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Privacy Protection and Interruption Avoidance for Cloud-Based Medical Data Sharing


Affiliations
1 Department of Computer Applications, S.A. Engineering College, India
     

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In this paper and analyse a behaviour-rule specification-based technique for intrusion detection of medical devices embedded in a Medical Cyber Physical System (MCPS) in which the patient's safety is of the utmost importance. A methodology to transform behaviour rules to a state machine, so that a device that is being monitored for its behaviour can easily be checked against the transformed state machine for deviation from its behaviour specification.

Using vital sign monitor medical devices as an example; In demonstrate that our intrusion detection technique can effectively trade false positives off for a high detection probability to cope with more sophisticated and hidden attackers to support ultra-safe and secure MCPS applications. Moreover, through a comparative analysis, A demonstrate that our behaviour-rule specification-based IDS technique outperforms two existing anomaly-based techniques for detecting abnormal patient behaviours in pervasive healthcare applications.


Keywords

Privacy Protection, Data Sharing, NTRU, Collaborative IDS.
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  • Privacy Protection and Interruption Avoidance for Cloud-Based Medical Data Sharing

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Authors

K. Nandhini
Department of Computer Applications, S.A. Engineering College, India
S. Jayanthi
Department of Computer Applications, S.A. Engineering College, India

Abstract


In this paper and analyse a behaviour-rule specification-based technique for intrusion detection of medical devices embedded in a Medical Cyber Physical System (MCPS) in which the patient's safety is of the utmost importance. A methodology to transform behaviour rules to a state machine, so that a device that is being monitored for its behaviour can easily be checked against the transformed state machine for deviation from its behaviour specification.

Using vital sign monitor medical devices as an example; In demonstrate that our intrusion detection technique can effectively trade false positives off for a high detection probability to cope with more sophisticated and hidden attackers to support ultra-safe and secure MCPS applications. Moreover, through a comparative analysis, A demonstrate that our behaviour-rule specification-based IDS technique outperforms two existing anomaly-based techniques for detecting abnormal patient behaviours in pervasive healthcare applications.


Keywords


Privacy Protection, Data Sharing, NTRU, Collaborative IDS.

References