The workshop welcomes high quality submissions on methods and technologies that enable the development of the next generation of mobile Internet, cloud computing and information security.
Title: Sustainable Development of Smart Cities with Cognitiveness of 5G Technology and Beyond
The main objective of this logical exploration is to analyze the job of Information & Communication Technologies (ICTs) in the sustainable development of smart cities toward futuristic communication. Along these lines, we have involved expressive examination and basic near investigation to feature the effect of the new age of 5G and beyond advancements on the shrewd improvement of the fundamental regions that structure the design of a city. The fundamental aftereffects of this logical article have shown that the advantages of incorporating 5G innovation are unequivocal for the smart comprehensive, and long haul improvement of a city overall, however, to economically profit from these, it is basic that urban areas/states make a productive execution structure as far as a mechanical framework, human resources, advancement, inside guidelines, and clients.
This workshop basically focus on :
1.D2D Communication
2.Tera Hertz Antenna
3.IoT Enabled to Smart Cities
4.Smart Transportation
5.Industrial Transformation
6.Smart Health Sector
5G; smart cities;  network capacity; energy efficiency,;massive MIMO; QoE

Chair: Devasis Pradhan | Acharya Institute of Technology
Prof. Devasis Pradhan currently working as an Assistant Professor |ResearchCoordinator in the Department of Electronics & Communication Engineering at Acharya Institute of Technology, Bengaluru, Karnataka from 2017 onwards. Hiscurrent research includes the effectiveness of 5G-Green Communications, mmWave antenna design, UWB antennas, and its implementation. He published 50 researchpapers in eminent international journals & conferences, 4 books and 3 Edited Bookswith a reputed publishing house. He is co-editor in Editorial Board & Peer-review of8 International Journal and committee member in the much-reputed organization. Hehas authored o co-authored 10 Book Chapters. He has been a Technical CommitteeMember and Reviewer for a reputed internal conference such as IEEE, Grenz Society,IFERP, etc; He has received 6 National Awards in the field of Academic and Researchwork from various governing bodies associated with the government of India. He isalso an active member of ISTE, IEEE, ATMS, and other professional associationstoward professional growth.
Title: Privacy and Security Technology in Evolving IoT
Owing to rapid technical development, many devices in the Internet of Things (IoT) environment, such as sensors, embeddedand mobile devices can receive huge amounts of information through data exchanging and interconnection. It is important to preserve individual privacy and secure the shared data. In addition, emergence of some new technologies(SDN, deep learning) also provides a new solution to the security strategy in the Internet of Things (IoT) environment. Thus, privacy and security has attracted a great deal of attention and research issues in recent decades. Many security solutions have recently been discussed for the IoT environment. Since many criteria and parameters must be considered with regard to privacy and security issues, it is critical to discuss and develop new methodologies and techniques by adopting evolutionary computations. The objective of this workshop on “Security and Privacy Techniques in Evolving IoT” is to compile recent research efforts dedicated to studying and developing security and privacy issues related to IoT devices and the IoT environment. 
The workshop solicits high quality and unpublished work on recent advances in new methodologies for security and privacy solutions, and theories and technologies proposed to defend IOT-oriented applications against adversarial or malicious attacks. The topics of interest include, but are not limited to:
  • Innovative techniques for IoT infrastructure security
  • Internet of Things (IoT) devices and protocols security
  • Attacks detection methodsfor Internet of Things (IoT)devices
  • Cloud computing-based security solutions for IoT data
  • SDN-based security solutions for IoT data
  • Security and privacy frameworks for IoT-based smart agricultures
  • Security and privacy frameworks for IoT-based smart cities
  • Critical infrastructures resilience and security in smart cities
  • Biometric modalities involved in IoT security for smart cities
  • Interoperable security for urban planning and applications
  • Security challenges and mitigation approaches for smart cities
  • Cyber attacks detection and prevention systems for IoT networks
IoT, privacy and security, data sharing, preservation

Chair: Dong Shi | Zhoukou Normal University
Dong Shi received Ph.D in computer science from southeast university in 2013. He is a visiting scholar in Washington University in St.Louis and a distinguished professor with Zhoukou Normal University. He has published more than 100 papers in top conferences and journals. He is a reviewer of IEEE Transactions on Parallel and Distributed Systems, IEEE/ACM Transactions on Networking; Computer Networks; IEEE Transactions on Network Science and Engineering; IEEE Transactions on Industrial Informatics; IEEE Internet of Things Journal. He also is an associate editor for IEEE Systems Journal, IET Wireless Sensor Systems, IET Networks, IEICE Transactions on Communications, and International Journal on Artificial Intelligence Tools. His major interests are network management, network security.
Title: Computer Vision for Intelligent Scene Perception
Visual understanding and multi-modality representation fusion are essential to intelligent scene perception. With the rapid progress in machine learning technologies, there are tons of remarkable advances in intelligent scene understanding, whose performance and application fields are extended greatly. However, the complexity of scene could be a challenge for efficient perception. For some application as automatic drive, pedestrian re-identification and robot tracking, the performance and efficiency are typically affected by disturbances in the natural scene. How to efficiently combine information from visual and other modalities to enhance the robustness of perception systems under accidental perturbation and complexity issues is crucial and meaningful.
This workshop aims to bring together the research accomplishments provided by researchers from academia and the industry. The other goal is to show the latest research results in the field of intelligent scene perception. We encourage prospective authors to submit related distinguished research papers on the subject of both: theoretical approaches and practical case reviews.
Computer Vision, Multi-modality Representation Learning, Intelligent Scene Perception and Application, Person re-identification, Deep Learning.

Chair: Zhigang Liu Northeast Petroleum University
Zhigang Liu, received a Ph.D. degree in Computer Resources and Information Engineering from Northeast Petroleum University, and was a visiting scholar with the Department of Electrical & Computer Engineering at National University of Singapore from 2018 to 2019. As a senior CCF member, he is currently the Department Director of Computer Science and Engineering, Northeast Petroleum University. His research interests include machine learning, computer vision, especially, data/label- and computation-efficient deep learning for visual recognition.
He participated in the National Natural Science Foundation, Natural Science Foundation of Heilongjiang Province, Scientific and Technological Projects of Petro-China, and Youth Science Foundation of Northeast Petroleum University. Based on these projects, he published many academic papers.
Title: Complex System Modeling and Its Digital Solutions
Logistics industry is a pillar industry related to the national economy. Its inefficient (not enough to information building) and disordered (not strong to intensive degree) operation is an important reason for the slow decline of China's logistics GDP (14.6%) into the bottleneck period, so that there is a significant gap compared with advanced logistics countries (GDP (8~9%)). In order to meet the needs of the digital development for the national logistics industry and break through the above bottlenecks, this project focuses on the land transportation segment of "Depot - Vehicle dispatching – Order delivery",with " formalizing mathematical description problem for the normal mode modern logistics ", "vehicle dispatching/order delivery in multi-goal/multi-constraint/multi-element optimization algorithm" and "building high-speed/high-accuracy vehicle dispatching/order delivery support system " of these three scientific problems on theory and application technology research, aiming to make achievements in mathematical modeling (discrete mathematical description), core algorithm (intelligent calculation of multi-level mixed data structure) and application development (constructing of vehicle dispatching/order delivery support system); The research carries out the above research plan with 11 detailed steps; Fulfillingthe great vision of digitalization/precision/intelligence/efficiency/low-carbonization, and contributes to the huge needs of delicacy management and high-quality development of logistics industry; At the same time, it is expected to use for reference to the related areas such as cargo and shipping.
Complex system modeling & optimization; Intelligent computing; Decision support; Fuzzy inference;

Chair: Kewei Chen | Ningbo University
Dr. Kewei Chen received his Ph.D. degree from Tokyo Institute of Technology in 2000, and was recognized and funded by IPA software in 2001. In 2002, he won the Prize of Excellent Paper in Fuzzy Science of Japan. In the past 25 years, he has participated in 19large-scale scientific research projects (7 of which are the core technology leaders) and published 26core papers in international top journals and international conferences. In 2018, as a high-level leading talent recruited by the Organization Department of Yuyao-city, Ningbo, Dr. Chen settled in two enterprises, Ningbo Intelligent Manufacturing Industry Research Institute(Robot Innovation Center)and Danian Technology Group, after that,successfully applied for national distinguishedexpert. In January 2020, he joined Ningbo University and worked as a distinguished professor in school of Mechanical Engineering and Mechanics, specializing in intelligent manufacturing and robot teaching and research. In March 2021, he was appointed as the director of the Institute of Advanced Intelligent Robots.
Title: The Emerging Digital Twin Ecosystem
With the deeper penetration of digital technologies in our day-to-day activities, there is a boost in the wellness and quality of our lives. As technologies are converging with each other to create a sophisticated application, they bring in new challenges and benefits. The future of these applications depends upon the development of smarter computational models that can tackle these new challenges and provide optimized performance. Digital Twin (DT) is a promising approach to accomplish such a convergence. The twining of a physical object to its counterpart in the digital metaverse not only enables to monitor the state of the object but also helps to improve its performance and predict its future state. The understanding, creation, and practice of DTs are inseparable from the underlying physical objects, applications, and user demands. By collecting real-time data from the observation sensors embedded on the object, DTs use technologies such as the Internet of Things, Data Aggregation, Cloud Computing, Artificial Intelligence, Machine Learning, and others to realize the evaluation of the current object’s state, as well as an accurate prediction of the future states. As an emerging field, the research and implementation of critical technologies of DT need standardized architecture, well-defined protocols, optimized solutions, and best practices. This workshop aims to bring together researchers and visionaries from academia and industry to share their recent findings on the topic of DTs. We seek paper submission in the following relevant topics, but not limited to. • Use-case scenarios and innovative DT applications 
• Industrial IoT and DTs 
• Cognitive Computing, Machine Learning & AI for DTs 
• DT product development & maintenance 
• Digital Twinning vs. Augmented Reality 
• Asset management through DTs 
• Network security of digital metaverse of DTs
• Cyber-Physical System of DT 
• Information security and privacy of DTs 
• Communications technologies for enabling DT 
• System architectures for digital twins 
• Quality assurance techniques for DT 
• Interfaces to enable data flow between DT subsystems
Use-case Scenarios, Digital Twin Adoption, Deployment Challenges, Security and Privacy Risks

Chair: Santosh Pattar | KLE Technological University
Santosh Pattar received the Ph. D. degree from University Visvesvaraya College of Engineering, India in 2021 and the Masters of Engineering degree from the same institution in 2015. He is currently working as Assistant Professor in the Department of Computer Science and Engineering at KLE Technological University, Belagavi, India. He is a data-driven IoT researcher and his research work focuses on developing efficient mechanisms for resource discovery in an IoT ecosystem. Also, at present he is working on a multitude of topics in deep learning techniques and their application to IoT and disease diagnosis; biological network alignment and its application in bioinformatics. He has authored and published papers on the above topic in refereed international journals and international conferences. He has also served as conference session chair and given several invited talks at various workshops and conferences. He serves on the review panel of several high-impact journals and conference such as IEEE Communications Magazine; IEEE Transactions on Industrial Informatics; Information Sciences, Elsevier; Future Generation Computer Systems, Elsevier; Swarm and Evolutionary Computation, Elsevier, IEEE WiECON ECE, ICInPro and etc.
Title: Optimization of Resources in Cloud Based Data Center
Cloud Computing is the most advance computation technology of this era. Compute Virtualization is the key piler on which cloud computing is sustained. To sustain it many factors, play a vital role in its optimization, that includes task scheduling, resource management, efficient bandwidth utilization for horizontal traffic in datacenters etc. Many algorithms have been proposed to achieve efficient task scheduling, however the machine learning based algorithms are playing an evolutionary role nowadays to improve resource management and task scheduling and optimize its other factors like QOS, Energy consumption and bandwidth utilization.
This workshop mainly focuses on following areas related to optimization:
1.Task Scheduling algorithms
2.Machine learning techniques-based optimization in Task Scheduling
3.Block Chain based resource scheduling
4.Optimized VM allocation algorithm
5.Energy efficient algorithm for scheduling.
Cloud Computing, Virtualization, task Scheduling, resource management, datacenter, Virtual machine migration

Chair: Zeshan Iqbal | University of Engineering and Technology Taxila
Prof. Dr. Zeshan Iqbal is currently working as an Assistant Professor in the Department of Computer Science at University of Engineering and Technology (UET) Taxila, Punjab, Pakistan. He joined UET in 2015. His current research includes the Compute Virtualization, Software Defined Networks and Adhoc Networks. He published more that 40 papers in eminent international journals and conferences. He is a reviewer and guest editor in 05 different Journals. He has been a Technical Member and reviewer for a reputed internal conference such as IEEE, ACM, etc. He is also an active member of IEEE, ISOC Chapters, IET, CSTA and IACSIT.
Title: Quality of Experience for cloud computing services
Quality of Experience (QoE) is data about users’ perceptions of using cloud services. Cloud service providers deliver services such as storage, computation, streaming of gaming, and multimedia content to users on their demands. Researchers are working on emerging technologies such as cloud computing, fog computing, 5G/network management, Internet of Things (IoT), and multimedia streaming to improve the services. Previously quality of service (QoS) parameters was used to upgrade services and provide services but user feedback was never considered for service provision. Quality of experience (QoE) was introduced to assess user satisfaction levels and upgrade and manage services according to QoE. 
The workshop will focus on the new metrics of QoE, data collection methods and analysis, and the contribution of researchers and experts around the world on QoE in cloud computing research. The topics of interest include, but are not limited to: 
QoE/QoS in Cloud/Fog/Edge computing, QoE/QoS for Network Management
QoE/QoS in Multimedia Streaming and Applications 
QoE/QoS in 5/6G networks, User preferences models, Machine/Deep learning and QoE.
Quality of Experience (QoE), Cloud computing, Multimedia services

Chair: Asif Ali Laghari | Sindh Madressatul Islam University
Asif Ali Laghari received the B.S. degree in Information Technology from the Quaid-e-Awam University of Engineering Science and Technology Nawabshah, Pakistan, in 2007 and Master degree in Information Technology from the QUEST Nawabshah Pakistan in 2014. From 2007 to 2008, he was a Lecturer in the Computer and Information Science Department, Digital Institute of Information Technology, Pakistan. In 2015, he joined the school of the Computer Science & Technology, Harbin Institute of Technology, where he was a PhD student. Currently he is Assistant professor in Sindh Madressatul Islam University, Karachi, Pakistan. He has published more than 60 technical articles in scientific journals and conference proceedings. His current research interests include Machine Learning, Computer networks, cloud computing, IoT, Fog computing and multimedia QoE management.
Title: Digital Transformation: Convergence of Blockchain, Edge-IoT, and AI
The next wave of digital transformation will focus on the convergence of Blockchain, Edge-IoT, and Artificial Intelligence. Blockchain increases the security, privacy level, and trustworthiness of IoT devices. Edge platform offers latency-free faster services to IoT applications. The AI enables intelligent approaches at edge/cloud servers to optimize resource utilization as well as to enhance the outcome. Up to this point, the interconnection between these three innovations is often neglected, and blockchain, Edge-IoT, and AI are typically used separately. The convergence of these technological aspects will introduce a new era in information security. The researchers have a great interest in the impact of AI over Edge platforms. The convergence of AI and Edge is called Edge intelligence. Edge intelligence, which brings together the fields of Artificial Intelligence and Edge Computing, is a key enabling technology for smart services. The introduction of blockchain technologies to Edge intelligence will increase trust, transparency, security, and privacy of IoT devices by providing a shared and decentralized distributed ledger. The overall security can be ensured by integrating blockchain-based intelligent algorithms at Edge Servers. Blockchain-based Edge intelligence should thus be a priority research concern. 
The workshop solicits high-quality and unpublished work on the latest research improvements in the area of Blockchain-based Edge Intelligence in the IoT environment. The topics of interest include, but are not limited to: ·
AI-based optimizations in the Cloud platform ·
Edge Intelligence ·
Blockchain in Smart IoT applications ·
Trust management mechanisms in IoT ·
Industrial Transformation ·
Smart Cities ·
Industrial IoT ·
Internet of Medical Things
Blockchain, Edge Intelligence, AI, Edge Computing, IoT, Network Security

Chair: Serin V Simpson | Madanapalle Institute of Technology and Science
Serin V Simpson (Member, IEEE) is presently working as Assistant Professor – Department of Computer Science and Technology, School of Computers, Madanapalle Institute of Technology and Science, AP, India - A UGC autonomous institution, affiliated to JNTUA, and approved by AICTE, New Delhi, India. He received his M.Tech degree in Computer Science and Engineering from the University of Calicut in 2015. He received his B.Tech degree in Information Technology from the University of Calicut in 2012. Currently, he is doing Ph.D. programme in Computer Science and Engineering at Sathyabama Institute of Science and Technology, India. His research area includes Edge Computing and Network Security. He has published research papers in peer-reviewed journals such as IEEE, Springer, Inderscience, Taylor and Francis, and Elsevier. He has 1 year of industrial experience (Orion India Systems Pvt. Ltd.) and 7 years of teaching experience (SCMS School of Engineering and Technology and Thejus Engineering College). He has been a Organizing Chair, Workshop Chair, Technical Committee Member and Reviewer for reputed international conferences such as IEEE – IC3SIS (Kerala, India), CRYPIS 2022 (Toronto, Canada), CICA2022 (Luoyang, China), ICNCIS2021 (Sanya, China), etc; He has published papers in the research areas of Edge/Fog Computing, Cloud Computing, Wireless Sensor Networks, IoT, Mobile Ad-hoc Networks, Network Security, and Cluster-based communication.
Title: Privacy Computing Facilitates the Secure Sharing of Data
In the era of big data, on the one hand, it is necessary to build a digital economy and society to support open sharing and interconnection of data; on the other hand, cross-comparison of data makes it easier to reverse the anonymized user information. The issue of privacy leakage must also be taken seriously. Privacy computing can make the data available invisible, the data does not move, the data is not shared, but the value of the data is shared, so as to achieve the purpose of being invisible to the data availability, so as to fully protect the privacy and security of the data during the sharing process. However, based on privacy computing There are still many challenges and problems in practical application of technology to achieve privacy-protected data sharing. This seminar will focus on the following contents: (1) Discussion and analysis of application scenarios of privacy computing technology, such as: finance, medical care, government affairs, etc., to sort out application paradigms. (2) Privacy computing promotes the safe sharing of data, and realizes multi-party privacy computing that takes into account confidentiality and public verifiability in terms of data security transmission, data privacy protection, and multi-party business collaboration. (3) The integration of privacy computing technology and other technologies promotes data security sharing. Privacy computing can integrate multiple underlying technologies to enable data flow, data security and data realization, such as: secure multi-party computing, federated learning, blockchain, etc.
Privacy calculation, Data sharing, Security privacy, Security Management

Chair: Guangxia Xu | Guangzhou University
Xu Guangxia is a professor and doctoral supervisor at the School of Cyberspace Security, Guangzhou University. She is currently a Senior Member of the China Computer Federation (CCF), Blockchain Committee member, ACM and IEEE member, Vice Chairman of Information Security Association of Chongqing University, expert of National Natural Science Foundation and committee member of Technical Committee on Fault Tolerant Computing of CCF. She has served as the Director of Big Data Security and Intelligence Analytics Technology Innovation Team at Chongqing University. She was a Visiting Scholar at the Stevens Institute of Technology, New Jersey, USA, and a Post-Doctor at the School of Communication and Information Engineering, Chongqing University. Prof. Xu's research interests include Blockchain Technology and Application, Big Data Security and Analytics, Network Security and Management, IoT Security and AI Security. Extensive and novel results have been accomplished and most of them have already been published through high-quality journals, conference papers and projects. She is in charge of one sub-project of National Science and Technology Support Projects, two projects of National Natural Science Foundation of China, one sub-project of information Security Projects of National Development and Reform Commission, and many more. In addition, she is a reviewer for ACM Computing Surveys IEEE Access, Digital Communications and Networks, International Journal of Geographical Information Science, and member of the editorial board of the Journal of Chongqing University of Posts and Telecommunications.
Title: Challenges and Trends in Android Malware Analysis
Malware attacks pose a high risk to compromise the security of Android apps. These threats have the potential to steal critical information, causing economic, social, and financial harm. Because of their constant availability on the network, Android apps are easily attacked by malicious network traffic. The network-based malware detection system has the potential to be effective because the majority of Android malware performs its malicious functions via network traffic. The goal of network traffic-based approaches is to find distinguishing features that can be used to classify malware more effectively. 
The aim of this workshop is to bring together the research accomplishments provided by researchers from academia and the industry. The other goal is to show the latest research results in the field of Android malware attacks. We encourage prospective authors to submit related distinguished research papers on the subject of both: theoretical approaches and practical case reviews.
Malware analysis, Network traffic,Security attacks, Digital forensics.

Chair: Farhan Ullah | Northwestern Polytechnical University
FARHAN ULLAH is an Associate Professor at the School of Software, Northwestern Polytechnical University (NPU), Xi'an Shaanxi, P.R. China. He received Ph.D. computer science degree in 2020 from the college of computer science, Sichuan University Chengdu, P.R. China. He was awarded a full-time Chinese Government Scholarship (CGS) for his Ph.D. studies. He is the special issue Lead Guest Editor for Security and Communication Networks, and the Computers, Materials, and Continua Journals. He is an editorial board member of KSII Transactions on Internet and Information Systems Journal. He also served as a Guest Editor for a special issue of Future Internet Journal. He received research landmark achievement award from school of software, NPU, Xian, China in 2021. He received Research Productivity Award (RPA) from COMSATS Institute of Information Technology (CIIT), Sahiwal, Pakistan in 2016. His research work is published in various renowned journals of IEEE, Springer, Elsevier, Wiley, MDPI, and Hindawi.
Title: Cloud Computing Moving towards Greener and Low-Carbon
Cloud computing effectively aggregates virtualized computing resources through the network, and provides dynamic, cost-effective, elastic scale expansion computing, storage and various information services for single users or multiple tenants based on the centrally built data centers. With the rapid expansion in the scale and number of cloud data centers, the issue of high energy consumption and carbon emissions has attracted considerable attention. There are growing policy, climate, and financial pressures to reduce this, and the benefits of traditional energy-saving methods have largely peaked. Innovation is greatly needed. This workshop calls for works demonstrating the most recent progress and contributions to energy-saving solutions for cloud data centers. In particular, the topic of interest include, but are not limited to:
1.Application of AI, big data, digital twin, robot and other technologies in reducing energy consumption for cloud data centers at device level.
2.Optimized energy-saving control logic and solutions at system level.
3.Carbon emission reduction related techniques at platform level.
4.Security assurance mechanism in green cloud data centers.
Cloud Data Centers, Energy Saving, AI, Green Technology, Security

Chair: Ziting Zhang | China Telecom Research Institute
Ziting Zhang received the M.Sc degree in electronic and communication engineering from Beijing University of Posts and Telecommunications. She currently works as a standard and solution engineer at China Telecom Research Institute (Beijing). Her research interests mainly focus on network intelligence, 5G, energy saving for data centers, intent-based networks. She contributed significantly to the ETSI ISG ENI as the leader of a PoC (Proof of Concept) project and the rapporteur for ENI GR 015. She led the Smart IDC catalyst project in 2021 TM Forum Digital Transformation World (DTW) summit, and won “Sustainability Impact” award, which was the first time for IDC related AI scenario practice.
The "E-Energy Saving" product developed by her team has been deployed in 21 provinces in China, covering 148 data centers, saving 50.13 million kWh of electricity which equivalent to 32.30 million CNY for DC customers. This product won the "New Product Award" at the China International Big Data Industry Expo in 2021. It was also selected for the "Recommended Catalogue of Energy-saving Technology Products in National Communication Industry (2021)" of the Ministry of Industry and Information Technology.
Title: An end-to-end intelligent monitoring platform used on distributed system
With the wide implementation of distributed architecture, it brings new challenges to operation and maintenance. The number of system nodes and microservices increased exponentially, and the monitoring workload increased sharply. The relationship between monitoring objects is extremely complex, and human maintenance is not competent. The traditional maintenance mode is difficult to sustain due to data fragmentation and remote storage. Traditional operation and maintenance has the following shortcomings: 1) Due to the group / provincial two-level maintenance system, the operation and maintenance is decentralized. As a result, the whole network business support cannot be effectively controlled, and the whole network problem / fault scheduling system is not smooth. 2) The whole network monitoring system is built according to different businesses, with scattered monitoring data and backward monitoring methods, which leads to the difficulty of position problem across businesses. 3) Traditional maintenance is oriented to single system and single business, without focusing on end-to-end customer perception. 4) Single system cross domain or layer problem / fault processing is slow and time-consuming, and can not achieve accurate fault location and rapid fault recovery. This paper proposes an end-to-end intelligent monitoring system based on pinpoint. It is an intensive operation and maintenance platform for cloud systems, which can realize cross domain monitoring and cross iaas/paas/saas layer monitoring. It is a shared operation and maintenance platform based on big data and AI technology to establish platform/application architecture. As for service, it can provide end-to-end cross service monitoring throughout the network. As for application, it can be used for the whole network to quickly find and locate faults. After using the end-to-end distributed cloud monitoring system, the fault discovery time is greatly shortened, and the fault handling is reduced from hour level to minute level. At the same time, the system fault time is greatly shortened, and the operation and maintenance efficiency is improved.
Distributed; microservices; monitor; end-to-end; fault location; fault recovery

Chair: Lanying Shi | China Telecom Research Institute

Lanying Shi works in China Telecom Research Institute and is a master's student graduated from Jiangxi University of Technology. In recent years, she has worked in the communications industry and has a thorough understanding of the core business of operators. Her main research interests are cloud computing, artificial intelligence, big data, micro services, distributed architecture, digital transformation, etc. She is a key member of the dual project of China Telecom Research Institute. In addition, in recent years, she has published many papers in top international conferences and journals, including Journal of Software, ICSP, ICCEA, ICPICS, etc.

Chair: Shuxin Yang | Jiangxi University of Science and Technology

Dr. Shuxin Yang is an associate professor in the school of information engineering, Jiangxi University of Science and Technology. He received PhD from Tongji University (China). He joined the Jiangxi University of Science and Technology in July 2000. His current research interests include information diffusion modeling, adversarial attack and defense on graph data, and intelligent computation for law text.

Title: Information Security, Data Sharing & Privacy, Generative Adversarial Network
The research of information security management system and information security assessment has attracted more and more scholars' attention. Based on antagonistic sample generation technology, we explorecopyright protection, data generation, artificial intelligence security, generative adversarial network and other information security practices.
This workshop aims to bring together the latest research accomplishments in the field of Information Security, Data Generation, Privacy.And we encourage the prospective authors to submit their distinguished research papers on the subjects.
Information Security, Data Generation, Privacy, Antagonistic sample generation technology, Deep learning, Generative Adversarial Network

Chair: Sheng Hong | Beihang University
Sheng Hong is an associate professor and doctoral supervisor in the School of Cyber Science and Technology at the Beihang University (BUAA).He engaged in network and information security, complex system security research, antagonistic sample generation technology, deep learning, generative adversarial network, completed a number of related scientific research projects in the field of network security, Presided over the national key basic research and development plan projects, national key research and development project, industrial Internet innovation and development project, technical basic project, pre-research project, National Natural Science Foundation of China There are more than 10 national, provincial and ministerial-level topics, and more than 10 horizontal topics in key industries such as industrial Internet, intelligent manufacturing, State Grid, and avionics systems. He is the editorial board member of several international journals and conferences, including "Information Network Security", "Information Technology and Network Security" and "Aeronautical Engineering Progress". In the national key research and development plan, he established a multi-level industrial network security protection model, through dangerous targets, key targets, cloud detection and other protection strategies and protective measures to ensure the network from the aspects of environmental credibility, situational knowledge, and controllable operation. Security; in the industrial Internet innovation and development project, he proposed a system security enhancement protection technology for the industrial Internet; in the National Natural Science Foundation, he broke through the critical phase change mechanism of fault propagation by focusing on the coupling, chaos and spreading characteristics of dynamic network faults The bottleneck of the maintenance control strategy provides a new solution for the prevention of complex dynamic network fault propagation and fault-tolerant control. In the open topic of the Shanghai industrial control system safety innovation functional platform, he aimed at the industrial Internet network suffered from virus attacks and equipment paralysis. The actual problems of the research network virus transmission mechanism and protection strategies. He has published more than 70 papers, including 30+ SCI papers, one co-authored academic book, and 14 national invention patents.
Title: Artificial intelligence is applied in the industry
Artificial intelligence (AI) is a method and technology to simulate and expand human thinking through scientific research and development, to make intelligent machines have the ability to respond to things similar to human beings, and apply it to medical care, network information security and other fields. This seminar requires the deep combination of artificial intelligence with medical treatment and network information security, thereby to solve some problems that cannot be achieved by traditional technologies, including: (1) The establishment of AI-based intelligent protection system to solve the problems of slow response, long time consumption and low efficiency of traditional network protection methods; (2) In the 3D reconstruction of digital twin environment, establish a  intensive deep learning (DL) network, combined with artificial intelligence and doctor operation training, establish force line recovery model scheme. The purpose of this seminar is to establish a deep cross-application mode of AI + medical intelligence and AI + network information security.
Artificial intelligence, deep learning (DL), medical care, and network information security

Chair: Baohui Wang | Beihang University
Professor Baohui Wang has more than 20 years of rich experience in scientific research and engineering technology, and many years of experience in big data and machine learning algorithm research and development. He has long been engaged in teaching and research work in network security, big data, artificial intelligence and other fields. He once led the development of image search engine and security search engine, responsible for the research of space satellite component envelope quality analysis algorithm, responsible for the research of financial AIOPS abnormal detection, root cause analysis and early warning algorithm, responsible for the research of network security encryption traffic level situational awareness algorithm. Proficient in deep learning and enhanced learning of artificial intelligence, he has taught lots of courses and has been well received. 
He has participated in the project design of many smart cities in Jiuquan, Gansu, Zhuzhou, Hunan and Pingxiang, Jiangxi, and presided over the research and development of dozens of large systems such as national science and technology support projects, special fund projects of National Development and Reform Commission, and civil aviation special fund projects. To participate in the formulation of the National Industrial Control Safety Standards. In recent years, he has published more than 40 academic papers and one monograph in famous journals and conferences at home and abroad, and has obtained 4 software Copyrights and 10 national patents.
Title: Metaverse and AI for Smart City, Intelligent Medical and Wisdom Education
Metaverse,as a virtual world constructed by human beings using the network and digital technologies, including 5G, cloud computing, virtual reality, block chain, digital currency, Internet of things, human-computer interaction and so on. It is a virtual world that reflects or transcends the real world and can interact with the real world.In this way, Metaverse can greatly empower the development of Smart City, Intelligent Medical and Wisdom Education, by reproducing the real-world and repeating the real-world scenarios. Now, combining with the booming artificial intelligencetechnologies, Metaverse and AI becomes the major driving forces for the development of mobile network technology. Aiming at such trend, this workshop focus on but not limited to: 
(1) Metaverse and AI enabled Smart City, including the smart home for better human live, smart robots for automate and high-quality service, smart driving for unmanned car, smart inspection for dangerous scenarios like electric power line, etc.
(2) Metaverse and AI enabled Intelligent Medical, including the intelligent healthy care and real-time monitoring for human, intelligent medical diagnosis for remote surgery, intelligent sensing and warning for human sports, intelligent medical image recognition for disease diagnosis, etc.
(3) Metaverse and AI enabled Wisdom Education, including the wisdom translators between different languages, wisdom roll call and cheating detection system for teaching in class, wisdom knowledge review and remind system, wisdom and virtual school for students, etc.
Metaverse, AI, Smart City, Intelligent Medical, Wisdom Education

Chair: Bo Yi | Northeastern University
Bo Yi works as an associate professor at the School of Computer Science and Engineering, Northeastern University, China. His main research interests include the network routing, service computing and orchestration, edge computing, network function virtualization, artificial intelligence, and etc. He has hosted several projects granted from the General Program of the National Natural Science Foundation of China, and the projects from the National Key Research and Development Program of China. Moreover, he has published more than 40 papers on top international conferences and journals in recent years including IEEE TPDS, TCC, TMC, IWQoS, CN, etc. The maximum number of citations for his paper has exceeded 500 times.
Title: Theory and Technology Internet of Vehicle and Automated Driving
The Internet of Vehicles (IoV) is a real-time communication network with moving vehicles as communication terminals or nodes. It is a highly dynamic and complex network. One of the important indicators of vehicle network is Ultra-Reliable Low-Latency Communications(uRLLC). In a highly dynamic network, in order to achieve uRLLC, it is necessary to break through the bottleneck from the links of information access, information transmission and information exchange to optimize the overall performance of the system.
This workshop intends to focus on vehicle nodes spatial distribution, wireless transmissiontheory between vehicles and vehicular protocols for Internetof Vehicle, and to solicit contributions from experts and research teams around the world. The topics of interest include, but are not limited to:
Spatial distribution of vehicle nodes on the ground formed by vehicle driving.
Theory and technology of wireless transmission between vehicles.
Vehicle LAN protocols.
Vehicle WAN architecture and protocols.
Theory and technology of sensedatafusion for automateddriving
Spatial distribution, vehicular wireless theory, vehicular protocols, automated driving

Chair: Jin Tian | Jinling Institute of Technology
Jin Tian is a Doctor/Professor/Senior Engineer, visiting scholar of CSIRO, in Australia. He received a Doctor's degree in the National Mobile Communication Laboratory, Southeast University, and received a Master's degree in the Advanced Photonics Center, Southeast University. Master's tutor of communication discipline in HoHai University, Nanjing University of Posts and Telecommunications and Anhui University of Science and Technology, and also an senior expert of the ministry of education in the evaluation of dissertations for Master degree. From July 2011 to April 2014, he served as the dean of the school of information technology, Jinling Institute of Technology, and from May 2014 to now, he has served as the dean of the engineering school of networks and telecommunications, Jinling Institute of Technology. He works as international standard expert of Inter System Telecommunication, member of National Standardization Technical Committee of Intelligent TransportationSystem, trustee of China Intelligent Transportation Industry Alliance, trustee of Jiangsu Communication Society, trustee of Jiangsu Optical Society, trustee of Internet of things branch of China Communication Industry Association, and supervisor of Nanjing Multimedia Information Technology Society. He is authorized an expert in National Natural Science Foundation of China (Youth Fund, general programs), and on Science and Technology Program of Jiangsu Province, Chongqing Province,Guangdong Province and Shandong Province. He published a monograph on “collaborative communication and network", published more than 60 natural science papers, and authorized 3 invention patents.Recent research fields: access technology and route technology on Internetof Vehicle.
Title: How to Balance Between Privacy Protection and Data Collection?
Information privacy is considered one of the biggest issues in cyberspacebecause of the ever-increasing collection and use ofpersonal information by companies. Largely driven bythe Artificial Intelligence technologies, big data, cloud computing, 5G, mobile Internet and so on, companies have more direct access to consumers’ private data(e.g., real-time location, biometrics) than ever before,thus opening the door to privacy invasion. Data breaches raise privacy concerns thatprevent consumers from disclosing their personal information, especially private information, thus preventing companies from obtaining and leveragingconsumer data. Data collection must be balancedwith protecting private information and consumerprivacy; otherwise, companies’ credibility and ability to collect data from consumers would be jeopardized. 
Thus, this workshop calls for work related to ideas, methods, design, technologies, user behaviors about balance between privacy protection and data collection, refers to all digital domains, such as mobile commerce, healthcare and social media, and so on. In particular, this workshop will focus on the follows (1) data privacy and protection in apps; (2)Trade-offs between personalization and privacy; (2)adoption, use and continuance of information privacy and security technologies; (3)design and development of information security and privacy-enhancing technologies; (4)Cognitive biases and heuristics in privacy decision making; (5)Privacy issues in human-computer interaction.
Data privacy, privacy protection, digital age

Chair: Bailing Liu | Central China Normal University
Bailing Liu woks as a professor at the School of Information and Management, Central China Normal University, China. She received her PhD degree in Computer Sciencefrom Huazhong University of Science and Technology, China. Her research interests include information privacy, privacy protection, user information behaviors, and mobile commerce. She was the PI of three research projects on information security(2011) and privacy protection (2015, 2020) funded by the National Natural/Social ScienceFoundation of China. Her research has appeared in Information Systems Research, Decision Support Systems, Computers & Security, Frontiers of Computer Science, International Journal of Electronic Commerce, and more.