This chapter proposes an efficient centralized secure architecture for end to end integration of IoT based healthcare system deployed in Cloud environment. The proposed platform uses Fog Computing environment to run the framework. In this chapter, health data is collected from sensors and collected sensor data are securely sent to the near edge devices. Finally, devices transfer the data to the cloud for seamless access by healthcare professionals. Security and privacy for patients' medical data are crucial for the acceptance and ubiquitous use of IoT in healthcare. The main focus of this work is to secure Authentication and Authorization of all the devices, Identifying and Tracking the devices deployed in the system, Locating and tracking of mobile devices, new things deployment and connection to existing system, Communication among the devices and data transfer between remote healthcare systems. The proposed system uses asynchronous communication between the applications and data servers deployed in the cloud environment.

Chandu thota

Revathi sundarasekar

Gunasekaran manogaram

Varatharajan r

Priya m k

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Exploring the Convergence of Big Data and the Internet of Things Advances in Data Mining and Database Management

As health data are very sensitive, there is a need to prevent and control the health data with end-to-end security solutions. In general, a number of authentication and authorization schemes are available to prevent and protect the sensitive data, which are collected with the help of wearable Internet of Things (IoT) devices. The transport layer security (TLS) protocol is designed to transfer the data from source to destination in more reliable manner. This protocol enables a user to overcome the no lost or reordered messages. The more challenge with TLS is to tolerate unreliability. In order to overcome this issue, Datagram transport layer security (DTLS) protocol has been designed and used in low-power wireless constrained networks. The DTLS protocol consists of a base protocol, record layer, handshake protocol, ChangeCipherSpec and alert protocol. The complex issue with the DTLS protocol is the possibility of an attacker could send a number of ClientHello messages to a server. This scenario would cause a denial-of-service (DOS) attack against the server. This DoS attack enables new connection between the attacker and server, increasing attacker bandwidth, and allocation of resources for every ClientHello message. In order to overcome this issue, we have proposed a smart gateway-based authentication and authorization method to prevent and protect more sensitive physiological data from an attacker and malicious users. The enhanced smart gateway-based DTLS is demonstrated with the help of Contiki Network Simulator. The packet loss ratio is calculated for the CoAP, host identity protocol, CoAP-DTLS and CoAP-enhanced DTLS to evaluate the performance of the proposed work. Data transmission and handshake time are also calculated to evaluate the efficiency of the enhanced DTLS. © 2017, Springer Science+Business Media, LLC.

The Journal of Supercomputing

Enhanced DTLS with CoAP-based authentication scheme for the internet of things in healthcare application

In the midst of all the applications empowered by the Internet of Things (IoT), constant health surveying framework is an especially essential one. The leg movement monitoring framework is utilized to recognize the beginning time of joint pain illness. Wearable sensor gadgets and Uric acid (UA) sensor utilized as a part of IoT health monitoring framework for joint inflammation ailment have been creating a gigantic measure of information on a nonstop premise with rapid, change of huge health facts, and identification of these infections present some significant issues. These can be overwhelmed by utilizing the proposed framework for health data transformation and alongside the calculation utilized for the discovery of human foot movement for the GOUT arthritis diagnosis. Sensitivity and specificity are computed to assess the Time wrapping calculation-based characterization display for Arthritis ailment. The exploratory outcomes demonstrated the adequacy of the dynamic time wrapping technique. At last, ROC examination is conducted to distinguish the most significance clinical and laboratory assessments to get joint inflammation (GOUT arthritis) and kidney ailment. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.

International Journal of Computers and Applications

A typical IoT architecture-based regular monitoring of arthritis disease using time wrapping algorithm

In wireless sensor networks (WSN), the nodes are used to collect and gather the data from different environments. Hence, the network consumes more energy which is the main and challenging issue in WSNs. Since the sensor is operating under battery, recharging is impossible and hence the lifetime of each sensor is an important issue. Therefore, it is necessary to introduce new and efficient techniques to extend the network lifetime. In this paper, a new delay constrained energy efficient routing technique is proposed for performing effective routing in WSNs. This approach introduces a delay constraint based reliable routing approach which reduces the energy consumption by constructing efficient clusters without increasing the end-to-end delay. Moreover, the proposed technique called the rule based clustering for routing model provides better performance in terms of network lifetime than the other existing techniques since they consume more energy during the formation of clusters and finding the shortest path. Moreover, additional overhead on the cluster head selection is tackled also using rules in this proposed model in an efficient manner by building balanced clusters. The main advantage of the proposed approach is that it extends the lifetime of the network and increases the throughput, energy efficiency, link quality and scalability. The experimental verification of this technique has been carried out using MATLAB simulations and proved that this model increases the packet delivery rate, network performance and reduces the delay and energy consumption. © 2017, Springer Science+Business Media, LLC.

Cluster Computing

A rule based delay constrained energy efficient routing technique for wireless sensor networks

Most of the advancements are now carried out by interconnecting physical devices with computers; this is what known as Internet of Things (IoT). The major problems facing by blind people fall in the category of navigating through indoor and outdoor environments consisting of various obstacles and recognition of person in front of them. Identification of objects or person only with perceptive and audio information is difficult. An intelligent, portable, less expensive, self-contained navigation and face recognition system is highly demanded for blind people. This helps blind people to navigate with the help of a Smartphone, global positioning system (GPS) and a system equipped with ultrasonic sensors. Face recognition can be done using neural learning techniques with feature extraction and training modules. The images of friends, relatives are stored in the database of user Smartphone. Whenever a person comes in front of the blind user, the application with the help of neural network gives the voice aid to the user. Thus this system can replace the regular imprecise use of guide dogs as well as white sticks to help the navigation and face recognition process for people with impaired vision.In this paper, we have proposed a novel image recognition and navigation system which provides precise and quick messages in the form of audio to visually challenged people so that they can navigate easily. The performance of the proposed method is comparatively analyzed with the help of ROC analysis. © 2017, Springer Science+Business Media, LLC, part of Springer Nature.

Intelligent face recognition and navigation system using neural learning for smart security in Internet of Things

In the present era of Information Technology, almost all big and small scale companies are moving towards cloud to store and manage the data. Cloud computing is a routine of deploying a structure of distant servers speed up on the Internet to store, oversee, and manage information, rather than a neighbourhood server or a PC. The purpose for cloud procurement is reduced cost, adaptability, regular access and refreshed programming. Nowadays, healthcare frameworks are adjusting computerized stages and ending up being more patient-centered and data driven. In this paper, we present a planning empowered intermediary re-encryption method to defeat the security issues. This Technique will allow only limited access rights to an authorized agent to access the records for a specific time period. This technique will use a searchable encryption and proxy Re-encryption technique. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.

Journal	Exploring the Convergence of Big Data and the Internet of Things Advances in Data Mining and Database Management
Publisher	IGI Global
ISSN	2327-1981
Open Access	0