Secure E-Health Platform
241
of the monitoring systems, the privacy of its users, the availability and the storage
of data.
To address the aforementioned issues, we propose a solution to provide the
healthcare community and patients with a secure medical service. Our platform offers continuous medical monitoring with the integration of medical data
backup mechanisms at the Cloud level, thus ensuring the notion of fault tolerance through data replication and thus the availability of information while
guaranteeing the integrity and confidentiality of the data exchanged ( using
sh1 and MD5 protocols for hashage and DES ,RSA for encryption), a minimal
response time and low latency due to the implementation of fog computing. The
remainder of this paper is organized as follows. Section 2 reviews related works on
healthcare systems. Section 3 describes the proposed solution. Section 4 presents
the experiments. Finally, Sect. 5 concludes the paper.
2 Related Works
In this section, we discuss the related work of healthcare systems. In [5], The
authors present a cloud computing solution for patient’s data collection in healthcare institutions. The system uses sensors attached to medical equipment to collect patient data and sends it to cloud for providing ubiquitous access. In [6],
the proposed architecture is dedicated to data acquisition via several personal
health devices via USB, ZigBee or Bluetooth. But the disadvantage of the abovementioned work is that the response time and latency increases due to the long
path to the cloud, which influences the user’s access time to the data. In [7] who
have implemented an IoT- healthcare system architecture which benefits from
the concept of fog computing, thus ensuring low latency data processing and low
bandwidth usage. The main disadvantage of the above works is the neglect of
the notion of security. In [15] authors have proposed a robust solution in terms
of response time by ensuring the confidentiality of data via an authentication
protocol except that it only authenticate LPU (Local Process Unit) and not
identify the users and neglects the property of data availability by centralizing
storage at the level of a single server, in the event of failure of the latter, access
to medical records will be suspended, which could endanger human life. While
the authors of [16] Propose a secure healthcare system with the same drawback as the previous one with neglect of the quality of service criteria (response
time and latency). On the other hand, our approach maintains a backup procedure to ensure continuity of service while guaranteeing the unique identity rule
via the NIN [12]. According to [17] that uses Blockchain as a security method
offers several advantages by allowing an agreement without the use of a trusted
third party and thus avoiding the bottleneck, the antecedent medical data are
also complete and coherent thanks to the chaining. However, this technology
requires a significant investment which is very costly. It should also be noted
that the blockchain consumes a lot of computing time, which is not ideal for
e-health platforms.
241
of the monitoring systems, the privacy of its users, the availability and the storage
of data.
To address the aforementioned issues, we propose a solution to provide the
healthcare community and patients with a secure medical service. Our platform offers continuous medical monitoring with the integration of medical data
backup mechanisms at the Cloud level, thus ensuring the notion of fault tolerance through data replication and thus the availability of information while
guaranteeing the integrity and confidentiality of the data exchanged ( using
sh1 and MD5 protocols for hashage and DES ,RSA for encryption), a minimal
response time and low latency due to the implementation of fog computing. The
remainder of this paper is organized as follows. Section 2 reviews related works on
healthcare systems. Section 3 describes the proposed solution. Section 4 presents
the experiments. Finally, Sect. 5 concludes the paper.
2 Related Works
In this section, we discuss the related work of healthcare systems. In [5], The
authors present a cloud computing solution for patient’s data collection in healthcare institutions. The system uses sensors attached to medical equipment to collect patient data and sends it to cloud for providing ubiquitous access. In [6],
the proposed architecture is dedicated to data acquisition via several personal
health devices via USB, ZigBee or Bluetooth. But the disadvantage of the abovementioned work is that the response time and latency increases due to the long
path to the cloud, which influences the user’s access time to the data. In [7] who
have implemented an IoT- healthcare system architecture which benefits from
the concept of fog computing, thus ensuring low latency data processing and low
bandwidth usage. The main disadvantage of the above works is the neglect of
the notion of security. In [15] authors have proposed a robust solution in terms
of response time by ensuring the confidentiality of data via an authentication
protocol except that it only authenticate LPU (Local Process Unit) and not
identify the users and neglects the property of data availability by centralizing
storage at the level of a single server, in the event of failure of the latter, access
to medical records will be suspended, which could endanger human life. While
the authors of [16] Propose a secure healthcare system with the same drawback as the previous one with neglect of the quality of service criteria (response
time and latency). On the other hand, our approach maintains a backup procedure to ensure continuity of service while guaranteeing the unique identity rule
via the NIN [12]. According to [17] that uses Blockchain as a security method
offers several advantages by allowing an agreement without the use of a trusted
third party and thus avoiding the bottleneck, the antecedent medical data are
also complete and coherent thanks to the chaining. However, this technology
requires a significant investment which is very costly. It should also be noted
that the blockchain consumes a lot of computing time, which is not ideal for
e-health platforms.