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Abstract
• Healthcare applications are considered as promising fields for wireless sensor
networks, where patients can be monitored using wireless medical sensor
networks (WMSNs).
• Current WMSN healthcare research trends focus on patient reliable
communication, patient mobility, and energy-efficient routing, as a few
examples.
• However, deploying new technologies in healthcare applications without
considering security makes patient privacy vulnerable.
• Moreover, the physiological data of an individual are highly sensitive.
• The main contribution of this paper is to distribute patient’s data securely in
multiple data servers and performing the Paillier cryptosystems to perform
statistical analysis on the patient data without compromising the patient’s
privacy.
Introduction
• Wireless medical sensor networks (MSNs)
• Patients’ health-related parameters can be
monitored remotely, continuously, and in real
time, and then processed and transferred to
medical databases.
• used for clinical diagnosis and emergency
medical response,
• Healthcare applications e.g CodeBlue . Alarm-
Net , UbiMon , MEDiSN , and MobiCare .
• Fig. shows the architecture of a typical Alarm-
Net healthcare application.
• Security threats to healthcare application
Literature Survey
Sr.
No
.
Paper
Name
Authors
1. Sharemind: a
framework for
fast privacy-
preserving
Computations
Dan Bogdanov, Sven
Laur, and Jan
Willemson
In this paper,we present a provably secure and efficient
general-purpose computation systemto address this
problem. Our solution—SHAREMIND—is a virtual
machinefor privacy-preserving data processing that relies
on share computing techniques.
2. Real-Time and
Secure Wireless
Health
Monitoring
S. Dagtas, G.
Pekhteryev, Z.
S¸ahinoglu, H. Cam,
and N. Challa
The main advantages of the proposed framework are
(1) the ability to detect signals wirelessly within a body
sensor network (BSN),
(2) low-power and reliable data transmission through
ZigBee network nodes,
(3) secure transmission of medical data over BSN,
(4) efficient channel allocation for medical data
transmission over wireless networks, and
(5) optimized analysis of data using an adaptive
architecture that maximizes the utility of processing and
Existing System
• The security is a paramount requirement of healthcare
applications, especially in the case of patient privacy, if
the patient has an embarrassing disease.
• We highlight some popular healthcare projects using
wireless medical sensor networks, and discuss their
security the existing systems solutions can simply protect
the patient data during transmission.
• But cannot protect the inside attack where the
administrator of the patient database reveals the
sensitive patient data.
Disadvantages
• Less secure.
• Cannot protect inside attacker.
• If any hacker get data from one DB server then whole
data will be get to hacker.
Problem Statement
Proposed system focus on the user accessibility and the Retrieval
Compromised server data.
1. User accessibility:
When any one of the server is compromised, Remaining two servers
are locked respective patient data and simultaneously key
notification will be sent to the respected user(patient). After that,
using this Key User can retrieve the compromised data.
2. Retrieval of compromised data:
When any server out of three is compromise through intruder then
the remaining server(s) would act as a proxy server (s).
Proposed System
• The existing solutions can protect the patient data during transmission, but cannot
stop the inside attack . E.g. administrator of the patient database may reveal the
sensitive patient data.
The proposed system include:
• practical approach to prevent the inside attack by securely distributing the patient
data in multiple data servers.
• employing the Paillier cryptosystems to perform statistic analysis on the patient
data without compromising the patients’ privacy.
• Retrieve patient data in case any server(s) get compromised.
Advantages
• In Proposed system Due to secured distributed
database architecture we can achieve data storage &
data analysis security.
• Proposed data retrieval technique allow to retrieve
the data compromised server(s)
Motivation
• In a wireless medical sensor network, the sensitive patient data is
transmitted through the open air.
• It is more vulnerable to eavesdropping, spoofing, altering and
replaying attacks, compared with the wired network.
• Some work has been done to secure the wireless medical sensor
network using efficient symmetric key cryptosystems.
• The efforts can protect the patient data during transmission, but
cannot stop the inside attack where the administrator of the patient
database reveals the sensitive patient data.
• To prevent from the inside attack, more advanced cryptographic
techniques, such as attribute based encryption.
Goals and Objectives
• Protect the patient data during transmission.
• Stop the inside attack where the administrator of the
patient database reveals the sensitive patient data of
patients.
System Architecture
System Specification
Hardware Requirements
• System : Pentium IV 2.4 GHz.
• Hard Disk : 40 GB.
• Ram : 256 Mb.
Software Requirements:
• Operating system :Windows XP Professional/7LINUX.
• Front End : JSP, CSS.
• Back End : MySQL.
• IDE : Eclipse.
Algorithm
• 1. AES
• 2. Sharemind - Paillier cryptography
• 3. MD5
Conclusion
• Here we identified the security challenges facing an MSN
for wireless health monitoring and then proposed
practical oriented solution for information retrieval in
case of server(s) compromising using Re-Encryption
Technique.
References
[1] Yi, Xun, et al. ”Privacy Protection for Wireless Medical Sensor Data.” IEEE Transactions
on Dependable and Secure Computing 13.3 (2016): 369-380.
[2] X. Yi, J. Willemson, F. Nat-Abdesselam. Privacy-Preserving Wireless Medical Sensor Network.
In Proc. TrustCom13, pages 118-125, 2013.
[3] D. He, S. Chan and S. Tang. A Novel and Lightweight System to Secure Wireless Medical
Sensor Networks. IEEE Journal of Biomedical and Health Informatics, 18 (1): 316-326, 2014.
[4] Y. M. Huang, M. Y. Hsieh, H. C. Hung, J. H. Park. Pervasive, Secure Access to a Hierarchical
Sensor-Based Healthcare Monitoring Architecture in Wireless Heterogeneous Networks.
IEEE J. Select. Areas Commun. 27: 400-411, 2009.
[5] K. Malasri, L. Wang. Design and Implementation of Secure Wireless Mote-Based Medical
Sensor Network. Sensors 9: 6273-6297, 2009.
[6] P. Belsis and G. Pantziou. A k-anonymity privacy-preserving approach in wireless medical
monitoring environments. Journal Personal and Ubiquitous Computing, 18(1): 61-74, 2014.
[7] T. ElGamal. A Public-Key Cryptosystem and a Signature Scheme Based on Discrete Logarithms.
IEEE Transactions on Information Theory, 31 (4): 469-472, 1985.
[8] P. Paillier. Public-key Cryptosystems Based on Composite Degree Residuosity Classes. In
Proc. EUROCRYPT99, pages 223-238, 1999.

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Private & Secure.pptx

  • 2. Abstract • Healthcare applications are considered as promising fields for wireless sensor networks, where patients can be monitored using wireless medical sensor networks (WMSNs). • Current WMSN healthcare research trends focus on patient reliable communication, patient mobility, and energy-efficient routing, as a few examples. • However, deploying new technologies in healthcare applications without considering security makes patient privacy vulnerable. • Moreover, the physiological data of an individual are highly sensitive. • The main contribution of this paper is to distribute patient’s data securely in multiple data servers and performing the Paillier cryptosystems to perform statistical analysis on the patient data without compromising the patient’s privacy.
  • 3. Introduction • Wireless medical sensor networks (MSNs) • Patients’ health-related parameters can be monitored remotely, continuously, and in real time, and then processed and transferred to medical databases. • used for clinical diagnosis and emergency medical response, • Healthcare applications e.g CodeBlue . Alarm- Net , UbiMon , MEDiSN , and MobiCare . • Fig. shows the architecture of a typical Alarm- Net healthcare application. • Security threats to healthcare application
  • 4. Literature Survey Sr. No . Paper Name Authors 1. Sharemind: a framework for fast privacy- preserving Computations Dan Bogdanov, Sven Laur, and Jan Willemson In this paper,we present a provably secure and efficient general-purpose computation systemto address this problem. Our solution—SHAREMIND—is a virtual machinefor privacy-preserving data processing that relies on share computing techniques. 2. Real-Time and Secure Wireless Health Monitoring S. Dagtas, G. Pekhteryev, Z. S¸ahinoglu, H. Cam, and N. Challa The main advantages of the proposed framework are (1) the ability to detect signals wirelessly within a body sensor network (BSN), (2) low-power and reliable data transmission through ZigBee network nodes, (3) secure transmission of medical data over BSN, (4) efficient channel allocation for medical data transmission over wireless networks, and (5) optimized analysis of data using an adaptive architecture that maximizes the utility of processing and
  • 5. Existing System • The security is a paramount requirement of healthcare applications, especially in the case of patient privacy, if the patient has an embarrassing disease. • We highlight some popular healthcare projects using wireless medical sensor networks, and discuss their security the existing systems solutions can simply protect the patient data during transmission. • But cannot protect the inside attack where the administrator of the patient database reveals the sensitive patient data.
  • 6. Disadvantages • Less secure. • Cannot protect inside attacker. • If any hacker get data from one DB server then whole data will be get to hacker.
  • 7. Problem Statement Proposed system focus on the user accessibility and the Retrieval Compromised server data. 1. User accessibility: When any one of the server is compromised, Remaining two servers are locked respective patient data and simultaneously key notification will be sent to the respected user(patient). After that, using this Key User can retrieve the compromised data. 2. Retrieval of compromised data: When any server out of three is compromise through intruder then the remaining server(s) would act as a proxy server (s).
  • 8. Proposed System • The existing solutions can protect the patient data during transmission, but cannot stop the inside attack . E.g. administrator of the patient database may reveal the sensitive patient data. The proposed system include: • practical approach to prevent the inside attack by securely distributing the patient data in multiple data servers. • employing the Paillier cryptosystems to perform statistic analysis on the patient data without compromising the patients’ privacy. • Retrieve patient data in case any server(s) get compromised.
  • 9. Advantages • In Proposed system Due to secured distributed database architecture we can achieve data storage & data analysis security. • Proposed data retrieval technique allow to retrieve the data compromised server(s)
  • 10. Motivation • In a wireless medical sensor network, the sensitive patient data is transmitted through the open air. • It is more vulnerable to eavesdropping, spoofing, altering and replaying attacks, compared with the wired network. • Some work has been done to secure the wireless medical sensor network using efficient symmetric key cryptosystems. • The efforts can protect the patient data during transmission, but cannot stop the inside attack where the administrator of the patient database reveals the sensitive patient data. • To prevent from the inside attack, more advanced cryptographic techniques, such as attribute based encryption.
  • 11. Goals and Objectives • Protect the patient data during transmission. • Stop the inside attack where the administrator of the patient database reveals the sensitive patient data of patients.
  • 13. System Specification Hardware Requirements • System : Pentium IV 2.4 GHz. • Hard Disk : 40 GB. • Ram : 256 Mb. Software Requirements: • Operating system :Windows XP Professional/7LINUX. • Front End : JSP, CSS. • Back End : MySQL. • IDE : Eclipse.
  • 14. Algorithm • 1. AES • 2. Sharemind - Paillier cryptography • 3. MD5
  • 15. Conclusion • Here we identified the security challenges facing an MSN for wireless health monitoring and then proposed practical oriented solution for information retrieval in case of server(s) compromising using Re-Encryption Technique.
  • 16. References [1] Yi, Xun, et al. ”Privacy Protection for Wireless Medical Sensor Data.” IEEE Transactions on Dependable and Secure Computing 13.3 (2016): 369-380. [2] X. Yi, J. Willemson, F. Nat-Abdesselam. Privacy-Preserving Wireless Medical Sensor Network. In Proc. TrustCom13, pages 118-125, 2013. [3] D. He, S. Chan and S. Tang. A Novel and Lightweight System to Secure Wireless Medical Sensor Networks. IEEE Journal of Biomedical and Health Informatics, 18 (1): 316-326, 2014. [4] Y. M. Huang, M. Y. Hsieh, H. C. Hung, J. H. Park. Pervasive, Secure Access to a Hierarchical Sensor-Based Healthcare Monitoring Architecture in Wireless Heterogeneous Networks. IEEE J. Select. Areas Commun. 27: 400-411, 2009. [5] K. Malasri, L. Wang. Design and Implementation of Secure Wireless Mote-Based Medical Sensor Network. Sensors 9: 6273-6297, 2009. [6] P. Belsis and G. Pantziou. A k-anonymity privacy-preserving approach in wireless medical monitoring environments. Journal Personal and Ubiquitous Computing, 18(1): 61-74, 2014. [7] T. ElGamal. A Public-Key Cryptosystem and a Signature Scheme Based on Discrete Logarithms. IEEE Transactions on Information Theory, 31 (4): 469-472, 1985. [8] P. Paillier. Public-key Cryptosystems Based on Composite Degree Residuosity Classes. In Proc. EUROCRYPT99, pages 223-238, 1999.