Big data analytics of IoT based Health care monitoring system

Dineshkumar, P.; Senthilkumar, Radha; Sujatha, K.; Ponmagal, R.S.; Rajavarman, V. N.

doi:10.1109/upcon.2016.7894624

Cited by 45 publications

(25 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Besides the real-time healthcare data, there are healthcare big data (e.g., structured eHR, electronic medical record (eMR), (non-)clinical/medical imaging data, unstructured clinical notes, etc.) which demand separate handling due to their requirement of advanced data analytics [87], [88]. In the proposed framework, both kinds of healthcare data are transmitted to specific overlaying layer (either mist or fog or cloud) based on the data type and their processing requirements.…”

Section: Perception Layermentioning

confidence: 99%

Toward a Heterogeneous Mist, Fog, and Cloud-Based Framework for the Internet of Healthcare Things

Asif-Ur-Rahman

Afsana

Mahmud

et al. 2019

IEEE Internet Things J.

180

View full text Add to dashboard Cite

Rapid developments in the fields of information and communication technology and microelectronics allowed seamless interconnection among various devices letting them to communicate with each other. This technological integration opened up new possibilities in many disciplines including healthcare and well-being. With the aim of reducing healthcare costs and providing improved and reliable services, several healthcare frameworks based on Internet of Healthcare Things (IoHT) have been developed. However, due to the critical and heterogeneous nature of healthcare data, maintaining high quality of service (QoS) -in terms of faster responsiveness and data-specific complex analytics -has always been the main challenge in designing such systems. Addressing these issues, this paper proposes a five-layered heterogeneous mist, fog, and cloud based IoHT framework capable of efficiently handling and routing (near-)real-time as well as offline/batch mode data. Also, by employing software defined networking and link adaptation based load balancing, the framework ensures optimal resource allocation and efficient resource utilization. The results, obtained by simulating the framework, indicate that the designed network via its various components can achieve high QoS, with reduced end-to-end latency and packet drop rate, which is essential for developing next generation e-healthcare systems.

show abstract

Section: Perception Layermentioning

confidence: 99%

Toward a Heterogeneous Mist, Fog, and Cloud-Based Framework for the Internet of Healthcare Things

Asif-Ur-Rahman

Afsana

Mahmud

et al. 2019

IEEE Internet Things J.

180

View full text Add to dashboard Cite

show abstract

“…There are several IoT authentication challenges and issues that need to be understood before employing the right security solution that can dynamically vary with the situation [21,35]. Based on certain critical situations such as IoT health applications, frequent authorization and authentication are necessary and could dynamically vary, potentially resulting in changes to the authorization of IoT devices [2]. To address these issues, automated mutual authentication without user intervention is required in supporting users from remembering passwords for a large number of devices [39].…”

Section: Iot Authentication Issues and Attacksmentioning

confidence: 99%

“…Applying the Brahmagupta-Fibonacci identity from above, we get 4 2 + 6 2 + 6 2 + 9 2 = (9 − 4) 2 + (6 + 6) 2 = 5 2 + 12 2 = (9 + 4) 2 + (6 − 6) 2 = 13 2 + 0 2 = However, in this case, there are nine sums of four squares. (1,4,6,18), (1,6,12,14), (2,2,12,15), (2,6,9,16), (4,6,6,17), (4,6,10,15), (5,8,12,12), (6,6,7,16), (6,8,9,14) Only one of these is applicable to the Brahmagupta-Fibonacci identity, providing the two sum of two squares. A faster method, using a modified binary greatest common divisor, quickly validates a sum of four squares.…”

Section: Casementioning

confidence: 99%

“…Consider the semi-prime, N = 1445897 = (555, 4(259, 2 (15,28)) The implementation of our proposed factorisation method using the GCD function is provided here. The above example, whilst illustrating the basic principle, is a special case, as one of the factors of the two squares is a higher power of 2 n than the other, such that 1433 = 8 2 + 37 2 .…”

Section: Casementioning

confidence: 99%

“…With the development of a variety of technologies such as sensors, actuators, controllers, mobile devices and cloud computing, the Internet of Things (IoT) is evolving to be a large network of networks connecting smart devices that are exponentially growing in the physical world [1]. By seamlessly interconnecting humans with such an intelligent physical world, the IoT brings about benefits in various domains such as public health, transportation, agriculture, energy management, and waste management that can lead to smart cities and homes [2,3]. While such smart devices have capabilities to collect and analyze huge data for decision-making, security is a major concern, as IoT attacks by perpetuators with malicious interventions are on the rise.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

New Method of Prime Factorisation-Based Attacks on RSA Authentication in IoT

Venkatraman¹,

Overmars²

2019

Cryptography

View full text Add to dashboard Cite

The potential benefits of the Internet of Things (IoT) are hampered by malicious interventions of attackers when the fundamental security requirements such as authentication and authorization are not sufficiently met and existing measures are unable to protect the IoT environment from data breaches. With the spectrum of IoT application domains increasing to include mobile health, smart homes and smart cities in everyday life, the consequences of an attack in the IoT network connecting billions of devices will become critical. Due to the challenges in applying existing cryptographic standards to resource constrained IoT devices, new security solutions being proposed come with a tradeoff between security and performance. While much research has focused on developing lightweight cryptographic solutions that predominantly adopt RSA (Rivest–Shamir–Adleman) authentication methods, there is a need to identify the limitations in the usage of such measures. This research paper discusses the importance of a better understanding of RSA-based lightweight cryptography and the associated vulnerabilities of the cryptographic keys that are generated using semi-primes. In this paper, we employ mathematical operations on the sum of four squares to obtain one of the prime factors of a semi-prime that could lead to the attack of the RSA keys. We consider the even sum of squares and show how a modified binary greatest common divisor (GCD) can be used to quickly recover one of the factors of a semi-prime. The method presented in this paper only uses binary arithmetic shifts that are more suitable for the resource-constrained IoT landscape. This is a further improvement on previous work based on Euler’s method which is demonstrated using an illustration that allows for the faster testing of multiple sums of squares solutions more quickly.

show abstract

Machine Learning for Smart Healthcare Energy‐Efficient System

Porkodi¹,

Kesavaraja²

2021

Design and Development of Efficient Energy Systems

View full text Add to dashboard Cite

Big data analytics of IoT based Health care monitoring system

Cited by 45 publications

References 6 publications

Toward a Heterogeneous Mist, Fog, and Cloud-Based Framework for the Internet of Healthcare Things

Toward a Heterogeneous Mist, Fog, and Cloud-Based Framework for the Internet of Healthcare Things

New Method of Prime Factorisation-Based Attacks on RSA Authentication in IoT

Machine Learning for Smart Healthcare Energy‐Efficient System

Contact Info

Product

Resources

About