  Since the number of elderly and patients who are in hospitals and healthcare
centers are growing, providing efficient remote healthcare services seems very
important. Currently, most such systems benefit from the distribution and
autonomy features of multiagent systems and the structure of wireless sensor
networks. On the one hand, securing the data of remote healthcare systems is
one of the most significant concerns; particularly recent types of research
about the security of remote healthcare systems keep them secure from
eavesdropping and data modification. On the other hand, existing remote
healthcare systems are still vulnerable against other common attacks of
healthcare networks such as Denial of Service (DoS) and User to Root (U2R)
attacks, because they are managed remotely and based on the Internet.
Therefore, in this paper, we propose a secure framework for remote healthcare
systems that consists of two phases. First, we design a healthcare system base
on multiagent technology to collect data from a sensor network. Then, in the
second phase, a layered architecture of intrusion detection systems that uses
Support Vector Machine to learn the behavior of network traffic is applied.
Based on our framework, we implement a secure remote healthcare system and
evaluate this system against the frequent attacks of healthcare networks such
as Smurf, Buffer overflow, Neptune, and Pod attacks. In the end, evaluation
parameters of the layered architecture of intrusion detection systems prove the
efficiency and correctness of our proposed framework.
