Preventing Mirror Problem And Privacy Issues In Multistorage Area With Dimensionality Reduction

International Journal of Scientific Research and Engineering Development-– Volume 2 Issue 5, Sep – Oct 2019
Available at www.ijsred.com
ISSN : 2581-7175 ©IJSRED: All Rights are Reserved Page 860
PREVENTING MIRROR PROBLEM AND PRIVACY
ISSUES IN MULTISTORAGE AREA WITH
DIMENSIONALITY REDUCTION
R.Mahendran1
, C.Karthik2
, M.Jothimani3
, K.P.Uvarajan4
Assistant Professor, ECE, K.S.R. College of Engineering, Tiruchengode1,2,3,4
rmahendranme@gmail.com1
,rpckarthikraja@gmail.com2
,mjothimanibe@gmail.com3
,uvaraj.kp@gmail.com4
Abstract:
In previous research of privacy issues in data storage is usually a patient to create, and control the personal
health data in one place through the web, which has made the storage, retrieval, and sharing of the medical
information efficiently. Each patient is promised the full control of the medical records and can share the health data
with a wide range of users, including family members, friends or healthcare providers. However, there have been
wide privacy concerns as personal health information could be exposed to those third party servers and to
unauthorized parties. To assure the patients control over access to their own Personal Health Records (PHR), this
method encrypts the PHR before given to third parties. This paper proposes a novel patient-centric framework and
also mechanisms for data access control to records stored in semi-trusted servers. To achieve scalable data access
control for records, Encryption techniques are introduced to encrypt each patient’s PHR data. Different from
previous works in secure data outsourcing, it is now focused on the multiple cloud mirror scenario, and adopt
different security mechanism such as different encryption methods in each attributes with the capability of the cloud
software architecture.
Keywords: Privacy, Personal Health Records, Encryption, Cloud.
I. INTRODUCTION
The cloud is a familiar cliché is a metaphor
for the Internet, but when combined with computing,
the meaning gets bigger and fuzzier. Some analysts
and vendors define cloud computing narrowly as an
updated version of utility computing, basically virtual
servers available over the Internet. Others go very
broad, arguing anything users consume outside the
firewall is in the cloud, including conventional
outsourcing.
Cloud computing [1] comes into focus only
when we think about what IT always needs: a way to
increase capacity or add capabilities on the fly
without investing in new infrastructure, training new
personnel, or licensing new software. It encompasses
any subscription-based or pay-per-use service that, in
real time over the Internet, extends IT's existing
capabilities. InfoWorld talked to dozens of vendors,
analysts, and IT customers to tease out the various
components of cloud computing. Based on those
discussions, here's a rough breakdown of what cloud
computing is all about:
Software as a Service (SaaS)
In the SaaS model, cloud providers install
and operate application software in the cloud and
cloud users access the software from cloud clients.
Cloud users do not manage the cloud infrastructure
and platform where the application runs. This
eliminates the need to install and run the application
on the cloud user's own computers, which simplifies
maintenance and support. Cloud applications are
different from other applications in their scalability-
which can be achieved by cloning tasks onto multiple
virtual machines at run-time to meet changing work
demand.
Platform as a Service (PaaS)
In the PaaS [2] models, cloud providers
deliver a computing platform, typically including
operating system, programming language execution
environment, database, and web server. Application
developers can develop and run their software
solutions on a cloud platform without the cost and
RESEARCH ARTICLE OPEN ACCESS

complexity of buying and managing the underlying
hardware and software layers.
The computer and storage resources scale
automatically to match application demand so that
the cloud user does not have to allocate resources
manually. The latter has also been proposed by an
architecture aiming to facilitate real-time in cloud
environments.
Infrastructure as a Service (IaaS)
In the most basic cloud-service model,
providers of IaaS offer computers – physical or
virtual machines – and other resources. A hypervisor,
such as OpenStack, Xen, Hyper-V runs the virtual
machines as guests. Pools of hypervisors within the
cloud operational support-system can support large
numbers of virtual machines and the ability to scale
services up and down according to customers varying
requirements. IaaS clouds often offer additional
resources such as a virtual-machine disk image
library, raw block storage, and file or object storage,
firewalls, load balancers, IP addresses, Virtual Local
Area Networks (VLANs), and software bundles.
IaaS-cloud providers supply these resources on-
demand from their large pools installed in data
centers. For wide-area connectivity, customers can
use either the Internet or carrier clouds. Recently, this
paradigm has been extended towards sensing and
actuation resources, aiming at providing virtual
sensors and actuators as a service.
II. BACKGROUND
The existing system is maintaining all
branch patient’s information in hospitals storage
space. More number of IT professionals is required to
keep availability of data at all time. More number of
hardware assets and their management cost is also
more
The importance of ensuring the remote data
integrity for hospitals has been highlighted by some
research works. These techniques, while can be
useful to ensure the storage correctness without
having users possessing data, cannot address all the
security threats in cloud data storage, since they are
all focusing on single server scenario and most of
them do not consider dynamic data operations. As a
complementary approach, researchers have also
proposed distributed protocols for ensuring storage
correctness across multiple servers to peers.
Again, none of these distributed schemes is
aware of dynamic data operations. As a result, their
applicability in cloud data storage can be drastically
limited. However, while providing efficient cross
server storage verification and data availability
insurance, these schemes are all focusing on static or
archival data. As a result, their capabilities of
handling dynamic data remains unclear, which
inevitably limits their full applicability in cloud
storage scenarios. The presented system classifying
the data based on the clustering work with similar
items. So the data classification is not accuracy. The
data is classified based on approximate k-NN search
in high-dimensional spaces and then processed in
another manner of a data reorganization method.
The thesis deals with the hospital branch and
patients management. Since cloud computing
delivers convenient, on-demand access to shared
pools of data, applications and hardware over the
internet. It provides unlimited infrastructure to store
and execute patient data and program. The
convenient PHR services for everyone, there are
many security and privacy risks which could impede
its wide adoption. The main concern is about whether
the patients could actually control the sharing of their
sensitive personal health information, especially
when they are stored on a third-party server which
people may not fully trust.
A PHR [3] system where there are multiple
owners and users. The owners refer to patients who
Frequently Used Notations have full control over
their own PHR data, i.e., they can create, manage,
and delete it. There is a central server belonging to
the PHR service provider that stores all the owners
PHRs. The users may come from various aspects, for
example, a friend, a caregiver or a researcher. Users
access the PHR documents through the server in
order to read or write to someone’s PHR, and a user
can simultaneously have access to multiple owners’
data. Due to this redundancy the data can be easily
modified by unauthorized users which can be stored
in the database. This leads to loss of data privacy and
security to database. The proposed scheme ensures
that cyclic redundancy check and time-tested
practices and technologies for managing trust
relationships in traditional enterprise environments
can be extended to work effectively in both private
and public clouds. Those practices include data
encryption, strong authentication and fraud detection,
etc.
III. PROPOSED DESIGN
A PHR service allows a patient to create,
manage, and control her personal health data in one
place through the web, which has made the storage,

retrieval, and sharing of the medical information
more efficient. Especially, each patient is promised
the full control of their medical records and can share
their health data with a wide range of users, including
healthcare providers, family members or friends.
The dissertation is required to eliminate the
risk in unavailability of one branch information in
other branch. The thesis is using an approach such
that with the cloud storage space, the hardware and
software maintenance risk is reduced. Owing to the
number of drawbacks evident in the earlier system,
the concept is being developed to computerized
which leads to effectiveness of the users and their
activities.
This facility enables people to record
information that will substantiate achievement
towards their objectives and goes a long way to
resolving the issue of forgotten information that is
relevant to the review. Information can be recorded
all the way and assists both admin and user to recall
information that will assist in the review.
Figure 1 Proposed framework for patient-centric,
secure and scalable PHR sharing on semi trusted
storage under multiowner settings.
The framework is illustrated in Figure 1. We
term the users having read and write access as data
readers and contributors, respectively. In our
framework, there are multiple SDs, multiple owners,
multiple AAs, and multiple users. In addition, two
ABE [4] systems are involved: for each PSD the
YWRL’s revocable KP-ABE scheme is adopted; for
each PUD, our proposed revocable MA-ABE scheme
is used.
With distributed verification of erasure-
coded data, the error recovery algorithm achieves the
storage correctness insurance as well as data error
localization. Whenever data corruption has been
detected during the storage correctness verification,
this scheme can almost guarantee the simultaneous
localization of data errors.
In this thesis, to preferred implementation of
k-NN search concept for classifying the patient
record by Euclidean distance metric for analyzing the
similar data based on one patient to another patient
with the high dimensionality reduction technique.
IV. PREVENTING PRIVACY ISSUES BY
DIFFERENT ENCRYPTIONS IN CLOUD AREA
A. Attribute Based Encryption
The main goal of the framework is to
provide secure patient-centric PHR access and
efficient key management at the same time. The key
idea is to divide the system into multiple security
domains namely, PUblic Domains (PUD) and
PerSonal Domains (PSD) according to the different
user’s data access requirements. The users who make
access based on their professional roles, such as
administrator, patients as users, and cloud provider.
In practice, a PUD can be mapped to an independent
sector in the society, such as the health care,
government, or insurance sector. For each PSD, it
users are personally associated with a data owner
(such as family members or close friends), and they
make accesses to PHRs based on access rights
assigned by the owner.
B. Triple DES Encryption Standard
Triple Data Encryption Algorithm is a
symmetric-key block cipher, which applies the Data
Encryption Standard (DES) [5] cipher algorithm
three times to each data block. It is three times slower
than regular DES but can be billions of times more
secure if used properly. Triple DES enjoys much
wider use than DES because DES is so easy to break
with today's rapidly advancing technology. This just
serves to illustrate that any organization with
moderate resources can break through DES with very
little effort these days. No sane security expert would
consider using DES to protect data. Triple DES was
the answer to many of the shortcomings of DES.
Since it is based on the DES algorithm, it is very easy
to modify existing software to use Triple DES.
It also has the advantage of proven
reliability and a longer key length that eliminates
many of the shortcut attacks that can be used to
reduce the amount of time and it breaks DES.
However, even this more powerful version of DES
may not be strong enough to protect data for very
much longer. The DES algorithm itself has become

obsolete and is in need of replacement. To this end
the National Institute of Standards and Technology
(NIST) is holding a competition to develop the AES
as a replacement for DES.
The AES will be at least as strong as Triple
DES and probably much faster. Many security
systems will probably use both Triple DES and AES
for at least the next five years. After that, AES may
supplant Triple DES as the default algorithm on most
systems, if it lives up to its expectations. But Triple
DES will be kept around for compatibility reasons for
many years after that. So the useful lifetime of Triple
DES is far from over, even with the AES near
completion. For the foreseeable future Triple DES is
an excellent and reliable choice for the security needs
of highly sensitive information.
Triple DES is simply another mode of DES
operation. It takes three 64-bit keys, for an overall
key length of 192 bits. In Private Encryptor, user
simply type in the entire 192-bit (24 character) key
rather than entering each of the three keys
individually. The Triple DES DLL (Dynamic Link
Library) then breaks the user provided key into three
sub keys, padding the keys if necessary so they are
each 64 bits long. The procedure for encryption is
exactly the same as regular DES, but it is repeated
three times. In figure 2, the data is encrypted with the
first key, decrypted with the second key, and finally
encrypted again with the third key.
Figure 2 Structure of triple DES
Triple DES runs three times slower than
standard DES, but is much more secure if used
properly. The procedure for decrypting something is
the same as the procedure for encryption, except it is
executed in reverse. Like DES, data is encrypted and
decrypted in 64-bit chunks. Unfortunately, there are
some weak keys that one should be aware of it. If all
three keys, the first and second keys, or the second
and third keys are the same, then the encryption
procedure is essentially the same as standard DES.
This situation is to be avoided because it is the same
as using a really slow version of regular DES.
Note that although the input key for DES is
64 bits long, the actual key used by DES is only 56
bits in length. The least significant (right-most) bit in
each byte is a parity bit, and should be set so that
there are always an odd number of 1’s in every byte.
These parity bits are ignored, so only the seven most
significant bits of each byte are used, resulting in a
key length of 56 bits. This means that the effective
key strength for Triple DES is actually 168 bits
because each of the three keys contains 8 parity bits
that are not used during the encryption process.
C. Advanced Encryption Standard
AES Crypt is a file encryption software
available on several operating systems that uses the
industry standard Advanced Encryption Standard to
easily and securely encrypt files. Using a powerful
256-bit encryption algorithm, AES Crypt can safely
secure the most sensitive files. Once a file is
encrypted, user does not have to worry about a
person reading the sensitive information, as an
encrypted file is completely useless without the
password. It simply cannot be read.
AES Crypt is the perfect tool for anyone
who carries sensitive information with them while
traveling, uploads sensitive files to servers on the
Internet, or wishes to protect sensitive information
from being stolen from the home or office. AES
Crypt is also the perfect solution for those who wish
to backup information and store that data at a bank, in
a cloud-based storage service, and any place where
sensitive files might be accessible by someone else.
AES Crypt is completely free open source
software. Since it is open source, several people have
contributed to the software and have reviewed the
software source code to ensure that it works properly
to secure information.
D. Data Encryption Standard
Encryption is the process of converting a
plaintext message into cipher text which can be
decoded back into the original message. An
encryption algorithm along with a key is used in the
encryption and decryption of data. There are several
types of data encryptions which form the basis of
network security. Encryption schemes are based on
block or stream ciphers.

The type and length of the keys utilized
depend upon the encryption algorithm and the
amount of security needed. In conventional
symmetric encryption a single key is used. With this
key, the sender can encrypt a message and a recipient
can decrypt the message but the security of the key
becomes problematic. In asymmetric encryption, the
encryption key and the decryption key are different.
One is a public key by which the sender can encrypt
the message and the other is a private key by which a
recipient can decrypt the message.
DES is the archetypal block cipher - an
algorithm that takes a fixed-length string of plaintext
bits and transforms it through a series of complicated
operations into another cipher text bit string of the
same length. In the case of DES, the block size is 64
bits. DES also uses a key to customize the
transformation, so that decryption can supposedly
only be performed by those who know the particular
key used to encrypt. The key ostensibly consists of 64
bits; however, only 56 of these are actually used by
the algorithm. Eight bits are used solely for checking
parity, and are thereafter discarded. Hence the
effective key length is 56 bits, and it is always quoted
as such.
E. Error Recovery Algorithm
Error localization is a key prerequisite for
eliminating errors in storage systems. It is also of
critical importance to identify potential threats from
mirror problem. The scheme outperforms those by
integrating the correctness verification and error
localization. The user can reconstruct the original file
by downloading the data vectors from the first m
servers, assuming that they return the correct
response values. Notice that the verification scheme
is based on random spot-checking, so the storage
correctness assurance is a probabilistic one.
F. K-Nearest Neighbor Search
k-NN is a non parametric lazy
learning algorithm. When user say a technique is non
parametric, it means that it does not make any
assumptions on the underlying data distribution. This
is pretty useful, as in the real world, most of the
practical data does not obey the typical theoretical
assumptions made.
Non parametric algorithms like k-NN come
to the rescue here. It doesn’t use the training data
points to do any generalization. In other words, there
is no explicit training phase or it is very minimal.
The training phase is pretty fast. Lack of
generalization consumes that k-NN keeps all the
training data. More exactly, all the training data is
needed during the testing phase. This is in contrast to
other techniques like Support Vector Machine (SVM)
where it can discard all non support vectors without
any problem.
Nearest Neighbor based Content Retrieval
This is one the fascinating application of k-
NN. Basically user can use it in Computer Vision for
many cases. It can consider handwriting detection as
a rudimentary nearest neighbor problem. The
problem becomes more fascinating if the content is a
data given a data find the video closest to the query
from the database.
If user wants to prepare a dictionary for
American Sign Language (ASL) [6] so that user can
query it doing a gesture. Now the problem reduces to
find the possibly k closest gestures stored in the
database and show to user
.
V. IMPLEMENTATION RESULTS
• The security of the proposed enhanced PHR
sharing solution is implemented in the application
and cloud area.
• The DES, Triple DES and AES algorithms
in cloud environment, emphasizing possible
improvements and vulnerabilities in
implementation of cryptographic algorithms,
usage of cryptographic frameworks and libraries,
as well as the speed of execution of implemented
cryptographic algorithms.
• Triple DES: It was enhancement of DES
and used to remove the mid-in-the-middle attack
occurred in 2-DES. In this 3 times iterations of
DES encryption on each block is performed.
• In Triple-DES the 3-times iteration is
applied to increase the encryption level and
average time. Common method of Triple-DES is
Minus Encrypt – Decrypt - Encrypt (-EDE). Each
iteration of 3-DES using-EDE will encrypt a block
using a 56-bit key.
• After encryption use a different 56-bit key to
decrypt the block. On the last pass, a 56-bit key is
used to encrypt the data again. This is equivalent to
using a 168-bit encryption key.
• The algorithm is most popular and a
symmetric key cryptographic algorithm. It may
used to provide both secrecy and data
authentication. It uses the prime number to
generate the public and private key based on

mathematical fact and multiplying large numbers
together.
The storage size of AES, DES and Triple DES
algorithm is high in encrypting the data are different
in length. Throughput of the encryption algorithms
is calculated by dividing the total plaintext in
Megabytes encrypted on total encryption time for
each algorithm. Thus, if throughput increased than
power consumption decreased.
Table 1 evaluates the plain data size and
encrypted data storage size in the tabular format and
these results are represented in the chart format in the
Figure 3. In this visit details, to process ten patients
records along with patient identity number. Each
patient record is differing from another patient. Here
visit details are encrypted using DES encryption
algorithm.
Patient
Id
Source Size (In
Bytes)
Encrypted Size (In
Bytes)
1 68 212
2 82 232
3 104 272
4 110 252
5 60 212
6 74 212
7 112 272
8 91 252
9 120 272
10 141 316
Table 1 Visit Details
0
50
100
150
200
250
300
350
1 2 3 4 5 6 7 8 9 10
Source Size ( In Bytes)
Encrypted Size(In Bytes)
Patient Id
Figure 3 Chart representation for Visit Details
In the receipt details, the record should
process in the application with the specification
details such as branch id, patient Id, data of receipt,
remarks, cheque number, consulted doctor name,
visited branch name. This information’s are
encrypted using Triple DES algorithm and stored in
the main server and multi cloud server at
simultaneously. Table 2 is used to represent the
receipt details of the patients and Figure 4 is used
to represent the pictorial chart representation of the
patients receipt details.
Patient
Id
Source Size ( In
Bytes)
Encrypted Size(In
Bytes)
1 68 140
2 91 164
3 114 196
4 86 164
5 132 216
6 66 144
7 92 184
8 50 120
9 66 144
10 101 184
Table 2 Receipt Details

0
50
100
150
200
250
1 2 3 4 5 6 7 8 9 10
Patient Id
Figure 4 Chart representation of Receipt Details
In the Prescription details, the record should
process in the application with the specification
details such as branch id, patient Id, date, tablet name
and with its quantity, charges of the tablet, remarks,
consulted doctor name, visited branch name. This
information’s are encrypted using AES algorithm and
stored in the main server and multi cloud server at
simultaneously. Table 3 is used to represent the
prescription details of the patients and Figure 5 is
used to represent the pictorial chart representation of
the patient’s prescription details.
Patient
Id
Source Size ( In
Bytes)
Encrypted Size(In
Bytes)
1 63 232
2 76 232
3 92 272
4 74 232
5 131 316
6 103 276
7 77 232
8 66 232
9 79 252
10 116 276
Table 3 Prescription Details
0
50
100
150
200
250
300
350
1 2 3 4 5 6 7 8 9 10
Patient Id
Figure 5 Chart representation of Prescription
Details
VI. CONCLUSION
It is believed that almost all the system
objectives that have been planned at the
commencement of the software development and the
implementation process of the dissertations are
completed. A trial run of the system has been made
and is giving good results the procedures for
processing is simple and regular order. The process of
preparing plans been missed out which might be
considered for further modification of the application.
The project effectively stores and retrieves the
records from the cloud space database server. The
records are encrypted and decrypted whenever
necessary so that they are secure. In this thesis, it
describes the design and prototype implementation of
a social healthcare network over the cloud. The
system is secured with a trust-aware attribute-based
access control. The work addresses an unmet need in
social healthcare networking -emotional support, and
demonstrates social healthcare network application in
a real cloud-computing environment.
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