1. Global Academy Of Technology
Rajarajeshwari Nagar,
Bengaluru-560098
Department of Electronics and Communication
Engineering
Technical Seminar on.
Enchancing Security of Helath Information using
Modular Encryption Standard in
Mobile Cloud Computing
Presented by:
Sagar AN
1GA19EC129
Under the guidance of:
Mrs. Ramya KV
3. INTRODUCTION
• Mobile cloud computing is a technology
that allows mobile devices, such as smartphones and
tablets, to access cloud-based services and resources .
• The concept behind mobile cloud computing is to
offload computation and storage tasks from
mobile devices to the cloud, which can handle
these tasks more efficiently and effectively.
• By leveraging the power of the cloud, mobile
users can access a wide range of applications
and services without the need for powerful hardware
or extensive storage space on their devices.
• This technology has numerous benefits, including
improved performance, increased storage capacity,
and reduced battery consumption on mobile devices.
4. LITERATURE SURVEY
Sl No Authors Title of article Analysis
1 Research on mobile
cloud computing:
Review, trend and
perspectives.
The paper provides a comprehensive review of the
literature on mobile cloud computing, covering key
concepts, challenges, and opportunities. It identifies
and discusses the latest trends and developments,
such as edge computing and serverless computing.
The analysis provides valuable insights for
researchers, practitioners in the field.
2 A. Nirabi ,
S. A. Hameed
Mobile cloud
computing for
emergency
healthcare model.
The paper proposes a mobile cloud computing-based
healthcare model for emergency situations. It
provides a detailed description of the proposed
model, including its architecture and functionalities.
The authors argue that this model can improve the
speed and efficiency of emergency healthcare,
offering a promising approach to public health and
safety.
H. Qi , A. Gani
5. LITERATURE SURVEY
Sl No Authors Title of article Analysis
3 L. A. Tawalbeh,
Mehmood,
E. Benkhlifa,
and H. Song.
Mobile cloud
computing model and
big data analysis for
healthcare applications.
The paper proposes a mobile cloud computing-based
model for healthcare applications that utilizes big data
analysis. The model provides real-time analysis of
patient data and clinical information, offering a
promising approach to improving healthcare services.
The paper's focus on integrating mobile cloud
computing and big data analysis in healthcare provides
new opportunities for healthcare professionals to make
informed decisions and improve patient outcomes.
4 H. Jin, Y. Luo, P.
Li, and J. Mathew
A review of secure and
privacypreserving
medical data sharing
The paper proposes a mobile cloud computing-based
healthcare model for emergency situations. It provides
a detailed description of the proposed model, including
its architecture and functionalities. The authors argue
that this model can improve the speed and efficiency of
emergency healthcare, offering a promising approach to
public health and safety.
6. OBJECTIVES
• The proposed work provides secure HI storage
against ensuring the confidentiality of the cloud
service provider.
• It ensures the confidentiality of HI against any
hacker or third party/malicious outsider.
• Full control of the patient to their HI.
• Layered modeling with modularity support
against the intruder’s attacks to HI.
• Unwanted attempt to access the HI would be
restricted.
7. METHODOLOGY
MES includes three significant measures. These measures are‘‘
Identification (IDN)’’, ‘‘Classification (CLF)’’, and ‘‘Securing (SC)’’. IDN
and CLF are performed at the MCC userside. While the SC step is
performed at the Crypto-cloud.Crypto-cloud is the intermediary cloud that
is dedicated toperforming cryptography measures.
CLASSIFICATION
IDENTIFICATION SECURING
MODULAR
INTRACTION
8. HI storage at cloud using MES. HI storage sharing using MES.
MODULAR ENCRYPTION STANDARD
9. 4
MODULARITY CHECK
• The module-based
processor utilization
of MES is processed.
• The more CPU used
in the enciphering
technique; the
higher the processor
load would be.
MEMORY UTILIZATION
• For performance
analysis, one of the
most critical
parametersis memory
utilization.
• The below graph
shows memory
utilization of AES,
Blowfish, RC5.
KEY VARIANCES
BASED ANALYSIS
• This is a qualitative
comparative approach.
KEY DATA COLLIGATION-
RATE FOR SINGLE ROUND
• The processor usage is
the analysis of the time
that a CPU takes to a
particular computation.
RESULTS
1
3
2
12. CONCLUSION
Despite the prospective solutions offered by MCC in Health record monitoring,
numerous impediments restrain the key potentials of MCC. Among these obstacles,
security and privacy are the key hindrances in the utilization of MCC in healthcare.
This is one of the considerable research gaps. Accordingly, this research utilizes a
layered, modular, data nature-centric cryptography approach, for example, MES,
that utilizes secure HI sharing, and storage mechanisms. The Comparative results
show that this scheme outperforms other commonly used techniques in the MCC .
Currently, this approach is intended for the enciphering and deciphering of textual
data and there is no consideration of the image-oriented data-set yet. However, in
future work, this issue would be considered. Secondly, layered modeling may
sometimes result in lowering system efficiency. Accordingly, the efficiency of the
proposed work can be further improved by the integration of quantum computing to
make it more adaptable for mobile and smart devices. In the future, we may ensure
patient privacy using the block-chain.
13. FUTURE SCOPE
The proposed approach of using a layered, modular, data nature-centric cryptography
approach for secure health record monitoring through mobile cloud computing (MCC)
has promising future scope.In the short term, the proposed approach can be extended to
include the encryption and decryption of image-oriented data and can be tested in a
real-world setting. Additionally, the integration of quantum computing can be explored
to further enhance the efficiency of the system and its adaptability to mobile and smart
devices.In the long term, the proposed approach can be expanded to include other
types of healthcare data such as video and audio recordings. Additionally, the use of
block-chain technology can be explored for secure data sharing and storage, which can
further enhance patient privacy and data security.
14. REFRENCES
1. H. Qi and A. Gani, ‘‘Research on mobile cloud computing: Review, trend and perspectives,’’ in Proc. 2nd Int.
Conf. Digit. Inf. Commun. Technol. Appl. (DICTAP), May 2012, pp. 195–202.
2. A. Nirabi and S. A. Hameed, ‘‘Mobile cloud computing for emergency healthcare model: Framework,’’
in Proc. Int. Conf. Comput. Commun. Eng., 2018, pp. 375–379.
3. L. A. Tawalbeh, R. Mehmood, E. Benkhlifa, and H. Song, ‘‘Mobile cloud computing model and big data
analysis for healthcare applications,’’ IEEE Access, vol. 4, pp. 6171–6180, 2016.
4. H. Jin, Y. Luo, P. Li, and J. Mathew, ‘‘A review of secure and privacypreserving medical data sharing,’’ IEEE
Access, vol. 7, pp. 61656–61669, 2019.
5. D. Liu, Z. Yan, W. Ding, and M. Atiquzzaman, ‘‘A survey on secure data analytics in edge computing,’’ IEEE
Internet Things J., vol. 6, no. 3, pp. 4946–4967, Jun. 2019.
