Cryptography in the Healthcare Sector With Modernized Cyber Security

Abstract

Cryptography is an indispensable tool used to protect information in any organization; providing secure transmission over the Internet. The major challenge faced by health-sector is data security, and to overcome this several advancements in medicine and biomedical research have proven to increase computer processing in data security. The study focuses on cryptography, the most emerging field in computer industries. Both artificial intelligence and quantum technology are both transforming the health sector in regard to cybersecurity. In this study, the AES algorithm is a cryptographic cipher used. One such application is implemented and is responsible for handling a large amount of the information in the health sector. An application with a double Hashing algorithm is accomplished to can maintain the data in a secure fashion.

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Chapter 8
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DOI: 10.4018/978-1-7998-2253-0.ch008
ABSTRACT
Cryptography is an indispensable tool used to protect information in any organization;
providing secure transmission over the Internet. The major challenge faced by health-
sector is data security, and to overcome this several advancements in medicine and
biomedical research have proven to increase computer processing in data security.
The study focuses on cryptography, the most emerging field in computer industries.
Both artificial intelligence and quantum technology are both transforming the health
sector in regard to cybersecurity. In this study, the AES algorithm is a cryptographic
cipher used. One such application is implemented and is responsible for handling a
large amount of the information in the health sector. An application with a double
Hashing algorithm is accomplished to can maintain the data in a secure fashion.
Cryptography in the
Healthcare Sector With
Modernized Cyber Security
Prisilla Jayanthi
https://orcid.org/0000-0002-4961-9010
K. G. Reddy College of Engineering and Technology, Hyderabad, India
Muralikrishna Iyyanki
Defence Research and Development Organisation, India

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Cryptography in the Healthcare Sector With Modernized Cyber Security
INTRODUCTION
Grand View Research Inc. in a statement announced by that “the global healthcare
biometric market is expected to reach USD 14.5 billion by 2025.” In this regard,
an insistent for Electronic Health Records (EHR) was raised by health system and
hospitals. Hence the need to computerize the health databases drives an insistent
for healthcare biometrics over the prognosis term of the patient. The concern is over
protecting the data from intruders and reduces fraud for providers and financiers by
payment collection through automated process, and increases patient contentment.
The science of shielding confidential information from unauthorized access,
by making sure about data integrity and authentication is cryptography. The
technique of hashing makes it more indispensable for ensuring that the transmitted
messages will not be tampered. The concept of fingerprints, facial recognition and
iris recognition are techniques derived from Artificial Intelligence. In this chapter
Advanced Encryption Standard (AES) algorithm and blockchain (BC) are discussed
to understand the need to safeguard and protect the electronic health data in more
secure manner.
The protection of data is required at every phase; the three phases of data shown
in figure 1 are: 1. data in action; 2. data in use; and 3. data at rest. The data in action
is the one which moves across the various networks, from system to system placed
at various locations. The data in use is frequently updated and altered on usage.
Figure 1. Data in three phases

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Cryptography in the Healthcare Sector With Modernized Cyber Security
The data at rest is the huge one with volume increasing day-to-day and becomes a
concern to businesses, government agencies and any other organization. The data
is kept unused and inactive for longer time. Most of theft takes place on the data
stored as backup. Hence, encrypting the data in every phase is essential.
NECESSITY OF CRYPTOGRAPHY IN HEALTHCARE
For any database which contains digital data, the need for data security is very
essential for protecting data from any unauthorized users. Data stored on disk for
longer period of time must be protected using disk encryption method known as on-
the-fly encryption. Implementing hardware device security to such long-time data
storage prevent malicious users or a data breach. One such application of hardware
security is biometric technique which prevents malicious users from logging in,
logging out and/ or tampering the privileges and is implemented in this chapter.
Authentication is verifying the user’s identity. It has two phases - identification
and actual authentication. In identification phase, any individual’s identity is
provided in the scheme of a user ID to the security system. The security system
examines all the abstract objects and maps the actual user, and grants permission.
This is carried out when the user provides indication to prove the specification to
the system. The authentication phase involves claiming of user identity by checking
user-provided evidence.
Encryption is the technique of encoding a message or information in which only
approved parties can access it. The algorithm generates pseudo-random encryption key.
The two encryptions used are symmetric and asymmetric encryption. In symmetric,
the encryption and decryption keys are the same. Communicating groups use the
same key for secure communication. In asymmetric, the encryption key is published
for anyone (publicly) and receiving team has the access to read the messages using
the decryption key known as private key.
The encryption of data at rest uses AES or RSA (Rivest–Shamir–Adleman)
algorithms. Cryptography will be implemented on the database housing the data
on the physical storage. In this case study, AES is implemented on the Electronic
Health Record databases.
Biometric in Industries
Biometric is a part of security in any industries as it gives the measurement and
numerical analysis of person’s unique physical and behavioral characteristics. For
identifying any individual, biometric can be used for proof of identity and right of
control, the one under surveillance. One can find it difficult for breaking into a system

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with biometrics. The device measures unique features of a person, such as voice
pattern, the iris, or fingerprint patterns. The biometric is broadly classified into two
categories such as physiological and behavioral where face recognition, fingerprints,
hand / palm, iris identification, DNA falls into the physiological categories. The
keystroke, signature, and voice pattern fall under behavioral categories shown in
figure 2.
Voice Print
As the growing population needs a secure means for settling the disbursement, in
and around the workplace, people found more comfortable with biometrics. One
such biometric is voice authentication, which discovers wider expansion across
trading activity, including healthcare, financing companies, and educational system.
Voice recognition systems monitor the rhythm and accent, in addition indicates the
structure of the larynx, nostril passage, and person’s vocal tract, to identify and
validate an individual.
(Chinnaswamy, 2018) discusses about the voice recognition system capturing the
voices by sound tracking the name, age, address, and a set of secret sound notes and
analyzes the speech and breathing patterns and stores it. Further the voice print is
encrypted and stored in the Active Directory in user’s authentication data, along with
Figure 2. Types of biometric for human identification

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added authentication credentials. When a person signs up for voice authentication
calls, the voice is coordinated with the voice print stored in the Active Directory,
ensuing in speedy and unified verification. This voiceprint recognition system is
referred as a Speaker Recognition System (SRS).
In a case study on voice prints suggested that each individual’s voice will be
different because the structure of the vocal cords, vocal cavity, oral and nostril
cavities is unique to every individual. Later the comparison of two recorded speeches
is carried out by spectrogram or the voice prints for the identification purpose are
called as voice fingerprinting. The person’s voice changes over time of the individual
aging; at time due to stress, illness and alcoholism. The person’s accent may also
vary as they move from one region to another. The best saying “garbage in, garbage
out” - garbage may come from various background similar to the sounds such as
trouble-some voices, music, or any machine noise that adds to the internal voice
while recording. If data received are unclear, analyzer produces conclusions that
are incorrect as described (Parmar & Udhayabanu, 2012).
Fingerprints and Facial Recognition
The biometric inputs for fingerprints and face identity results proved their results
accurately on the image quality received. Figure 3 represents how the fingerprints
are scanned for the biometric and later stored in the form of matrix of 1’s and 0’s.
This matrix is stored for further use of the security need which is implemented on
regular source. The data captured is encrypted using Advanced Encryption Standard
algorithm in figure 4 and then stored in the database.
Face recognition is a three-step process. Initiating with the subject picture and
making an effort to identify a person in the given image. The system locates the
individual’s head and eyes. A face signature is developed in matrix form centered
on the individual’s face characteristics. Comparing this matrix with the database in
figure 5 and generating a similar score for each comparison in figure 6.
The biometric system works on two types of comparisons namely verification
and identification. The automated facial image quality evaluation software (AFQES)
module captures real-time facial image and automated fingerprint identification
Figure 3. The representation of fingerprints in form of 1’s and 0’s

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systems (AFIS) module for obtaining fingerprints as discussed (Ko & Krishnan,
2003). The database of the faces of a person is collected in different angles with
different moods in figure 5. In this study as only one pose of photo was given, the
photos in different angles are shown in the database. The database will consist of
doctors, surgeons, and clinicians and other staff of health care center.
(Ablayev et al., 2016) introduced the quantum fingerprinting computational aspects
and clarifies the properties of cryptographically quantum hashing, and thereby the
possible use of quantum hashing for quantum hash-based message authentication
codes is done. (Buhrman et al., 2001) describes about quantum fingerprints in a
case study where the entire group analyzed fingerprints using without shared key
and shared key. In without shared key requires fingerprints of Θ (√n) are sufficient
whereas for shared key requires a fingerprints of length (n). Next, the scheme with
a shared quantum key of O(log n) that requires fingerprints of length O(log n) bits.
The condition was relaxed to the error probability of O (1= nc) (where c is constant)
with classical keys and fingerprints of length O(log n).
(ElDahshan et al., 2017) proposed a quantum face authentication method. This
method is for face boundaries detection, image resizing, and removal of any noise,
feature extraction, matching and decision. Also the method used QFWT (Quantum
Fast Wavelet Transform) and QFT (Quantum Fourier Transform) in extraction phase.
In this study, the doctor’s photos were taken for face recognition and are
authenticated for accessing the electronic health records. The faces and eyes in the
photos are identified by the square block using the software python code on Spyder,
a cross-platform shown in figure 7 and figure 8.
Figure 4. Implementation of AES algorithm for fingerprints

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Figure 5. Sample set of facial database
Figure 6. Cipher facial recognition database

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CRYPTOGRAPHY: QUANTUM TECHNOLOGY- QUANTUM KEY
Cryptography is a technique for secure communication with the third party. The aim of
cryptography is that the sender and receiver will communicate with the unintelligible
with third parties. This gives an authentication of messages to demonstrate that the
data were not altered while in transit. Both the sender and receiver share the secret
key which is a random sequence number, a valuable strength for both. Quantum
communications makes the secret key distribution possible. The key distribution
process is accomplished by quantum cryptography and encrypted message is not
transmitted. This is known as quantum key distribution, proposed by (Hughes et
al., 1995). The emerging field of physics and engineering is termed as quantum
technology, which creates practical applications - such as quantum computing,
quantum sensors, quantum cryptography, and quantum simulation. The quantum
technology is paving its way in keeping data secure.
Health Sector is the largest source of repository as it consists of all the patients
complete information and this huge data is stored on electronic device. This data can be
easily attacked by any active attacker, lost, stolen or data breaches. The health records
have family name, addresses, state and ZIP code, social security number / Aadhaar card
number/ pan card number, email addresses, phone numbers and insurance policy ID
numbers, among the general information provided by the patients shown in figure 9.
Figure 7. Authenticated doctors after face recognition
Figure 8. Iris detection

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The figure 10 shows the encrypted data of the health record at healthcare center.
This healthcare data is a precious and is prey for the ransomware, spear phishing
attacks or any other attacks.
BLOCKCHAIN – INDUSTRIES – HEALTHCARE
An increasing list of records, named as blocks are interconnected using cryptography
is known as blockchain (BC). Every individual block comprises of the following:
a cryptographic hash of the preceding block, a timestamp, and transaction data. As
the number of applications of BC technology is increasing rapidly, the knowledge in
realization of the technology and its potentials is accordingly extreme. The potential
for dramatic change in the society with the developments and implementation of BC
includes improvements in the healthcare information exchange. BC characteristics
are its nature of de-centralization, openness and lesser privilege for permission that
Figure 9. Electronic health record for patient entries
Figure 10. Health Records in encrypted form

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Cryptography in the Healthcare Sector With Modernized Cyber Security
offer a unique solution for any industry but here in this context it is healthcare. The
development of cryptocurrencies drives current usage by reaching global greater
than 20 million users; in the other areas, the use of BC is growing was discussed
(Prokofieva & Miah, 2019).
Several BC facilities in integrating and encrypting digital assets comprising
of health records or dispensation claims on a ledger. The ledger ensures patient
confidentiality and protection of relevant data thereby ensuring regulatory compliance,
e.g. HIPAA - Health Insurance Portability and Accountability Act. Medical chain is
operational engaged with EHR Blockchain Company, in enabling several healthcare
agents, such as doctors, hospitals, testing laboratories, pharmacists, and insurers,
for requesting permission to access and interact with patients’ medical records.
(Dimitrov, 2019) discusses the personal health records (PHR) service trajectory
has an appreciated data source for BC service providers and BCs are good alignment
with General Data Protection Regulation (GDPR). As stated earlier, BC have the
potentiality for enabling decentralized management; for applications where healthcare
stakeholders (e.g., hospitals, patients, and payers) cooperating with one another
without the need of an intermediary central management. They provide immutable
audit trails; that are suitable for recording unvarying databases for insurance claim.
They enable data source and manage patient digital resources. Only the owner has
the rights to change. They provide robustness and data availability; preservation and
continuous EHR availability. Finally, they enhance the data security and privacy;
data is encrypted in BCs and can be decrypted with the patient’s private key. Thou
the network are infiltrated by a malicious party, there is no concrete way to access
the patient data.
The applications of healthcare are redefining data modeling in BC technology.
The adaptability and abilities to segment secure and share medical data and services.
Many developing industries with BC technology are at the center of healthcare. The
blockchain-based healthcare system is organized into four layers that include data
sources, BC technology, healthcare applications, and stakeholders.
Figure 11. Block chain healthcare data management

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In figure 11, initially the data is generated between the patient and their concerned
doctors. The health data comprises of medical history, existing issue/ problem and
other related biological information. This medical information is gathered from nursing
care, medical imaging, and medication history and pathological investigation to be
mentioned in EHR. The patient who has the ownership of EHR, and customized
access control is given the ownership. Parties who would like to access any valuable
information must seek permission which is advanced to the EHR owner, and the
owner will decide to whom access should be granted. The whole healthcare process
includes database, BC, and cloud storage shown in the steps 4, 5 and 6.
(Khezr et al., 2019) used database and cloud storage for storing the records in
a distributed fashion and BC provides privacy for ensuring customized authentic
user access. Healthcare providers such as ad-hoc clinic, community care center,
hospitals are the end user who gets access for a safe and sound care delivery which
will be authorized by the owner.
(Vora et al., 2018) used the framework based on BC for providing efficient
storage and maintenance of EHRs. This provides secure and efficient access of
medical data to patients, providers, and third parties, while preserving the patient
confidential information. The aim of this study was to analyze how the proposed
framework fulfills the patients’ needs between the providers and third parties, and
thereby understand the framework maintenance regarding the privacy and security
concerns in the healthcare 4.0.
In figure 12, a block consists of all the related information of patient is gathered
in database as in figure 13 and the transactions are addition, updating and deletion
that take place in every patient health record are shown in table 1. This information
is further hashed and maintained in the block and again the information is hashed
to get a unique and unobtainable number shown in table 2. Such a hashing value
cannot be easily broken by any intruders.
The patients details are entered as shown in table 1, and table 2 represents the
outcome of the hashing python code. The hashing value will be different for each
record entered. And when hashing is carried out the second time, a new random
number is generated as shown in table 2. The figure 13 is generated, when the first
Figure 12. The structure of block chain

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hash is executed. The hashing value will not be the same, each time the code is
executed. A new random number is generated, hence this random number cannot
be broken that easily by intruders. By using this method, one can save the database
of the patient’s details in very secure manner and confidential.
Each time a patient record gets added or updated. Then, the record is said to
have a transaction when it is finalized. The chaining of blocks is achieved through
a cryptographic way that involves the use of hash functions. A hash function takes
a message of arbitrary length and crunches it into a hash output of a fixed length,
known as a message digest or a digital fingerprint shown in annexure 1 and table 2.
(Knezevic, 2018) stated for any financial transaction, the records will be tracked
by BC and can serve to keep confidential information issued and controlled by
government agencies. The digital ID through BC is much safer in any technology.
The BC- ID permits any person to verify their personal identity, helps in connecting
to their families, and exchange money without the need for intermediary banks. While
a person’s fingerprint is taken with all the related information is linked through BC
with other information about the individual (name, gender, nationality). If in case
of any verification of the person’s identity, the fingerprint unlocks the BC-ID.
Nowadays, in several organizations, Quantum Key Distribution is making a
big wave and making it possible. Any two-level quantum system would be used to
implement Quantum Cryptography (QC), which is also called quantum encryption.
It relates to the quantum mechanics to encrypt messages in a way it is read by
anyone outside of the intended recipient. The Shor’s algorithm is used in QC and the
algorithm is a quantum computer algorithm for integer factorization. If an integer is
given the prime factors are found. The algorithm’s efficiency is due to the efficiency
of the quantum Fourier transform (Nam, 2011 & Fang).
In this approach, a quantum circuit is used for quantum computation which has
a sequence of quantum gates, which does reversible transformations on a quantum
mechanical analog of an n-bit register referred to as an n-qubit register (Beauregard,
2003; Wikipedia, n.d.). Shor’s algorithm has basically two parts namely classical and
Figure 13. Patient details in a database while hashing

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quantum period finding part. The implementation of Shor’s algorithm and quantum
circuit is carried out to show the secret key generated. This quantum period finding’
results are based on the quantum circuit and are shown in figures 14, 15, 16 and 17.
The figure 15 shows the quantum circuit generated and the corresponding
GridQubit is shown in figure 14. The circuit can be generated based on the requirement
of the length, be it 4, 6, 8 or more. Different combinations are generated and result
is produced using a python code shown in figure 15.
Table 1. Patients details
Name: Jyotsna
Age: 40
Weight: 80
Address: Kurnool
Disease: Thyroid Cancer
Enter more data? (y/n): y
Name: Bringanzo
Age: 42
Weight: 87
Address: Hyderabad
Disease: Stomach Ulcer
Enter more data? (y/n): y
Name: Sudheer Kumar
Age: 52
Weight: 67
Address: Secunderabad
Disease: Throat Cancer
Enter more data? (y/n): y
Name: Susheela
Age: 45
Weight: 88
Address: Medak
Disease: Heart Disease
Enter more data? (y/n): y
Name: Sweety
Age: 77
Weight: 80
Address: Bangalore
Disease: Brain Tumor
Enter more data? (y/n): y
Name: Helen
Age: 20
Weight: 70
Address: Karimnagar
Disease: Shoulder Cancer

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Table 2. Patient details with hash values
Name: Jyotsna
Age: 40
Weight: 80
Address: Kurnool
Disease: Thyroid Cancer
dict_keys([‘name’, ‘age’, ‘weight’, ‘address’, ‘disease’])
Keys hash values -8177344308388891750
patient values {FH} → 7017358820209295784
{SH} -> 99829792568213931
Name: Bringanzo
Age: 43
Weight: 87
Address: Hyderabad
Disease: Stomach Ulcer
dict_keys([‘name’, ‘age’, ‘weight’, ‘address’, ‘disease’])
Keys hash values -8177344308388891750
patient values {FH} → -7684213949946050628
{SH}-> -766684922304968775
Name: Sudheer Kumar
Age: 52
Weight: 78
Address: Secunderabad
Disease: Throat Cancer
dict_keys([‘name’, ‘age’, ‘weight’, ‘address’, ‘disease’])
Keys hash values -8177344308388891750
patient values {FH} → -8942438013081472235
{SH} → -2024908985440390382
Name: Sheela Marimam
Age: 45
Weight: 88
Address: Medak
Disease: Heart Disease
dict_keys([‘name’, ‘age’, ‘weight’, ‘address’, ‘disease’])
Keys hash values 8177344308388891750
patient values { FH } → 2487048830996786795
{SH} →2349367120759344459
Name: Sweety
Age: 78
Weight: 80
Address: Bangalore
Disease: Brain Tumor
dict_keys([‘name’, ‘age’, ‘weight’, ‘address’, ‘disease’])
Keys hash values 8177344308388891750
patient values {FH}→ 6140692638140212949
{SH} → 1529006619712825047
Name: Ellen Sushma
Age: 20
Weight: 55
Address: Karimnagar
Disease: Shoulder Cancer
dict_keys([‘name’, ‘age’, ‘weight’, ‘address’, ‘disease’])
Keys hash values 8177344308388891750
patient values {FH}→ 5230373201553129828
{SH} →618687183125741926
All_ dict_keys([]) {HV} 133156838395276
All_values:{HV} 8754152354750935598
*{FH} indicates first hash and {SH} is 2nd hash value, {HV} represents hash value

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Figure 16 is the key length generated on executing python code. The figure 16
shows the randomly generated key of length equal to 40 for different input values
(4, 8) and (8, 10). Figure 17 displays the factors of the Shor’s algorithm when N =
4, the factors are 1.0 and 1.0 and for N = 6, the factors are 3.0 and 1.0. The results
show that quantum technology is advancing with qubits values. Thereby the quantum
cryptography or quantum communication system signifies that they offer virtually
unbreakable encryption.
CONCLUSION
In the world of networks, the cryptography plays a significant part for all the data
transmitted over the wireless network and how it is stored on any electronic device.
In this study the complete implementation of the Advanced Encryption Standard
algorithm and hashing technique are used to carry out for handling the security of
the electronic health database. But the safety measures should be emphasised for
storing and preserving the data for the employees of any industries, as the data can
be stolen through malicious programs. To avoid such cases, the implementation of
Artificial Intelligence techniques are used. Facial recognition and eye detection are
deep learning techniques of AI that helps to verify the authentication of right person
Figure 14. Defining Qubit values of length = 8
Figure 15. Quantum circuit

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Figure 17a. Shor’s algorithm results for N=4 and N=6
Figure 16a. Outputs of circuit with 40 length key for different input values
Figure 16b. Outputs of circuit with 40 length key for different input values

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to access the database, in this case study doctors of the healthcare sector can only
access the data. Hence, the health database is secured with cryptographic cipher, a
concept of quantum cryptography is used from being tampered or stolen.
ACKNOWLEDGMENT
The authors would like to thank all the doctors for sharing their photos for the face
recognition work to be carried out in this study.
1. Dr. Veena Acharya is a senior Gynecologist at Jaipur Hospital and is associated
with NARCHI.
2. Dr. Priya Yenebere is Nephrologist at Chicago.
3. Dr. Sadhana Agrawal is Cancer Immunologist at AIIMS, New Delhi.
4. Dr. Chandana Gandam is Physiotherapist at New Jersey.
Figure 17b. Shor’s algorithm results for N=4 and N=6

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APPENDIX 1
The transactions in blocks are chained to form a block chain as figure 18.
APPENDIX 2
1. Face and IRIS Recognition Partial Source Code
Step 1: Import the Libraries
import numpy as np
import cv2
Step 2: read the face
face_cascade = cv2.CascadeClassifier(‘haarcascade_frontalface_
default.xml’)
eye_cascade = cv2.CascadeClassifier(‘haarcascade_eye.xml’)
img = cv2.imread(‘1303786.jpg’)
for (x,y,w,h) in faces:
img = cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
roi_gray = gray[y:y+h, x:x+w]
roi_color = img[y:y+h, x:x+w]
eyes = eye_cascade.detectMultiScale(roi_gray)
for (ex,ey,ew,eh) in eyes:
cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+
eh),(0,255,0),2)
Figure 18.

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Step 3: Print the Image
cv2.imshow(‘imgc’,img)
Step 4: Close all windows
cv2.waitKey(0)
cv2.destroyAllWindows()
2. Hashing Algorithm
Step 1: Read the required inputs, in this case study- patient name, age, weight,
address and disease and so on.
Step 2: Write / Store the details in a database.
Step 3: Apply hash ()
Step 4: Repeat Step 3 i.e. Hash function is applied twice. And store the details in
database.
3. Advanced Standard Encryption Algorithm
Step 1: Read the patient details
Step 2: Encrypt the details and store them
Step 3: Decrypt the details from the database and print the details
Step 4: The Algorithm is implemented for addition, updating and deletion of the
patient record.