[hpc-announce] The Sixth International Conference on Internet of Things, Big Data and Security 2020 (IoTBDS 2021) due on 30 Nov

Victor Chang vic1e09 at soton.ac.uk
Mon Nov 9 21:02:16 CST 2020

Dear colleagues,

I hope you and your family are doing well. We have the Sixth International Conference on Internet of Things, Big Data and Security 2020 (IoTBDS 2021), an online streaming conference, between 23-25 April, 2021. Submission deadline is 30 Nov, 2020. We work with high quality journals, well-known keynote speakers and
researchers/scientists/practitioners/decision-makers from all over the world. Please check our websites http://iotbds.org/ and COMPLXIS 2021 http://www.complexis.org with the same submission deadlines and also /, FEMIB 2021 http://femib.scitevents.org/ and social network website https://www.facebook.com/ES2014ECs2015/.

We have the support from Journal of Global Information Systems (JGIM, WOS SCI/SSCI Q2), Computers and Electrical Engineering (CAEE, WOS SCI Q1) and a few more top journals. Our conference has an index from Scopus, EI etc. We look forward to meeting you. Many thanks in advance.

Thanks and regards,


6th International Conference on Internet of Things, Big Data and Security IoTBDS

website: http://www.iotbds.org

April 23 - 25, 2021 Online Streaming

In Cooperation with: DNS.PT
Proceedings will be submitted for indexation by: SCOPUS, Google Scholar,
DBLP, Semantic Scholar, EI and Conference Proceedings Citation Index.


Regular Paper Submission: November 30, 2020
Authors Notification (regular papers): February 5, 2021
Final Regular Paper Submission and Registration: February 22, 2021

Position Paper Submission: January 19, 2021
Authors Notification (position papers): February 24, 2021
Final Regular Paper Submission and Registration: March 9, 2021

The internet of things (IoT) is a platform that allows a network of
devices (sensors, smart meters, etc.) to communicate, analyse data and
process information collaboratively in the service of individuals or
organisations. The IoT network can generate large amounts of data in a
variety of formats and using different protocols which can be stored and
processed in the cloud. The conference looks to address the issues
surrounding IoT devices, their interconnectedness and services they may
offer, including efficient, effective and secure analysis of the data
IoT produces using machine learning and other advanced techniques,
models and tools, and issues of security, privacy and trust that will
emerge as IoT technologies mature and become part of our everyday lives.
Big Data (BD) has core values of volume, velocity, variety and veracity.
After collecting much data from IoT, BD can be jointly used with machine
learning, AI, statistical and other advanced techniques, models and
methods, which can create values for people and organizations adopting
it, since forecasting, deep analysis and analytics can help identify
weaknesses and make improvements based on different analysis.
Maintaining a high level of security and privacy for data in IoT are
crucial and we welcome recommendations, solutions, demonstrations and
best practices for all forms of security and privacy for IoT and BD.

Conference Topics:
Area 1: Big Data Research
- Big Data Fundamentals: Volume, Velocity, Variety, Veracity and Value
- Modeling, Experiments, Sharing Technologies & Platforms
- Analytics, Intelligence and Knowledge Engineering
- Data Center Enabled Technologies
- Networking and Social Networks
- Data Management for Large Data
- Software Frameworks (MapReduce, Spark Etc) and Simulations
- Social Science and Implications for Big Data

Area 2: Emerging Services and Analytics
- Health Informatics as a Service (HIaaS) for Any Type of Health
Informatics, Computation and Services
- Big Data as a Service (BDaaS) including Frameworks, Empirical
Approaches and Data Processing Techniques
- Big Data Algorithm, Methodology, Business Models and Challenges
- Security as a Service including Any Algorithms, Methodology and
Software Proof-of-Concepts
- Financial Applications for Risk, Pricing, Disaster Analysis and
Predictive Modeling
- Education as a Service (EaaS) Including eLearning, Tele-educational
and Tele-research Applications
- Business Process as a Service (BPaaS) including Workflows and Supply
Chain in IoT and Big Data
- Analytics as a Service (AaaS) for Any Types of Analytics
- Scheduling, Service Science, Performance Evaluation and Load Balance
for SaaS and Analytics
- eGovernment, eCommerce, eScience and Creative Technologies for IoT and
Big Data
- IoT Services and Applications
- New Service Models and Emerging Services

Area 3: Internet of Things (IoT) Fundamentals
- Software Architecture and Middleware
- Context-Awareness and Location-Awareness
- Performance Evaluation and Modeling
- Networking and Communication Protocols
- Machine to Machine Communications
- Energy Efficiency
- Software Engineering for IoT and IoE
- Machine Learning and Deep Learning Approaches Data Analytics

Area 4: Internet of Things (IoT) Applications
- Technological Focus for Smart Environments
- Smart City Examples and Case Studies
- Architecture for Secure and Interactive IoT
- Social Implications for IoT Intelligent
- Systems for IoT and Services Computing
- Sensor Networks, Remote Diagnosis and Development
- Transportation Management Traffic Theory, Modeling and Simulation
- Intelligent Infrastructure and Guidance Systems for Vehicles, Green
Systems and Smart City

Area 5: Big Data for Multi-discipline Services
- Smart City and Transportation
- Education and Learning
- Business, Finance and Management
- Case Studies of Real Adoption
- Biomedical Experiments and Simulations
- Social Networks Analysis, Media and eGovernment
- Risk Modeling and Analysis, Simulations of Economic Impacts of the
- Healthcare Services, Health Informatics and Biological Research of the

Area 6: Security, Privacy and Trust
- Algorithms, Software Engineering and Development
- Encryption (All Aspects)
- Firewall, Access Control, Identity Management
- Intrusion and Detection Techniques
- Case Studies
- Location-Based Privacy
- Data Security, Data Recovery, Disaster Recovery
- Adoption Challenges and Recommendation
- Security, Privacy and Trust
- Testing (Software Engineering; Penetration; Product Development)
- Experiments on Using Security Solutions and Proof-of-Concepts
- Emerging Issues and Recommendations for Organizational Security
- Social Engineering, Hacking Preventions and Ethical Hacking:
Techniques, Recommendations and Case Studies
- Software Engineering for Security Modeling, Business Process Modeling
and Analytics

Area 7: IoT Technologies
- Artificial Intelligence
- Biotechnology
- Communication
- Data Processing
- Internet of Things
- Sensors
- Zigbee
- Vehicle-to-Infrastructure
- Vehicle-to-Vehicle
- Transport Safety and Mobility
- Electronic Technologies for in-Vehicle
- 3D Printing and Nanotechnology

Yaochu Jin, University of Surrey, United Kingdom

Victor Chang, Teesside University, United Kingdom

Gary Wills, University of Southampton, United Kingdom
Péter Kacsuk, MTA SZTAKI, Hungary


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