IRJET- A Survey on-Security for using Pervasive Healthcare Monitoring System in Mobile Cloud Computing

INTERNATIONAL RESEARCH JOURNAL OF ENGINEERING AND TECHNOLOGY (IRJET) E-ISSN: 2395-0056
VOLUME: 06 ISSUE: 04 | APR 2019 WWW.IRJET.NET P-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 3268
 A Survey On-Security for using Pervasive Healthcare Monitoring System
In Mobile Cloud Computing
D. Lekha1, A. Bhagyalakshmi2
Velammal Engineering College
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Abstract - In modern world more and more smart devices are implementing and that most popular equipment is mobile device.
Nowadays smart devices are improving the smart cities. The wireless sensor node are preventing the healthcare networked system
through the mobile cloud computing. Using the security key the encryption and decryption are generated in public sector in
wireless senor nodes. There are different healthcare center are achieving the mutual authentication and create a key for
protecting the communication with the help of Android app. It has three V’s: Velocity, Volume, Variety are available in big data
technology. The paradigm shift and growth interest are the number of factors that rising cost of illness. This paper discussed the
technology has the major role in cost curve and patient lifestyles in real-time healthcare monitoring system in cloud based
approaches.
Keywords - Healthcare Monitoring System, Cloud Computing, Mobile Pervasive Computing, System Converged.
1. INTRODUCTION
Nowadays mobile devices are playing major role in various useful tasks. In mobile devices are many apps [1]. Using this app
can check our health condition like blood pressure, weights, exercise etc. and mobile devices can use for booking hotels,
ordering foods, searching places, reading books etc. By sitting in place itself doctor can check the patient condition. Next
technology is cloud computing is can access to store the information this at any time and anywhere. Data is stored in cloud and
accessed in environments shared sophistically through internet [2]. Mobile Networks for social healthcare systems are
emerged as communications in health services. Big data also can store the information from the data base of cloud
storage.There is an app in mobile devices can check the heart rate of pulse in human body.This app can check heart rate with
the help of sensors.Using the sensors the mobile can check our whole body. This sensors has four pins in red, black, grey,
brown in color to connect in the mobile device board and other end in will connect in sensors board. The system is taken
from the source of network connected appropriate the system security in sensors board. The connection is correct
automatically the green light will blink otherwise there is no light. Smart phones and laptops are major advantages of the lie
cycles and at the same time there is also a disadvantages.
2. OVERVIEW OF THE WORK
With outstanding calibration ofthe mobile devices in cloud computing that stored the data in cloud to modify the data to cloud
contain many traffic. Due to this traffic the big data will stored the information in analytics monitoring the healthcare
system.To reduce the traffic in remote areas the computational nodes are introduced in wireless sensor nodes using this will
reduce the traffic. The topology of mesh ,ring, star are have the wireless sensor nodes to surround the network to reduce the
traffic in user providers.
3. DESCRIPTION
In the networked healthcare and it’s enabling the mobile cloud computing and big data. The hospital as many patient record to
store in database. Cloud is an open storage to store huge amount of data [3]. In patient body a coordinate node is inserted
using that node the doctors will check the patient heart rate, blood pressure etc. and can check the pregnancy women fetal
heart rate also. It is used by many tools like Google Refined Spreadsheet, Data Wrangler for cleaning and rearranging data,

Tableau Public it can turn data into simple to complex [4]. By handling the personalized medicine, reduce the cost of
healthcare and operational processors for better clinical facilitates.
All the patients’ data are updated in database with the help of IT professionals. In hospital and clinics the doctors and nurses
are updated the new patient and old patient record with the patient id number [5]. Physically organized by reducing the
hospital rates. It takes the exact care at exact time. By doing this many security problems will arises. The employees are using
the professional data and private data are in same equipment there will be a chances of causing attacks in the equipment. For
this problems there is no software developed methodologies only the symmetric key is encrypt and decrypt for every
encryption of information security. The anti-malware software in cloud based and local usage in next generation awareness to
secure the mobile devices [6].Each patient has one or more wireless body sensor nodes.This nodes monitor the patient in
remote healthcare center via in 3G/4G or WIFI network .It collect the personal information such as blood pressure
,temperature cardinal heart rates etc. and send the PHI through mobile devices, via Bluetooth or other communication
channel[7]. The medicine will updated in network for each disease there is a medicine. The trusted authority is accessed the
internet through base station with the help of some security functioning. While simultaneously two patients are registered in
trusted authority based on the handshake the private key s provided for the secure channel [8],[9]. In fig:1 tells that mutual
authentication, patient anonymity, patient traceability like that various security functions are required for patient treatment.
Fig 1: Internet of Patient in cloud.
The machine learning method healthcare monitoring systems are very personalized the concept of using smart devices
including the physical exercises, sleep trackers and stress detectors[10].In fig :1 Smart watches, Ring, Bracelets, Shoes, Glasses
are convenient platform for users to track the condition of the body .The control and application plane are have the multi-tier
architecture are protecting the patient record through device tier and collecting the information from edge tier and then
transmit to the internet[11]. While continuously performing many data transaction the traffic will obtain. To avoid traffic the
load balancer is maintained the healthcare application process. The user tier will pass the information to pre-processes to
draw data to sense the fusion and analysis gait module to form the short term data repository will continuously synchronized
to long term data repository. There will be two stages to execute for the user. Each user given the time to clear the traffic for
every 5 minutes or 20 seconds after the preceding user [12]. In order to analysis the data are store in cloud data center.

Fig 2 :Transaction in Base Station
This algorithm states that the mobile phones lie Samsung, Apple companies can have a health kit in mobile apps. This main
challenges that the base station will occur all over the mobile network in health monitoring system using the targeted low
capability of body sensor node [13]. It has sensing the data to generated physical condition of using apple watch in iphone.
During they transmitting the network through various base station in that some base station only have the service providers
to transmit the patient condition on behave of the cost based system. Sensing data for medicare in routing the base station rom
user service providers in the cost of the uplink and downlink communication cost minimization network [14]. Potential effect
of the healthcare domain are improving the technology in smart cities environment in fig:2. It leads the power and energy to
consolidate the standardized applications will deals our own personalized data is not secure in web applications [15].By
accepting the technologies many advantages are appear.
In this paper we discussed about the heart failure patients in healthcare monitoring system though the mobile computing
devices such as heart rate, blood pressure, weight, oxygen saturation [16]. Mobile devices are including the limitations are
throughout the life time.It will check the new born baby condition and while baby growing condition also can check in
technology. It has newly founded for the babies. Many organization system has developed the healthcare technologies in the
high level. It will store the patient details in the main frame computer and it will use the communication
Networkas personal computer [17]. It owns the organization system as high cost in hardware and software.
4. SYSTEM FEATURES
In this the mobile devices are used in the form of hardware based technology and moreover the complexity of hardware is
mainframe computers .(a)It will send the request and response through the client server computing of monitoring system in
the advantages of low (or) high level of personal computers. (b)Through the sense of internet computing the personal
computers and mobile devices are highly framable.

5. NETWORK SYSTEM COMPUTING
The service called the Platform as a service in that operating system is major play role ofLinux , Unix windows and application
in server database . Microsoft windows are another operating system in the mobile devices.
6. CLIENT- SERVER/ REQUEST RESPONSE COMPUTING
By defaultly all the computing devices are communication through the personalnetworks.Database Management system are
transaction in client then the exclusive process are managed in the structure query language database in fig 3.
7. INTERNET COMPUTING
The storage of data in system characteristics in mainframe of network system computing and the client server data are
stored in reques t response connectivity of the storage . It has the client server software application in that many process can
stored the data information.
8. ORGANIZATION OF THE SYSTEM
The total cost of the devices are very high or low in nature of hardware and software in the applicant software system. It has
security key usage while transmitting the data information from client to the server system.
Fig .3 Client server Transaction
9. DESCRIPTION OF THE TEXTURE
From the above mention scenario many cases of mobile health development are proposed very high performance through the
internet computing by the usage of software development. It has no software development. It has only security keys or the
transaction of the availability of the medicine cost and doctors cost and hospital travelling charges are savage these money.
Through the cloud computing and big data analytics are shared the networks space to the medical biometrics.

10. CONCLUSION
Mobile technology is a platform for the health delivery monitoring system at anytime and anywhere. It survives many
technology like booking tickets, booking cabs, ordering foods, dresses, cosmetics etc. A cloudlet infrastructures has modulated
the features in big data analytics in nature to moduled the consumption of the healthcare. Next generation has follow the
standardized tasks for trend appear in the smart cities. Mobile technology has disabling the rising cost of hospitalization it
decreases the eldering population in illness through the better lifestyle environment will be designed in the future generation
of the smart modern country in the world. To the management of the mobile computing concept are used for many purpose in
the monitoring system.
11. REFERENCES
1.Lo’al.Tawalbeh, Rashid Mehmood, ElhadjBenklia, Houbing Song, ’’Mobile Cloud Computing Model and Big Data Analysis for
Healthcare Applications’’IEEE volume 4 Oct 15, 2016.
2. SilasL.Albuquerque and Paulo R.L. Gondim ’’Secuity in Cloud Computing-Based Mobile Health’’IEEE compute society
May/June 2016.
3. Debiao He, Neerajkumar, Huaqun Wag, Lina Wang, Kim-Kwang Raymond Choo, Alexey Vinel’’A Provably-Secure Coss-
Domain Handshake Scheme with Symptoms-Matching for Mobile Healthcare Social Network’’IEEE volume15, No4, July/August
2018.
4. AhmetC.Baktir,CanTunca, AtayOzgovde ,GulustuSalu, CemErso’’SDN-Based Multi-Tier Computing andCommnunication
Architecture for Pervasive Healthcare’’IEEE October 25, 2018.
5.Lin Gu, Deze Zeng, Song Guo, Ahmed Barnawi, Yong Xiang’’Cost Efficient Resource Management in Fog Computing Supported
Medical Cyber –Physical System’’ IEEE 3 March, 2017.
6. Darrellielde, U.JohnTanik, Chistiane C. Gattaz, Murat Tanik, FuadSobrinho ’’Mobile Healthcare Delivery: A Dynamic
Environment Whee Healthcare, Mobile Technology, Engineering, and Individual Lifestyle Cnverge’’IEEE 2017.
7.TshiamoSigwele, Yim Fun Hu, Muhammad Ali and JiachenHou “Intelligent and Energy Efficient Mobile SmartphoneGateway
for Healthcare Smart Devices based on 5G” IEEE 2018.
8. Thahamuhammed ,Rasidmehmood&IyadKatib
“UbeHealth:APersonalized Ubiquitous Cloudand Edge-Enabled Networked HealthcareSystem for Smart Cities” IEEE, Volume 6
2018.
9. SuhailaHabeeb and Lo’ai A. Tawalbeh“Feasibility Study and Requirements for Mobile Cloud Healthcare Systems in Saudi
Arabia” IEEE 2018.
10.Lo’ai A. Tawalbeh and SuhailaHabeeb “An Integrated Cloud Based Healthcare System” IEEE 2018.
11. SantoshiKumari, Haripriya.A,Aruna.A, Vidya.D.S, Nithya.M.N “Immunize - Baby Steps for smart healthcare” IEEE 2017.
12. JinglinQiu, Xueping Liang, Sachin Shetty &Daniel Bowden “Towards Secure and Smart Healthcare in Smart
Cities Using Blockchain” IEEE 2018.
13. Erick Candela-Mendoza, Lilian Cruz-Ipanaque& Jimmy Armas-Aguirre “Mobile Technology Model to Ambulatory
Healthcare Information online Using Cloud Platform” IEEE 2018.
14. Cheng Xie, Member, IEEE, HongmingCai, Senior Member, IEEE, Yun Yang*, “User Profiling in Elderly Healthcare Services in
China: Scalper Detection” IEEE 2018.

15. Ji Kwang Kim1, Jung Hwan Oh, Oh SeongGwon , JungWoong Yang, and SeungEun Lee. “Real-time PPG Monitoring System
for Mobile Healthcare Devices” IEEE 2018.
16. Zhang Yi, Zhu Shan, Liu Hong-xin, Chen Cheng &Wang Zhu-juan “Structural Healthcare Services For Multi-users Based on
Spectrum Sharing Strategy” IEEE 2018.
17. Andreas Triantayllids, Carmelo Velado, Syed Ahmer Shah, Lionel Tarassenko,TraceyChantler, Chris Paton, KazamRahimi
“Supporting Heart failure Patients Through Personalized Mobile Health Monitoring.” IEEE 2018.

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