Workshop 1 : Blockchain-based Federated Learning
Title: Traceability: Decentralized Federated Learning under the Blockchain
Blockchain and federated learning, as fast-growing emerging industrial technologies, are widely used in manufacturing, agriculture, tourism, medical care, and other industries. On the one hand, blockchain enables decentralized and immutable data storage. On the other hand, federated learning has achieved great success in solving the problem of data islands. This workshop calls for works demonstrating the most recent progress and contributions to blockchain-based federated learning. In particular, this workshop will focus on including but not limited to the following aspects: 
(1) Federated learning based on blockchain to achieve decentralized privacy protection. 
(2) Combined with the limited resources of the Internet of Things (IoT), it is used in IoT to implement blockchain-based federated learning. 
(3) For traceability, audit, and so on aspects of the learning scheme based on blockchain. 
(4) A decentralized system based on blockchain with privacy, security, and credibility.
(5) Security, privacy, and trust for 6G-enabled ubiquitous, intelligent, and cooperative sensing.
(6)IoT technologies with artificial intelligence (AI) for smart cities, precision agriculture, industry 4.0 solutions, self-driving vehicles and health tracking, etc.

Keywords: Federated Learning, Blockchain, Internet of Things, 6G, Artificial Intelligence

Chair: Assist. Prof. Zuobin Ying, City University of Macau, China(Macau)
Zuobin Ying works at the City University of Macau. He is currently the Program Coordinator (Postgraduate) and Assistant Professor in the Faculty of Data Science. He also serves as a committee member of IEEE Macau. His main research interests are blockchain theory and applications, federated learning, and IoT security. In the past four years, he has published more than 50 papers in top international academic journals such as IEEE TSC, IEEE TITS, IEEE TVT, IEEE TCC, IEEE IoTJ, SCIS, and famous international academic conferences such as IEEE ICASSP, IEEE GLOBECOM, IEEE ICA3PP, and ACM CCS Workshop. In addition, he hosted and participated in several national and Macao scientific research projects.
Workshop 2 :  Deepfake: Face Manipulation and Fake Detection
Summary:As one of the characteristics of identity authentication, face plays an essential role in biometrics and human communication. With the rapid development of artificial intelligence and machine learning, people without programming and image editing foundation can also use open-source software and applications to realize face forgery. False news, spoof videos, pornographic videos, etc. created by criminals based on fake face videos have seriously damaged the public's trust in mass media, disrupted social order, and undermined national security. This workshop calls for works demonstrating the most recent progress and contributions to deepfake. In particular, this workshop will focus on the following: (1) Face manipulation, including entire face synthesis, face identity swap, facial attributes manipulation, and facial expression manipulation; (2) Fake facial image/video generation; (3) Fake detection. 

Keywords:Deepfake, face manipulation, fake detection, artificial intelligence, machine learning,

Chair:Assoc. Prof. Le-Bing Zhang,Huaihua University, China
Le-Bing Zhang works as an associate professor in School of Computer and Artificial Intelligence (School of Software), Huaihua University. His research interests include biometric security, multimedia security, and deep learning. He participated in several projects granted by the General Program of the National Natural Science Foundation of China. He published more than 15 papers on top international conferences and journals in recent years including IEEE ICME, ToM, etc. He has been invited to review manuscripts for many top journals such as IEEE TIP, TIFS for a long time.
Workshop 3 :  Performance Analysis and Optimization for Blockchain
Summary:Blockchain, as a distributed ledger technology, has drawn tremendous attentions in various applications and fields in the past few years. The evolutions of blockchain technologies have experienced a series of challenges including malicious behaviors occurred in blockchains, low throughput, and poor scalability, and etc. Various theories, frameworks, consensus models, and sophisticated mechanisms have been proposed to deal with the above problems of the blockchain but all suffer from limited performance. Especially when the future B5G/6G communication, Internet of Things, financial system and other fields are closely integrated with blockchain, a series of technical issues are emerging, such as the conflict in transactions, the balance of security and performance, resource allocation and so on. Therefore, it's necessary to further analyze and optimize the blockchain performance to meet the information interaction needs of the future society. This workshop is seeking submissions of technical papers in the following areas related to performance analysis and optimization for blockchain as well as other emerging areas of blockchain. (1) Performance modelling and analysis of blockchain; (2) Conflict transaction mitigation mechanism for blockchain; (3) Shard selection algorithm or mechanism for blockchain; (4) Efficient and safe consensus algorithm for blockchain; (5) Efficient smart contract for blockchain; (6) Parallel processing mechanism for blockchain transactions; (7) Efficient and reliable broadcast, routing protocol for blockchain networks; (8) Performance optimization for blockchain and its applications; (9) Performance optimization for payment channel networks.

Keywords: Blockchain architecture, Consensus algorithm, Performance optimization, Payment channel network, Smart contract

Chair:Prof. Gang Sun, University of Electronic Science and Technology of China, China
Gang Sun is a full professor at the University of Electronic Science and Technology of China. He has received his Ph.D. degrees in Information and Communication Engineering from the University of Electronic Science and Technology of China in 2012. He was a visiting professor at The Australian National University in 2015. His research interests include network virtualization, data center networking, cloud computing, high performance computing, parallel and distributed systems, ubiquitous/pervasive computing and intelligence and cyber security. He has published over 160 research papers in international journals and conference proceedings by leading international publisher like IEEE, Elsevier, Springer-Verlag, etc. He has published 6 books and more than 70 invention patents. He has given academic reports at international conferences more than 10 times. He has served as reviewers of more than 20 international journals such as IEEE TII, IEEE WC, IEEE TWC, IEEE TITS, IEEE TCC, IEEE TSC, IEEE IoTJ, IEEE TVT, IEEE TNSM, IEEE TIFS, FGCS, JNCA, etc. He is a member of IEEE and ACM.
Workshop 4 :  Learning-based Malware and Vulnerability Analysis
Summary:With the development of big data and mobile Internet technology, malware on computers and mobile smart terminals is increasing, which seriously threatens the property and privacy of users. Traditional malware analysis methods are facing new challenges, and artificial intelligence technology brings new opportunities in the field of software security. Security experts need to conduct more effective analysis of emerging malware and vulnerabilities and come up with more robust anti-malware and vulnerabilities detection method. In particular, this workshop will focus on including but not limited to the following aspects: (1) Mobile Malware Analysis. (2) Malware Variant Analysis. (3) Taint Analysis. (4) Construction and Validation of Malware and Vulnerabilities Dataset. (5) Anti-Malware Methods. (6) Intelligent Vulnerability Detection.

Keywords: Malware Analysis, Learning-based Method, Artificial Intelligence, Software Security

Chair:Dr. Junwei Tang, Wuhan Textile University, China
Junwei Tang received his Ph.D degree in School of Computer Science and Technology from Huazhong University of Science and Technology in 2020. Now he works in School of Computer Science and Artificial Intelligence, Wuhan Textile University. His research interests include mobile security, system security. He hosted and participated in several national and Hubei scientific research projects and open funds of key laboratories. He published papers on important international conferences and journals in recent years including FGCS, SACMAT and TrustCom. He is TPC member of international conferences (such as UIC 2022). He is one of experts in Wuhan Cyber Security Association.
Workshop 5 :  Information security algorithm and application.
Summary:This workshop aims to conduct research on information security algorithm and application in the fields of stream cipher, block cipher, random number, synchronization technology, software and hardware encryption, chaotic cryptography, etc.

Keywords: cipher, synchronization, hardware and software encryption, chaotic cryptography

Chair:Dr. Lina Ding, Heilongjiang University Of Science And Technology, China
Lina Ding, School of Electronics and Information Engineering, Heilongjiang University of Science and Technology. Education: Heilongjiang University, Ph.D. in Microelectronics and Solid State Electronics. Research area of interest: Information security and secret communication.
Workshop 6 :  Evidence Preservation and Audit: Evidence Preservation and Audit of Personal Private Data Operation Based on Blockchain
Summary:In view of the characteristics and needs of the personal sensitive information ecosystem, such as extensive sharing, large time and space span, numerous regulatory objects, and multiple collaborative supervision, research was carried out on the technical framework of active and passive collaborative supervision, the preservation and audit of evidence of private data operation, the fusion analysis of private data regulatory information, and the disposal of privacy infringement incidents. Key technologies include: 1. Personal rights and interests protection technical system and technical verification 2. Identification and classification of personal privacy data, classification and presentation method, classification identification and compliance evaluation 3. Desensitization and evaluation of privacy data on demand, desensitization control and compliance evaluation, protection of sensitive information on demand, de-identification and anonymization 4. Privacy computing, differential computing, federated computing, homomorphic encryption 5. Evidence preservation and audit of personal private data operation based on blockchain 6. Personal rights and interests protection supervision, active and passive supervision coordination, personal privacy infringement risk monitoring, regulatory information fusion analysis and event handling, etc.

Keywords: Personal Privacy Protection, Infringement Risk Monitoring, Blockchain, Evidence preservation, Desensitization, Artificial Intelligence

Chair:Dr. Nishui Cai, Senior Engineer, China Telecom Research Institute, China
Nishui Cai received the PhD degree from Shanghai Jiaotong University, Shanghai, China. He is currently working in China Telecom. His research interests include Information Security, Artificial Intelligence, System Reliability, Network Security, Data Security, Personal Privacy Protection, Blockchain, Cryptocurrency, Application Security. In recent years, as an information security expert and security architect, he has participated in the digital RMB DC development project of the national financial key infrastructure construction project, responsible for the design of blockchain technology and digital RMB security transaction process, has a number of patent applications related to digital currency, participated in the national project "Research on the protection of personal rights and interests of private data", applied for more than 10 patents, and published or contributed a number of SCI/EI papers.
Workshop 7 :  Privacy-preserving and Robust Federated Learning
Summary:Federated Learning (FL) have been proposed to enable multiple organizations to jointly train deep learning models without sharing private data. FL systems alleviate data privacy concerns as sharing local models instead of raw private data, but it may increase the hidden vulnerability to Byzantine attacks, where compromised organizations submit abnormal local models to steal data privacy or degrade the accuracy of global models. This workshop calls for works demonstrating the most recent progress and contributions to privacy-preserving and robust Federated Learning, which focus on defending against these Byzantine attacks, avoiding privacy leakage and guarantee model accuracy. In particular, this workshop will focus on including but not limited to the following aspects: (1) Privacy-preserving Federated Learning. (2) Byzantine-robust Federated Learning. (3) Privacy-preserving machine learning. (4) Privacy-preserving data sharing, anonymization, and privacy of synthetic data. (5) Privacy attacks. (6) Federated and decentralized privacy-preserving algorithms. (7) Secure multi-party computation techniques for machine learning. (8) Relations of privacy with fairness, transparency and adversarial robustness

Keywords: Federated Learning, Artificial Intelligence, Privacy Protection, Byzantine Attacks

Chair:Dr. Xiangyun Tang, Minzu University of China, China
Xiangyun Tang received the B.Eng degree in computer science from Minzu University of China, Beijing, China in 2016, and received the Ph.D. degree in Cyberspace Security from Beijing Institute of Technology, Beijing, China in 2022. She is currently a lecturer with the School of Information Engineering, Minzu University of China. Her research interests include Machine Learning Security, Privacy Protection, and Blockchain Applications. In the past four years, she has published multiple papers in top international academic journals such as IEEE TDSC, IEEE JSAC, IEEE IoT-J, and famous international academic conferences such as AAAI. She is a member of the IEEE.
Workshop 8 :  Fundamentals of the distributed ledger technology (blockchain technology) and cryptography as a whole and its new features.
Summary: Today, we can confidently say that blockchain technology has won its place in the financial sector, particularly in the cryptocurrency. As the further development of the distributed ledger technology, based on the blockchain, has shown, this does not exhaust the scope of its applications. There have been publications on the application of technology methods in the decentralized Internet of the future, medicine, housing and communal services, education, and so on.
Further analysis of the practical use of distributed ledger technology (blockchain technology) (DLT/Blockchain) showed that its new qualities are mainly based on the complex mathematical foundation of cryptology.
This means that in order for the new technology to become publicly available, the subscriber of the DLT/Blockchain network, requires special knowledge of the basics of the theory of cryptology. Then it was found that cryptology technologies are very expensive. Further, difficulties arose related to the transformation of the consciousness of the population of the countries to the new DLT/Blockchain technologies.
These tasks were especially acute with using DLT/Blockchain in humanitarian social and economic spheres. All this has led to difficulties not only in the use of DLT/Blockchain in the above areas, but also in the development of new algorithms, schemes and technologies. Based on the foregoing, it is proposed to consider the following tasks at the seminar:
1. Development of a model of DLT/Blockchain network subscribers and formulation of standard qualification requirements for it.
2. Development of a miner model in the humanitarian social and economic spheres, that is, replacing it with a notary-cryptographer who provides services for the formation of DLT/Blockchain and a service for embedding transaction blocks into the main DLT/Blockchain network.
3. Development of minimum requirements for technical support of DLT/Blockchain network subscribers.
4. Development of the fundamentals of the theory of designing DLT/Blockchain networks based on a criterion linking such parameters as the number of subscribers, the number of transactions, their cryptographic strength and network cyber security, with restrictions on its cost.
5. Development of protocols for asymmetric encryption, authentication and key management system, in relation to the humanitarian, social and economic fields of application, as well as the definition of requirements for hashing operations in blocks of the main chain of linked blocks.

Blockchain, cryptography, distributed ledger technology, authentication and key distribution protocols, asymmetric encryption, humanitarian, social and economic fields. 

Chair:Prof. Makarov Anatoly Mikhailovich, Pyatigorsk State University
Makarov Anatoly Mikhailovich was born in 1950 in USSR. 
He graduated from the Taganrog Radio Engineering Institute with a degree in Radio Engineering in 1977. He had  entered postgraduate studies at the St. Petersburg State University of Aerospace Instrumentation (SPSUAI) in 1981 and successfully defended his dissertation there for the degree of candidate of technical sciences in 1984. Anatoly Mikhailovich entered doctoral studies at SPSUAI in 1989 and defended doctoral dissertation in 1993. Dissertation topics are related to solving problems of pattern recognition and signal processing against the background of noise. He worked at the Taganrog Radio Engineering University as a professor until 2003. Makarov Anatoly Mikhailovich had received the degree of professor at the Department of Radio Engineering and Telecommunication Systems in 1995. 
After that he was elected to the position of the head of the Department of Complex Protection of Informatization Objects and Standardization and Certification in Pyatigorsk State Technological University in 2005.
He are working as a professor at the Department of Information and Communication Technologies of Mathematics and Information Security at Pyatigorsk State University since 2016, with researching in blockchain technology. 
There have been written about 93 papers and received 18 patents for inventions by professor Makarov, of which one patent for blockchain and cryptography technologies was received in 2022. Professor has 8 publications placed in the Scopus (5) and Web of Science (3) scientometric databases on the subject of a distributed ledger technology. Professor was participated at 15 international conferences over the past five years. 
Honorary Worker of Higher Education.

Co-Chair:Lecturer Ermakov Alexander Sergeevich, Pyatigorsk State University
Ermakov A. was graduated from the North Caucasian Federal University with a degree in Complex Protection of Informatization Objects in 2013.
He has been carrying out practical activities in the field of information security of automated systems since 2013.
 Ermakov A. has been lecturing a number of studies in the field of information security at the North Caucasus Federal University since 2016.
Also he has been lecturing at Pyatigorsk State University on ensuring the security of automated systems since 2020.
Ermakov A. had published over 35 papers on information security. Research area: informational security of automated systems
Workshop 9 : Blockchain scalability solutions and their security trade-offs
Summary: Blockchain scalability refers to the ability of a blockchain network to process a large number of transactions in a given time period. As blockchain networks become more popular and widely adopted, the need for scalability becomes more pressing. There are several solutions to address blockchain scalability, but each solution has its own set of trade-offs, particularly in terms of security. Here are some of the most common solutions to blockchain scalability and their associated security trade-offs: Sharding: Sharding is a technique that involves breaking up the blockchain into smaller, more manageable pieces called shards. Each shard operates independently, processing its own set of transactions. Sharding can increase the transaction processing capacity of the blockchain by several orders of magnitude. However, it can also introduce new security risks because each shard must maintain its own consensus mechanism, which can be vulnerable to attacks. Off-chain transactions: Off-chain transactions involve moving some of the transaction processing off the blockchain and onto secondary networks or sidechains. This can improve scalability because it reduces the burden on the main blockchain. However, it also introduces new security risks because off-chain networks are not subject to the same level of security as the main blockchain. Segregated Witness (SegWit): SegWit is a soft fork that separates transaction signature data from the transaction data itself. This reduces the amount of data that needs to be processed, which can improve scalability. However, it also introduces new security risks because the signature data is no longer included in the transaction, which could potentially make it easier to create fraudulent transactions. Lightning Network: The Lightning Network is a layer-two protocol that enables off-chain transactions between parties. This can improve scalability because it reduces the number of transactions that need to be processed on the main blockchain. However, it also introduces new security risks because the Lightning Network is not subject to the same level of security as the main blockchain. Proof of Stake (PoS): PoS is a consensus mechanism that enables network participants to validate transactions based on the amount of cryptocurrency they hold. This can improve scalability because it reduces the amount of energy required to validate transactions. However, it also introduces new security risks because it makes the network vulnerable to a "51% attack," in which a single participant controls the majority of the network's cryptocurrency. Overall, blockchain scalability solutions involve a trade-off between scalability and security. It's important to carefully evaluate each solution to determine the appropriate trade-off for a particular use case.
Keywords: Blockchain, Information Security, Scalability
Chair: Assist. Prof. Dr. Pratima Sharma, Bennett University, Greater Noida
PhD in Computer Science, Delhi Technological University, India, 2018-2022
Master of Technology in Information Security, Inderprastha University, India, 2013-2015
Bachelor of Technology in Computer Science, Inderprastha University, 2009-2013
Research Interests: Blockchain TechnologyInformation SecurityDistributed Systems
Teaching Experience: OOPS using JAVA, Bennett University, India, Spring 2022 
Data Structures, Delhi Technological University, India, Spring 2020 
Database Management System, Inderprastha Engineering College, India, Fall 2018
Awards and Honors: Research Excellence Award, Delhi Technological University, 2020
Professional Memberships: Institute of Electrical and Electronics Engineers (IEEE)

Workshop 10 : Blockchain Consensus and its Applications
Summary: Blockchain consensus, as a core underlying technology of blockchain, fundamentally determines the security and performance of a blockchain system. Generally, blockchain consensus needs to meet the requirements of consistency and liveness, and different blockchain consensus mechanisms vary under different network models. Traditional blockchain consensus mechanisms include Proof of Work (PoW), Proof of Stake (PoS), and Byzantine Fault Tolerance (BFT). In different scenarios, such as Metaverse, 5G, Federated Learning, and the Internet of Things (IoT), blockchain consensus mechanisms that meet different needs need to be designed. This workshop is calling for the latest research and applications related to blockchain consensus, including but not limited to the following aspects: Improved PoW consensus algorithms or PoS algorithms; Hybrid consensus algorithms, including improved BFT algorithms; Improved sharding consensus algorithms, including sharding member election, intra-shard consensus, and cross-shard transaction processing modules; Blockchain security analysis; Techniques to increase the throughput of blockchain; Applications of blockchain in the 5G scenario; The combination and application of blockchain and Metaverse.
Keywords: Blockchain Consensus, Metaverse, Byzantine Fault Tolerance, Sharding,  Internet of Things, 5G
Chair: Assist. Prof. Yizhong Liu, Beihang University, China
Yizhong Liu is an assistant professor at the School of Cyber Science and Technology, Beihang University, China. He has been selected as a young talent of the China Association for Science and Technology under the auspices of the Chinese Electronics Society. He is leading four research projects, including the National Natural Science Foundation of China for Young Scientists, the Beijing Natural Science Foundation for General Projects, and the Open Project of the State Key Laboratory of Cryptology. Additionally, he has participated in three major national research projects, including the National Key R&D Program of China, the Joint Fund Key Project of National Natural Science Foundation of China, and the National Natural Science Foundation of China. He has published over 20 academic papers, 17 of which he is the first author or corresponding author. These publications appear in journals such as IEEE Transactions on Dependable and Secure Computing, Computer Science Review, Computer & Security, Computer Networks, Future Generation Computer Science, ACISP 2021, TrustCom 2020, ICA3PP 2020. He has also been granted four patents and has ten patent applications under review. He serves as a guest editor for Frontiers in Blockchain and as a committee member for SmartBlock 2020, TrustCom 2022. He is a reviewer for international journals, including IEEE TII, IEEE TBD, IEEE TSMC, and ACM TIT.

Workshop 11 : Research on Key Technologies of Moving Target Defense in Software Defined Network
Summary: The increasing number of major network security incidents shows that the traditional defense system is difficult to effectively cope with the constantly developing network attack methods. The cyberspace is facing an asymmetrical situation of "easy to attack and hard to defend". To extricate defenders from the asymmetrical predicament, Moving Target Defense (MTD) is proposed. By continuously changing the attack surface, the attacker cannot detect and predict the real properties of the system, which increases the attack cost of the attacker and improves the system defense benefit. Software Defined Networking (SDN) decouples the control plane, it brings great convenience to deploy MTD due to its programmability and flexibility. The workshop will focus on including but not limited to the following aspects: Moving Target Defense Strategies, network-based MTD technique, MTD based on SDN, MTD technique applied in IoT, etc.
Keywords: Moving Target Defense, Software Defined Network, IoT
Chair: Assist. Prof. Li Han,  Tianjin University of Technology, China
Li Han works at the Tianjin University of Technology Tianjin. She is currently Associate Professor in School of Computer Science and Technology. She also serves as a committee member of CCF. Her main research interests are Software Defend security, Network anomaly traffic detection, Moving Target Defense and IoT security. In the past four years, she has published multiple SCI, EI indexed papers, Licensed Patents. In addition, she hosted and participated in several national and Tianjin scientific research projects.

Workshop 12 : Blockchain meets Image Processing
Summary: Welcome to our workshop on "Blockchain meets Image Processing"! This workshop aims to explore the intersection of two cutting-edge technologies: blockchain and image processing. Blockchain technology provides a secure and decentralized platform for storing and sharing data, while image processing techniques enable the analysis and manipulation of visual information. By combining these two fields, we can create innovative solutions for various applications such as digital identity verification, copyright protection, and smart contracts for image-based transactions. In this workshop, we will bring together experts from both areas to discuss the latest research, share ideas, and collaborate on exciting new projects.
Keywords: Blockchain, Image processing

Chair: Assoc. Prof. Xueqing Zhao,  Xi'an Polytechnic University, China
Xueqing Zhao is currently an associate professor and tutor of the School of Computer Science of Xi'an Polytechnic University, and has been a visiting scholar to Peking University, Graz University of Technology in Austria, "Young Outstanding Talents" in Shaanxi Province Universities, "Young Talents Entrusted Talents" of Shaanxi Higher Education Science Association, a member of ACM, and the CCF Information System Committee. Her main research areas are intelligent computing, big data and blockchain, she has presided and participated in 25 scientific research projects and published more than 30 research papers; He has applied for 20 China National invention patents (4 have been authorized), 3 software Copyrights, published 1 monograph.

Co-chair: Dr. Hao Liu, Xi'an Polytechnic University, China
As a graduate student with a research focus on blockchain technology, I have published papers on image copyright protection schemes and hold a certificate of software copyright. My academic interests lie in exploring the applications of blockchain in various fields, such as digital asset management and decentralized finance. I am committed to advancing the understanding and development of this innovative technology through my research and academic pursuits.
Workshop 13Consensus algorithm, architecture, performance analysis on blockchain
Summary: Consensus algorithm is the core technology in blockchain, which describes how peers in blockchain network achieve data consistency and directly determines the operating efficiency of the entire blockchain system. At the same time, the architecture is also the key to the blockchain application. However, the existing consensus algorithm and architecture are different to meet the performance and security requirements of blockchain applications. So, to study the new consensus algorithm and architecture have important significance for the actual application of blockchain.
Keywords: consensus algorithm, architecture, performance analysis

Chair: Associate Prof. Xiaohong Deng , School of Electronics and Information Engineering, Gannan University of Science and Technology University, China
Xiaohong Deng, received a Ph.D. degree in Computer Application Technology from Central South University. He worked as an associate professor at the School of Electronics and Information Engineering, Gannan University of Science and Technology University. His research interests include Blockchain and Information Security. He participated in the National Natural Science Foundation, Natural Science Fund Project in Jiangxi province, etc. Based on these projects, he published more than 50 papers in important academic publications at home and abroad. At present, he is a peer reviewer of some academic journals on Blockchain and its application.

Workshop 14 : Blockchain-based Privacy Protection
Summary: Technology has eroded our privacy protections. Most things individuals or organizations do are now in the public domain. Third-parties monitor, store, and use personal and organizational data, patterns, preferences, and activities. Many emerging business models rely on the collection, organization, and resale of our personal data. Blockchain technology could potentially limit the impact of this erosion of privacy, while still releasing personal information when it is useful. For example, a user could store personal information on a blockchain and release parts of it temporarily to receive services. This workshop calls for works demonstrating the most recent progress and contributions to blockchain-based privacy protection. In particular, this workshop will focus on including but not limited to the following aspects: (1) Blockchain-based Identity Authentication (2) Blockchain-based Data Integrity Verification or Data Auditing (3) Blockchain-based Privacy Protection for IoT (4) Blockchain-based Privacy Protection for IoV (5) Blockchain-based Privacy Protection for IIoT (6) Blockchain-based Privacy Protection for Satellite Networks
Keywords: Privacy Protection, Blockchain, IoT, IoV, IIoT

Chair: A. P. Hui Qi, Changchun University of Science and Technology, China

Hui Qi works at the Changchun University of Science and Technology. He is currently the Associate Professor and the Deputy Director of Information Security Department in the School of Computer Science and Technology. He also serves as a member of China Computer Federation (CCF). His main research interests are blockchain theory and applications, privacy protection, and IoT/IoV security. In the past four years, he has published more than 10 papers in top international academic journals such as INS, FGCS, MONE, WINE, and famous international academic conferences such as IEEE ISPA, WASA, and IEEE TrustCom. In addition, he hosted and participated in several national scientific research projects.

Workshop 15 : Blockchain in the face of IoT Security
Summary: Blockchain, as a technology to maintain the reliability of data in a decentralized and untrusted way, can provide novel solutions for the security of the Internet of Things. First, the decentralized architecture of Blockchain subverts the traditional central architecture of the Internet of Things, which can prevent the whole network from being paralyzed after the control center is attacked by malicious attacks. Second, the accuracy and imtampability of Blockchain ledger make the data transmission of the Internet of things evidentable, which strengthens the defense and processing capabilities of user identity authentication and data protection. Third, the verification and consensus mechanism of Blockchain helps to identify legitimate Iot Taccessing the network. Fourthly, Blockchain technology, combined with distributed and decentralized structure, encryption algorithm and chain structure, provides sufficient protection for information security. Key issues addressed by Blockchain-based IoT application technologies include the following: 
(1) Research on security Guarantee architecture and security performance analysis method of multi-layer Blockchain in the Internet of Things. 
(2) Secure and efficient distributed consensus algorithm of IoT Blockchain. 
(3) Security technology of information exchange in Mobile Internet of Things based on DAG. 
(4) Blockchain Internet of Things access control and data protection technology. 
(5) Optimization mechanism of node resource deployment of mobile Internet of Things based on Blockchain.
Keywords: Security,Blockchain, Internet of Things(IoT), Consensus Algorithm

Workshop 16 : Trusted Blockchain with Confidential Computing
Summary: As a promising technique to achieve decentralized consensus, blockchain has been applied into various fields, e.g., digital currency, supply chain, etc. Thus, its security and privacy are of great importance. Confidential computing is a promising security technology that isolates sensitive data in a protected region during processing, which ensures data confidentiality, integrity and privacy. This workshop calls for works demonstrating the recent development and state-of-the-art methods of trusted blockchain with confidential computing. In particular, this workshop will focus on including but not limited to the following aspects:
1. Blockchain Architectures based on Trusted Execution Environment (TEE) 
2. Distributed Trust and Reputation Modelling 
3. Secure and Privacy-preserving Design of Key Management 
4. Trust Verification of Blockchain Nodes 
5. Scalable Privacy-preserving Techniques for Smart Contracts and Blockchain
Keywords: Blockchain, Confidential Computing, Trust

Chair: Prof. Juan Wang, Wuhan University, China
Wang Juan is an Professor at School of Cyber Science and Engineering of Wuhan University. She received her M.E. and Ph.D degrees in computer school from Wuhan University, China in 2004 and 2008. In 2018 and Jan. 2010, she did research as a visiting scholar in Pennsylvania State University and Arizona State University, USA. Her research has been supported by NSF projects. She has authored and coauthored over 40 papers and holds 10 patents in security areas. Her current research interests include cloud security, trust computing, SDN and NFV security.