SVD and ASCII Character Encoding-Based Compression of Multiple Biosignals for Remote Healthcare Systems

2018 ◽  
Vol 12 (1) ◽  
pp. 137-150 ◽  
Author(s):  
Sourav Kumar Mukhopadhyay ◽  
M. Omair Ahmad ◽  
M.N.S. Swamy
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Mourade Azrour ◽  
Jamal Mabrouki ◽  
Rajasekhar Chaganti

Recently, Internet of Things and cloud computing are known to be emerged technologies in digital evolution. The first one is a large network used to interconnect embedded devices, while the second one refers to the possibility of offering infrastructure that can be used from anywhere and anytime. Due to their ability to provide remote services, IoT and cloud computing are actually integrated in various areas especially in the healthcare domain. However, the user private data such as health data must be secured by enhancing the authentication methods. Recently, Sharma and Kalra projected an authentication scheme for distant healthcare service-based cloud-IoT. Then, authors demonstrated that the proposed scheme is secure against various attacks. However, we prove in this paper that Sharma and Kalra’s protocol is prone to password guessing and smart card stolen attacks. Besides, we show that it has some security issues. For that reason, we propose an efficient and secured authentication scheme for remote healthcare systems in cloud-IoT. Then, we prove informally that our projected authentication scheme is secure against multiple attacks. Furthermore, the experimental tests done using Scyther tool show that our proposed scheme can withstand against known attacks as it ensures security requirements.


Author(s):  
Rajeev Agrawal ◽  
Amit Sehgal

This paper introduces an information theoretic approach for location management in cellular/mobile networks and allows the network to maintain the record of the mobility pattern of every user. The critical nature of remote healthcare service demands for continuous updates on the location of healthcare expert with the patient monitoring device. To reduce the paging cost, the proposed work uses the information from the system database by representing given past knowledge of the mobility pattern using Markov Chain. The expected search under the proposed work reduces number of search required in the earlier techniques. An entropy-per-location based scheme has also been introduced for comparative analysis among different models. This scheme can also be utilized as a general comparative framework for schemes to be introduced in future m-Health framework.


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