Batch 21 - Final project review -PPT.pdf

Project

1. KSR COLLEGE OF ENGINEERING
(Autonomous)Tiruchengode-637 215
DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING
20CS821–PROJECT WORK
IMAGE ENCRYPTION AND DECRYPTION NETWORK OF MEDICAL THINGS BY USING
CRYPTOGRAPHY
PRESENTEDBY: GUIDEDBY:
DHANASRIA (2013017) K.S.MANOJEEM.E.,(Ph.D.).,
MOHAMED KALIFAS(2013063) (ASSISTANTPROFESSOR)
INDRISHS (2013505)
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2. CONTENT
•DOMAIN INTRODUCTION
•ABSTRACT
•LITERATURE SURVEY
•OBJECTIVE
•EXISTING SYSTEM
•DRAWBACKS
•PROPOSED SYSTEM
•ADVANTAGES
•ARCHITECTURE DIAGRAM & BLOCK DIAGRAM
•MODULES
•SAMPLE IMAGE
•CONCLUSION
•FUTURE ENHANCEMENT
•REFERENCES
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3. DOMAIN INTRODUCTION
➢Cryptography is a vital tool in ensuring the confidentiality, integrity, and authenticity of digital information.
➢It employs mathematical algorithms to convert plaintext into ciphertext, making data unreadable to
unauthorized parties.
➢Through encryption and decryption, cryptography enables secure communication and data storage, guarding
against unauthorized access and manipulation.
➢Cryptography includes techniques like encryption, decryption, digital signatures, and hashing to protect
sensitive information and verify its authenticity in the digital realm.
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4. ABSTARCT
➢The identification of the medical images is common to encrypt and decrypt the binary message . To
implement the RSA model for secure encryption process and the stegno image model is used.
➢The most popular and most widely used cryptosystem is the RSA whose security depends on the difficulty of
discovering the private key in a reasonable time but not on the details of the algorithm To ensure a maximum
security, RSA requires the highest form of representation in the image encryption field.
➢The proposed method induces the sample medical image which A new hybrid security algorithm is presented
for RSA cryptosystem. The system works on the concept of using different keys- a private and a public for
encryption processes.
➢Thus, it provides more secure path for encryption process. The value of n public key with the value of n
private keys is generated with the phi and the process of the encryption process is done..
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5. LITERATURE SURVEY
S.NO TOPIC AUTHOR JOURNAL
& YEAR
TECHNIQUE/
ALGORITHM
USED
LIMITATION
1.Hybrid Image
Steganography
Technique Using
EMSD and LSB
Substitution
Algorithms
Serdar Solak et al(IEEE)
2023
The proposed
technique combines
the Enhanced
Modified Signed
Digit (EMSD)
algorithm with
Least Significant
Bit (LSB)
substitution.
•Security
compromised by
detection.
• Advanced
Detection
Techniques
2.Anticipatory Quality
Assessment Metric
for Evaluating Data
Hiding
Imperceptibility
Raniyah Wazira Li(IEEE) 2023In paper introduces
the Anticipatory
Quality Assessment
Metric (AQAM)
algorithm, which
predicts subjective
image quality
objectively.
•Subjective
Perception
Variation
•Limited
applicabilityin
diversescenarios.
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6. S.NO TOPIC AUTHOR JOURNAL &
YEAR
TECHNIQUE/
ALGORITHM
USED
LIMITATION
3.Reversible Data
Hiding
Optimization
Wenguang He
et al
(IRJET)
2022
Multiple Pairwise
Prediction-Error
Expansion (PEE) and
Two-Layer Embedding
•Computational
Complexity Challenges
•Improving Marked
Image Quality
4Exploring
innovative
approaches to
reversible data
hiding,
particularly
focusing on
block-wise
histogram
shifting.
Kandala Sree
Rama Murthy
et al
(IEEE)
2022
Block-Wise Histogram
Shifting and Run-
Length Encoding
• Potential Challenges in
Segment-Based
Histogram Shifting
•Potential complexity in
segment-based
histogram shifting
LITERATURE SURVEY (cont.)
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7. S.NO TOPIC AUTHOR JOURNAL &
YEAR
TECHNIQUE/
ALGORITHM
USED
LIMITATION
5Safeguarding the
authenticity and
integrity of
medical images
is paramount in
telemedicine
applications
Xiyao Liu et
al
(IEEE) 2022Recursive Dither
Modulation (RDM)
combined with Slantlet
Transform (SLT) and
Singular Value
Decomposition (SVD)
•Risk of Misdiagnosis
due to Image
Distortions
•Challenges in ensuring
distortion-free images
for accurate diagnosis.
6 Enhanced Data
Hiding Using
Deep Neural
Networks (DNN)
Lianshan Liu
et al
(IJCRT)
2020
Recursive Dither
Modulation (RDM)
combined with Slantlet
Transform (SLT) and
Singular Value
Decomposition (SVD)
•Risk of Misdiagnosis
Due to Image
Distortions
•The Critical Importance
of Distortion-Free
Images for Accurate
Medical Diagnosis
LITERATURE SURVEY (cont.)
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8. OBJECTIVES
➢Develop a reversible data hiding system for medical images by embedding encrypted messages
using RSA.
➢ Enhance security and confidentiality of medical image transmission through robust steganographic
techniques.
➢ Ensure recipient-exclusive access to embedded information by employing RSA decryption with a
private key.
➢Facilitate secure communication of medical data by integrating encryption and steganography into a
cohesive framework.
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9. EXISTING SYSTEM
➢ Reversible data hiding (RDH) is a recently emerged research domain in the field of information security
domain with broad applications in medical images and meta-data handling in the cloud. The amount of data
required to handle the healthcare sector has exponentially increased due to the increase in the population.
➢Medical images and various reports such as discharge summaries and diagnosis reports are the most
common data in the healthcare sector. The RDH schemes are widely explored to embed the medical reports
in the medical image instead of sending them as separate files.
➢The receiver can extract the clinical reports and recover the original medical image for further diagnosis.
This manuscript proposes an approach that uses a new lossless compression-based RDH scheme that creates
vacant room for data hiding.
➢The conventional Elias gamma encoding process is modified in the proposed method to embed some
additional data bits during the encoding process itselfThe experimental study is conducted on both natural
images and medical images
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10. DRAWBACKS
➢The embedding capacity is limited. The amount of secret data that can be embedded in an image is
limited by the amount of vacant room that is available. This can be a problem for medical images, which
are often high-resolution and contain a lot of detail.
➢The image quality may be degraded. The embedding process can slightly degrade the image quality,
especially if the embedding capacity is high. This is because the secret data is embedded by slightly
changing the pixel values of the image.
➢The algorithm is complex. The RDH algorithms are often complex and computationally expensive.
This can make them difficult to implement and use.
➢The security of the data may be compromised. If the RDH algorithm is not designed carefully, it may
be possible for an attacker to extract the secret data without knowing the embedding key.
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11. PROPOSED SYSTEM
➢The proposed system integrates RSA encryption and steganography techniques to enhance the
security of medical image transmission and storage.
➢Utilizing the robust RSA cryptosystem, the system generates public and private keys for
encryption, ensuring maximum security. Steganography is employed to embed the encrypted data
within medical images, maintaining confidentiality while avoiding detection.
➢ Through the modular implementation of RSA encryption, steganography, decoding, and decryption
modules, the system enables secure transmission and retrieval of sensitive medical information,
safeguarding patient privacy and ensuring data integrity in healthcare settings
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12. ADVANTAGES
➢Ensures secure transmission of medical images with hidden information, safeguarding patient privacy.
➢Allows extraction of the original data from the stegoimage, maintaining data integrity.
➢Integrates RSA encryption for strong cryptographic protection alongside steganography.
➢Enables only authorized recipients with the private key to decrypt and extract hidden data.
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13. ARCHITECTURE DIAGRAM
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14. BLOCK DIAGRAM
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INPUT IMAGE
GREY LEVEL
CONVERSION
ENHANCED
IMAGE
STEGO IMAGE
ENCRYPTED
IMAGE
DECRYPT
ION

15. LIST OF MODULES
➢RSA ENCRYPTION
➢STEGNO IMAGE
➢DECODING
➢DECRYPTION
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16. MODULE DESCRIPTION
i) RSA ENCRYPTION:
This module focuses on implementing the RSA encryption algorithm. RSA encryption involves
generating a public and private key pair, where the public key is used for encryption and the private key is
used for decryption. The module likely includes functions for generating these keys, as well as methods for
encrypting data using the public key.
ii) STEGNO IMAGE:
This module involves the implementation of steganography techniques to embed encrypted data
within medical images. Steganography is the practice of concealing data within other non-secret data to
ensure its confidentiality. In this case, the module would include functions or algorithms for embedding
encrypted messages within the pixels of medical images without significantly altering the image's
appearance.
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17. MODULE DESCRIPTION (cont.)
iii) DECODING:
The decoding module is responsible for extracting the encrypted data from the
steganographically modified medical images. It likely involves ananlysing the image pixels to identify and
extract the embedded data, which can then be passed on for decryption.
iv) DECRYPTION:
This module handles the decryption of the extracted data using the RSA decryption process. It
involves using the private key corresponding to the public key used for encryption to reverse the
encryption process and obtain the original plaintext data. The module would include functions for
decrypting the data using the private key and possibly handling any necessary postprocessing steps to
obtain the final decrypted message.
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18. SAMPLE IMAGE
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19. SAMPLE IMAGE
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20. SAMPLE IMAGE
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21. SAMPLE IMAGE
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22. CONCLUSION
➢In conclusion, the proposed system presents a comprehensive approach to enhancing the security of medical
image transmission and storage through the integration of RSA encryption and steganography techniques.
➢By leveraging the robust RSA cryptosystem and embedding encrypted data within medical images, the system
ensures confidentiality and integrity while facilitating secure communication in healthcare settings.
➢The modular design, rigorous testing, and meticulous implementation contribute to the reliability and
effectiveness of the system in safeguarding sensitive patient information.
➢Moving forward, continued research and development in this area are essential to address emerging threats
and ensure ongoing protection of medical data in an increasingly digital healthcare landscape.
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23. FUTURE ENHANCEMENT
➢In future work, the proposed system for securing medical images using RSA encryption and LSB
steganography is a promising approach, but there are still some areas where future work can be done.
➢It is to improve the security of the system. This could be done by using a more sophisticated
encryption algorithm, such as AES encryption. Additionally, the system could be modified to use
multiple cover images to embed the encrypted medical images.
➢This would make it more difficult for unauthorized individuals to extract the medical images from the
stego image.
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24. REFERENCES
•[1] Rupa, C.; Harshita, M.; Srivastava, G.; Gadekallu, T.R.; Maddikunta, P.K.R. Securing Multimedia
using a Deep Learning based Chaotic Logistic Map. IEEE J. Biomed. Health Inform. 2022. [CrossRef]
•[2] Abd el Samie, F.E.; Ahmed, H.E.H.; Elashry, I.F.; Shahieen, M.H.; Faragallah, O.S.; El-Rabaie,
E.S.M.; Alshebeili, S.A. Image Encryption: A Communication Perspective; CRC Press: Boca Raton, FL,
USA, 2020.
•[3] Srivastava, G.; Jhaveri, R.H.; Bhattacharya, S.; Pandya, S.; Maddikunta, P.K.R.; Yenduri, G.; Hall,
J.G.; Alazab, M.; Gadekallu, T.R. XAI for Cybersecurity: State of the Art, Challenges, Open Issues and
Future Directions. arXiv 2022, arXiv:2206.03585.
•[4] Manikandan, V.; Masilamani, V. An efficient visually meaningful image encryption using Arnold
transform. In Proceedings of the IEEE Students’ Technology Symposium (TechSym), Kharagpur, India,
30 September–2 October 2020 pp. 266–271.
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25. THANK YOU
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