Social network analysis (SNA) focuses on underlying social structure in a social network. Social media naturally is quite diverse in its usage and many people use it to exchange information healthcare issues. Many people update their health conditions daily using such systems and is extremely helpful for cases where patients want to self-report and observe their own conditions over time. However, this type of data is confidential and over time large data sets have been collected, legally, for research purposes. This type of data has led to great studies that connect certain lifestyles with types of diseases. With the introduction of wearable devices with healthcare applications, such wireless sensor networks have been shown to become more vulnerable to active and passive attacks.
Great harm can come from these attacks in the form of data modification, impersonation, and eavesdropping. In the case that wearable devices are used to administer drugs, such attacks could lead to serious outcomes if drug delivery is compromised. Furthermore, the almost nonexistence of strict cybercrime laws is a large factor in reducing the resistance against privacy concerns. In general, a healthcare model based on social networks includes actors, the system, the environment, and communication between the actors and system.
With the multi-cloud setup, we can get integration and communication of data transmission from one cloud to another allowing for faster and more consistent sharing of information among various hospitals and even between hospitals and the patient’s home. Without a well-planned architecture and hierarchy though, this multi-cloud setup would be very vulnerable to various attacks.
