More and more organizations have embraced the industrial internet of things (IIoT) to adopt novel information communication technologies to improve their industrial processes and daily operation. In this case, crackers may discover more and more opportunities to bypass organizational perimeter protection systems like firewalls to access industrial information systems and assets. While IIoT system has connected end-devices with industrial and IT (Information Technology) systems, the risk of data transmission among these heterogeneous systems has been increased. Therefore, organizations should not simply rely on their perimeter protection systems for IIoT resilience. Recently, zero trust concepts have promptly gathered much attention due to minimizing risk in enforcing accurate, least privilege per-request access decisions in service applications under the circumstance of a compromised network. In a zero trust architecture, each access request should be authenticated and checked whether the request is permitted no matter it originated from external or internal network. In addition, unauthorized people from utilizing devices of authorized users to intrude other devices for lateral movement. Organizations need to evaluate trustworthiness of access requests based on user behaviors and threat intelligence and adapt associated access control policies. In that case, zero trust concepts are highly suitable to leverage IIoT risk we are facing.
Therefore, the track is going to discuss algorithms, methodologies, frameworks to evaluate risk of access requests for achieving zero trust in IIoT. Example topic includes:
- Trust evaluation algorithm for IIoT
- Cyber threat intelligence and cyber threat information sharing for IIoT
- Edge device risk evaluation for IIoT
- Adaptive access control for IIoT
- Policies and selective restrictions for zero trust in IIoT
- Novel theories, architectures, applications and paradigms with zero trust in IIoT
- Practices and experiences for zero trust architecture in IIoT
- Security modelling for zero trust architecture in IIoT
- Effectiveness evaluation and benchmark of zero trust technologies in IIoT
- Advances in the use of zero trust underlying technologies (e.g., AI, blockchain, deterministic networks, cloud/edge computing, etc.) in IIoT
- Miscellaneous issues for zero trust in IioT
Dr. Shi-Cho Cha, SMIEEE, National Taiwan University of Science and Technology
Shi-Cho Cha (SM’17) received the B.S. and Ph.D. degrees in information management from National Taiwan University, in 1996 and 2003, respectively. He is currently a professor and department chair with the Department of Information Management, National Taiwan University of Science and Technology (NTUST), where he has been a faculty member since 2006. He is also the director of the information security center, NTUST. He is a certified PMP, CISSP, CSSLP, CCFP, and CISM. From 2003 to 2006, he was a Senior Manager with PricewaterhouseCoopers, Taiwan. His current research interests include security and privacy of blockchain applications, IoT security and privacy, and information security.
Dr. Yoshihiro Ohba, Kioxia Corporation
Yoshihiro Ohba is Chief Specialist of System Technology R&D Center, Institute of Memory Technology R&D, Kioxia Corporation. He is an IEEE Fellow. He received B.E., M.E. and Ph.D. degrees in Information and Computer Sciences from Osaka University in 1989, 1991 and 1994, respectively. He is a Senior Member of IEEE. He has been active in standardizing security and mobility protocols for 18 years. He served as Chair of IEEE 802.21a and IEEE 802.21d, and also served as Vice Chair and Secretary of ZigBee Alliance Neighborhood Area Network (NAN) WG also known as JupiterMesh. He is one of the main contributors to RFC 5191 (PANA – Protocol for carrying Authentication for Network Access), which is used as the standard network access authentication protocol for B-Route and Home Area Network profiles of Wi-SUN Alliance and ZigBee IP profile of ZigBee Alliance, and has been implemented in all smart meters in Japan supporting B-Route communication with 920MHz band. He received IEEE Region 1 Technology Innovation Award 2008 for Innovative and Exemplary Contributions to the Field of Internet Mobility and Security related Research and Standards. His current interest is parallel and distributed computing and storage system security.
Dr. Kuo-Hui Yeh, SMIEEE, National Taiwan University of Science and Technology
Kuo-Hui Yeh (SM’16) is a full Professor with the department of Information Management, National Dong Hwa University, Hualien, Taiwan. He received M.S. and Ph.D. degrees in Information Management from the National Taiwan University of Science and Technology, Taipei, Taiwan, in 2005 and 2010, respectively. Dr. Yeh has authored over 100 articles in refereed journals and conferences. His research interests include IoT security, Blockchain, mobile security, NFC/RFID security, authentication, digital signature, data privacy and network security. Dr. Yeh is currently an Associate/Academic Editor of the Journal of Information Security and Applications (JISA), Symmetry, Security and Communication Networks (SCN), Mobile Information Systems (MISY), the Journal of Internet Technology (JIT), the Journal of Surveillance, Security and Safety (JSSS), Foundations, Research Reports on Computer Science and Frontiers in Communications and Networks – Security, Privacy and Authentication. In addition, he has served as an Associate Editor for IEEE Access and Data in Brief and a Guest Editor for Future Generation Computer Systems (FGCS), Cloud Computing, IEEE Access, Annals of Telecommunications, CMC-Computers, Materials & Continua, Mathematical Biosciences and Engineering (MBE), and the International Journal of Information Security (IJIS), JIT, Sensors and Cryptography. Moreover, Dr. Yeh has served as a TPC member for 50 international conferences/workshops on information security. He is a Senior Member of the IEEE and a Member of the (ISC)2, ISA, ISACA, CAA, CCISA, as well as holds CISSP, CISM, Security+, ISO 27001 LA, ISO 27701 LA and IEC 62443-2-1 LA certifications.
Dr. Hsing-Kuo Pao, National Taiwan University of Science and Technology
Hsing-Kuo Pao (Kenneth) received the bachelor degree in mathematics from National Taiwan University, and M.S. and Ph.D. degrees in computer science from New York University. From 2001 to 2003, he was a post-doctorate research fellow in the University of Delaware, and later he joined in Vita Genomics as a research scientist. In 2003, he joined the department of computer science and information engineering in National Taiwan University of Science and Technology, and now a professor and chairman in the department. His current research interests include machine learning methodology and its applications such as IoT analytics, computer vision and information security.
Dr. Yuh Jye Lee, National Yang Ming Chiao Tung University
Dr. Yuh-Jye Lee received the PhD degree in Computer Science from the University of Wisconsin-Madison in 2001. Now, he is a professor of Department of Applied Mathematics at National Yang Ming Chiao Tung University. His research is primarily rooted in optimization theory and spans a range of areas including network and information security, machine learning, data mining, big data, numerical optimization and operations research. During the last decade, Dr. Lee has developed many learning algorithms in supervised learning, semi-supervised learning and unsupervised learning as well as linear/nonlinear dimension reduction. His recent major research is applying machine learning to information security problems such as network intrusion detection, anomaly detection, malicious URLs detection and legitimate user identification. Currently, he focus on online learning algorithms for dealing with large scale datasets, stream data mining and behavior based anomaly detection for the needs of big data and IoT security problems.