Blockchain and federated learning-based security solutions for telesurgery system: a comprehensive review

【Author】 Chaudjary, Sachi; Kakkar, Riya; Gupta, Rajesh; Tanwar, Sudeep; Agrawal, Smita; Sharma, Ravi

【Source】TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES

【影响因子】0.853

【Abstract】The advent of telemedicine with its remote surgical procedures has effectively transformed the working of healthcare professionals. The evolution of telemedicine facilitates the remote monitoring of patients that lead to the advent of telesurgery systems, i.e. one of the most critical applications in telemedicine systems. Apart from gaining popularity, the telesurgery system may encounter security and trust issues of patients' data while communicating with the surgeon for their remote treatment. Motivated by this, we have presented a comprehensive survey on secure telesurgery systems comprising healthcare, surgical robots, traditional telesurgery systems, and the role of artificial intelligence to deal with the numerous security attacks associated with the patients' health data. Furthermore, we propose a blockchain and federated learning-based secure telesurgery system to secure the communication between patient and surgeon. The results of the proposed system are better than those of the traditional system in terms of improved latency, low data storage cost, and enhanced data offloading. Finally, we explore the research challenges and issues associated with the telesurgery system.

【Keywords】Telesurgery; telemedicine; artificial intelligence; blockchain; federated learning

【发表时间】2022

【收录时间】2023-01-14

【文献类型】理论模型

【主题类别】

区块链应用-实体经济-医疗领域