing works to explore their pros and cons. The open issues and research challenges in the context of recent 5G communications and edge computing trends are also discussed.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Computer Science, Information Systems
Diksha Rangwani, Dipanwita Sadhukhan, Sangram Ray, Muhammad Khurram Khan, Mou Dasgupta
Summary: Wireless sensor networks play a key role in the Industrial Internet of Things, facilitating remote monitoring and analysis of data to ensure security and privacy protection. A robust provable-secure privacy-preserving three-factor authentication protocol is proposed to prevent security threats in the IIoT environment.
PEER-TO-PEER NETWORKING AND APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Amir Javadpour, Samira Rezaei, Arun Kumar Sangaiah, Adam Slowik, Shadi Mahmoodi Khaniabadi
Summary: This study utilizes QoSR-PSO algorithm to improve QoS in vehicular ad hoc networks. By employing particle swarm optimization, the best solution is found. NS2 simulator and VanetMobisim are used for simulation experiments. The comparison results indicate improvements in packet delivery rate, delay, packet drop, and overload.
Article
Computer Science, Theory & Methods
Haroon Wahab, Irfan Mehmood, Hassan Ugail, Arun Kumar Sangaiah, Khan Muhammad
Summary: Video capsule endoscopy (VCE) is a revolutionary technology for early diagnosis of gastric disorders, but manual interpretation of VCE videos is time-consuming due to the high redundancy and subtle manifestation of anomalies. Several machine learning methods have been adopted to improve VCE analysis, but their clinical impact is yet to be explored. This survey aimed to bridge the gap between existing ML-based research and clinically significant rules established by gastroenterologists. A framework for interpreting raw frames and merging findings with meta-data was proposed. The challenges and opportunities for VCE analysis were discussed, and the importance of maximizing the discriminative power of features, creating large datasets, and ensuring explainability and reliability of ML-based diagnostics in VCE was emphasized.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2023)
Article
Automation & Control Systems
Amir Javadpour, Arun Kumar Sangaiah, Forough Jafari, Pedro Pinto, Hamidreza Memarzadeh-Tehran, Samira Rezaei, Fatemeh Saghafi
Summary: Monitoring security and quality of service in wireless networks, especially in wireless body area networks (WBANs), is crucial due to the rapid growth of nodes and the direct impact on patients' and scientists' health. This article comprehensively reviews MAC protocols in WBANs, comparing time-based, contention-based, and hybrid protocols in terms of MQoS and security vulnerabilities. The study reveals a research gap in addressing security and privacy issues in MAC layer protocols, highlighting the need for a secure MAC protocol to enhance MQoS in WBANs.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Automation & Control Systems
Yinzhi Lu, Liu Yang, Simon X. Yang, Qiaozhi Hua, Arun Kumar Sangaiah, Tan Guo, Keping Yu
Summary: The edge-enabled Industrial Internet of Things (IIoT) platform is crucial in the acceleration of smart industry development. However, as real-time IIoT applications increase, it becomes challenging to achieve fast response time, low latency, and efficient bandwidth utilization. To address this issue, researchers have recently studied time-sensitive network (TSN) to enable low latency communication through deterministic scheduling. This article analyzes the combinability problem and proposes the noncollision theory-based deterministic scheduling (NDS) method for achieving ultralow latency communication for time-sensitive flows. Additionally, a dynamic queue scheduling (DQS) method is presented to improve bandwidth utilization for best-effort flows. Experimental results demonstrate the effectiveness of NDS/DQS in supporting deterministic ultralow latency services and efficient bandwidth utilization.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Automation & Control Systems
Kaixiang Yang, Yifan Shi, Zhiwen Yu, Qinmin Yang, Arun Kumar Sangaiah, Huanqiang Zeng
Summary: With the development of Industry 4.0, industrial Big Data has become essential in the Industrial Internet of Things. Intelligent anomaly detection, which is challenging, is still a crucial issue in industrial cyber-physical systems. This article presents a new alternative solution for network intrusion detection in Industry 4.0 through the development of the one-class broad learning system (OCBLS) and the stacked OCBLS (ST-OCBLS) algorithms.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Computer Science, Artificial Intelligence
Wenhui Bai, Chao Zhang, Yanhui Zhai, Arun Kumar Sangaiah
Summary: Water quality inspection is essential for the safe utilization of water resources, and complex data modeling and analysis are crucial in finding the best water quality resources. However, challenges such as missing data, differences in decision results, and bounded rationality of decision-makers still exist in water quality inspection. Therefore, this paper proposes a comprehensive multi-attribute group decision-making approach for water quality inspection based on stable and behavioral decision-making in multi-granularity incomplete intuitionistic fuzzy information systems.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2023)
Article
Computer Science, Interdisciplinary Applications
Raheleh Khanduzi, Arun Kumar Sangaiah
Summary: This study proposes a robust and efficient recurrent neural network (RNN) for solving the continuous defensive location problem (CDLP). The RNN shows promising results with good execution time and precision, outperforming previous methods such as tabu search, imperialist competitive algorithm, and hybrid algorithms. It successfully stops the attacker at a further distance from the core compared to other methods.
JOURNAL OF COMPUTATIONAL SCIENCE
(2023)
Editorial Material
Chemistry, Multidisciplinary
Xiaochun Cheng, Ding-Zhu Du, Arun Kumar Sangaiah, Rongxing Lu
APPLIED SCIENCES-BASEL
(2023)
Article
Engineering, Civil
Farimasadat Miri, Amir Javadpour, Forough Ja'fari, Arun Kumar Sangaiah, Richard Pazzi
Summary: With the increasing popularity of interconnected Vehicular ad-hoc networks (VANET) and intelligent transportation systems, the importance of maintaining acceptable levels of Quality of Service (QoS) and Quality of Experience (QoE) in time sensitive applications is crucial. Allocating the right number of resources in a distributed manner to avoid congestion and fill deficiencies is a challenging issue. Vehicle networks play a significant role in providing safety, comfort, and entertainment, making them a compelling research topic in intelligent transportation systems.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Chemistry, Analytical
Arun Kumar Sangaiah, Amir Javadpour, Pedro Pinto, Haruna Chiroma, Lubna A. Gabralla
Summary: This research aims to develop an intelligent system to handle approximate set-value inquiries. The proposed method enhances the system's intelligence through particle optimization without the use of sampling. The results demonstrate significant improvements in terms of the number of queries, peers examined, and execution time.
Article
Computer Science, Information Systems
Jie Wang, Ying Jia, Arun Kumar Sangaiah, Yunsheng Song
Summary: Network clustering is an important research area for mining protein complexes from protein-protein interaction networks. This paper proposes a network clustering algorithm for protein complex detection fused with the power-law distribution characteristic. Experimental results show that the algorithm can effectively detect protein complexes and outperforms other comparative algorithms.
Article
Business
Arun Kumar Sangaiah, Amir Javadpour, Forough Ja'fari, Pedro Pinto, Huan-Ming Chuang
Summary: The government and industry attach great importance to the development of IoT in the healthcare sector. Healthcare data collected by service providers are valuable for patient diagnostics and analysis, but they contain sensitive personal information that needs to be protected. Privacy protection is crucial for individuals and organizations, especially when user data is sent to data centers for mining.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2023)
Article
Computer Science, Cybernetics
Ying Ma, Chuyi Yu, Ming Yan, Arun Kumar Sangaiah, Youke Wu
Summary: The accessibility of mobile apps is important for visually impaired smartphone users. However, most app icons lack natural language labels, making it challenging for these users to engage with mobile phones. COALA is a solution that generates textual labels from imaging icons and addresses this issue. Our interconnected two-stream language model with mean teacher learning outperforms previous single-language models on low-resource datasets and significantly decreases the dark side of the socio-cyber world.
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
(2023)
Article
Computer Science, Information Systems
Jian Peng, Yifang Zhao, Dengyong Zhang, Feng Li, Arun Kumar Sangaiah
Summary: This paper presents a new feature extraction strategy named DSAFF-Net, which includes three parts: SAFF module, D-block, and experimental validation. The experimental results demonstrate that this strategy can significantly improve the accuracy of COVID-19 image classification and small object detection.
CMC-COMPUTERS MATERIALS & CONTINUA
(2023)
Article
Business
Liangyan Wang, Brian Wu, Cornelia Pechmann, Yitong Wang
Summary: Research shows that the effects of creative imitation on the originals depend on the quality of the imitation. Low-quality creative imitation increases satisfaction with and choice of the original, while moderate-quality creative imitation does the opposite.
STRATEGIC MANAGEMENT JOURNAL
(2023)
