Human Sensor Network (HSN) is an emerging technology that allows to remotely monitor, gather and maintain the information of patient’s health parameters using bio-sensors. The bio-sensors are either implantable or wearable or may be stitched on the clothes of a patient.The collected health information is processed and maintained in a database server. The information from the database can be accessed by the users such as doctors, health servants, government, insurance agencies and by the patient or his relatives. Since, the information collected is related to thepatient’s private health record, it is required to be safely stored and protected from an unauthorized access. Thus, Security and Privacy are the key issues in HSNs.In this paper, the infrastructure-based and adhoc-based communication architecture of HSN and challenges and measures of security and privacy issues have been reviewed.
Premature delivery of baby leads to death of babies below the age of 5 years. Even if they survive, they have to leave with a permanent disability like loss of vision, reduced learning abilities and hearing problems. Over the past years researchers have noticed that, observing uterine contractions can help in assessing the advancement of pregnancy and health of baby. It also decides whether pregnant lady is in the process of giving birth and thus accordingly reduce the impacts of premature delivery. This paper proposes a simple, secure, comfortable and cheaper system to screen pregnant ladies who are vulnerable to premature delivery. This system comprises of a wireless Human Sensor Network (HSN) for non-obtrusively observing the uterine contractions and if it is observed that readings are outer the normal limits, then a warning alert is send via a smart device. This paper also proposed a proof-of-idea model and tried it for testing the performance, power utilization and quality of the system.
Proportional to the growth in the usage of Human Sensor Networks (HSN), the volume of the data exchange between Sensor devices is increasing at a rapid pace. In HSNs, the sensors are either implanted or placed on the human body which are responsible for sensing the health data such as BP, Sugar level, Heart rate, etc. All this collected information is processed by the base station and is sent to the HSN servers via internet. Medical assistants who will have access to servers will analyze the health data of the patient and suggest appropriate medication. This will allow the doctors to have continuous monitoring on patient’s health condition. Since the data is related to patient’s health, it should be secured and confidential. In this paper, we have proposed an Energy Efficient Lightweight Encryption (EELWE) algorithm for providing the confidentiality of data at sensor level, particularly suitable for resource-constrained environments. Results obtained have proved that an EELWE consumes less energy relative to present lightweight ciphers and it supports multiple block sizes of 32-bit, 48-bit and 64-bit.
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