This study proposed an efficient fuzzy vault-based security method that adopts time-domain parameters extracted from physiological signals for tele-healthcare applications, including rehabilitation and stress management systems among others. One of the main challenges of the existing fuzzy vault-based approaches is that they depend on frequency-domain parameters of bio-signals to generate entities identifiers which require more processing time and energy consumption. Hence, we firstly designed a wearable platform for bio-signals collection, and later extracted time-domain features from the signals to generate efficient and distinctive identifiers for securing medical data in tele-healthcare applications. The statistical tests and hamming distances were applied to verify the performance of the generated identifiers regarding their uniqueness and randomness, respectively. This research work considered a total of 30 subjects data and the experimental results reveal that the proposed approach has better performance in WBSNs regarding processing time (0.168 ms) and energy consumption (1.423 mJ) than the traditional techniques. © 2018 Elsevier Ltd

Arun Kumar S

Department of Information Security

School of Computer Science and Engineering

Vellore Campus

Pirbhulal S

Shang P

Wu W

Samuel O.W

Li G.

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

Computers & Electrical Engineering

Internet of Medical Things (IoMTs) is a building block for modern healthcare having enormously stringent resource constraints thus lightweight health data security and privacy are crucial requirements. A critical issue in implementing security for the streaming health information is to offer data privacy and validation of a patient's information over networking environment in a resource efficient manner. Therefore, we developed a biometric-based security framework for resource-constrained wearable health monitoring systems by extracting heartbeats from ECG signals. It is analyzed that time-domain based biometric features play a significant role in optimizing security in IoMT based medical applications. Moreover, resource optimization model based on utility function is proposed for clinical information transmission in IoMT. In this study, ECG signals from 40 healthy subjects were employed comprising lab environment and publicly available database i-e-physionet. The experimental results validate that proposed framework requires less processing time and energy consumption (0.0068ms and 0.196 microJoule/Byte) then Alarm-net (0.0128ms and 0.351 microJoule/Byte) and BSN-care (0.0175ms and 0.53 microJoule/Byte). Moreover, from the results, it is also observed that biometric key generation mechanism not only provide random and unique keys but it also offer a trade-off between security and resource optimization. Thus, it can be concluded that the proposed framework has got both social and economic significance for real-time healthcare applications. © 2019 Elsevier B.V.

Future Generation Computer Systems

A joint resource-aware and medical data security framework for wearable healthcare systems

Resource allocation in cloud being NP-complete lacks a generalised optimal solution. In this work, we propose a nature-inspired ACO-Fuzzy framework based joint resource allocation algorithm for cloud datacenters. The algorithm assigns compute and network resources efficiently to minimize end-user cost. An ACO-based local search heuristic is used to discover the current status of resources and then a Fuzzy-based decision maker finds the most optimal set of compute and network resources minimising the end-user cost. Analytical and experimental evaluations validate the efficiency of joint allocation. Abbreviations: CSP: cloud service provider; VM: virtual machine; VMP: virtual machine placement; NIJA: nature-inspired joint allocation; DM: decision maker; WAN: wireless area network; ACO: ant colony optimisation; SDFF: server defined first-fit; GA: genetic algorithm; PSO: particle swarm optimisation; SA: simulated annealing. © 2019 Informa UK Limited, trading as Taylor & Francis Group.

Enterprise Information Systems

Nature-inspired cost optimisation for enterprise cloud systems using joint allocation of resources

Computers in Human Behavior

Fog computing-based intelligent healthcare system for the detection and prevention of mosquito-borne diseases

Fog computing is the backbone of modern healthcare systems, it not only cut-downs the associated treatment and medicine costs but also decreases the logistics requirements. Recently, both stationary and wearable systems are utilized for long-term monitoring of Electrocardiogram (ECG) signals in fog computing based medical applications. However, the comfort of monitored patients is not at a satisfactory level and therefore, a well-designed textile electrode with excellent signal quality and comfortability (SQC) plays a significant role in collecting ECG signals. In this study, in order to provide SQC optimization, a textile electrode with knitted structure and conductive material comprising cotton /nylon fiber coated silver is investigated. This textile composite is integrated to a wearable carrier (T-Shirt) with a miniaturized wireless sensing platform to collect ECG signals from the human. As a design strategy to acquire dimensional stability, the fabric was knitted with two layers that form the same technical face on both fabric surfaces. The conducted experiment elaborate that to find out a balance between the quality of signal and wearable comfort level by finely adjusting the composition of fiber type, yarn density, fabric pattern, fabric density, and thickness. From our experimental results, it is observed that textile electrodes having cotton (30) /nylon fiber coated silver (70) provides less air resistance (0.17 KPa•s/m), optimized tactile comfort (9/10), reasonable signal to noise ratio (SNR) value of 30.78dB, and better thermal conductivity (0.018W/m•K) than compared electrodes. Thus, it can be concluded that developed textile electrode can be useful for future research to offer the balance for SQC ratio for ECG measurement in fog computing based healthcare systems. © 2018 Elsevier B.V.

Optimization of signal quality over comfortability of textile electrodes for ECG monitoring in fog computing based medical applications

The Journal of Supercomputing

An augmented reality-supported mobile application for diagnosis of heart diseases

ES Energy & Environment

Near-Field Radiative Thermal Modulation by Tunneling Through Graphene Sheet

Robot-assisted therapy for rehabilitation of children with cerebral palsy - A complementary and alternative approach

IEEE Transactions on Biomedical Engineering

Heartbeats Based Biometric Random Binary Sequences Generation to Secure Wireless Body Sensor Networks

Fuzzy vault-based biometric security method for tele-health monitoring systems

Journal	Data powered by TypesetComputers & Electrical Engineering
Publisher	Data powered by TypesetElsevier BV
ISSN	0045-7906
Open Access	0