MLSPIoHT-2021: Machine Learning for Security and Privacy in Internet of Healthcare Things |
Submission link | https://easychair.org/conferences/?conf=mlspioht2021 |
Poster | download |
Abstract registration deadline | October 31, 2020 |
Submission deadline | October 31, 2020 |
IoT is expanding worldwide in recent years, it also provides new challenges and opportunities related to the cyber security risk in IoT healthcare sector. IoHT devices diagnose the diseases very easily in less time with more accuracy but with the lack of network segmentation, insufficient access control on legacy system as well as enhance the vulnerable surface area that can be exploited by cyber attackers. Most common threats that IoHT devices poses is of data privacy and security. As IOT device transmit and receive data in real time. Cybercriminals attack the system and steal the Personal Health Information (PHI) of both doctors as well as patients. Later on cybercriminal misuse these data to generate fake IDs to buy medical equipment and drugs, which they sell later. Hacker also files false medical Insurance claim on patient’s name. Another more significant threat is an integration of multiple network devices which causes hindrance in the implementation of IoT in the healthcare sector. The huge amount of data generated by IoT healthcare devices disrupts the decision making of doctors to diagnose the diseases.
The researchers can contribute in “Security and Privacy for Internet of Healthcare Things” book to answers many problems related to security risk in internet of healthcare things. Researcher can provide strong solution to the security concerns in the healthcare system and design new system that focus on data security and privacy, integration of multiple devices and protocol, data overloading and accuracy, etc
Submission Guidelines
All papers must be original and not simultaneously submitted to another journal or conference.
List of Topics
This is an edited book. The main topics for the chapters of this book are:
- Introduction of Internet of Healthcare Things (IoHT).
- Machine Learning and Security challenges in IoHT.
- Case studies of trust in IoHT and Machine Learning.
- Secure Data Transmission network model for IoHT.
- Authentication and Authorization mechanism for IoHT.
- Data Security and Privacy Concern in HealthCare System.
- Security Enhancements in cloud computing based Healthcare System.
- Fog computing based security platform for IoHT.
- Security and Privacy Issue related to IoT based ubiquitous Healthcare System.
- BlockChain for IoHT.
- Big data and Machine learning based secure e-Healthcare System.
Guest Editor
- Dr. Kavita Sharma, Associate Professor, Department of CSE, G. L. Bajaj Institute of Technology and Management, Greater Noida, India
- Dr. Yogita Gigras, Assistant Professor (Sel. Grade), Department of CSE and IT, The NorthCap University, Gurugram, India
- Dr. D. Jude Hemanth, Associate Professor, Department of ECE, Karunya University, Coimbatore, India.
- Dr. Ramesh Chandra Poonia, Post-Doctoral Fellow, Department of ICT and Natural Sciences, Norwegian University of Science and Technology, Norway
Publication
MLSPIoHT-2021 proceedings will be published by Wiley-Scrivener
Contact
All questions about submissions should be emailed to
Dr. Kavita Sharma, Department of CSE, G. L. Bajaj Institute of Technology and Management, Greater Noida, India. Email: kavitasharma_06@yahoo.co.in
Dr. Yogita Gigras, Department of Computer Science Engineering and Information Technology, The NorthCap University, Gurugram, Haryana, Email: yogitagigras@ncuindia.edu