Anomaly Detection Modeling In Medical Pervasive Systems
Application Based Anomaly Detection
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In this work, we have dealt with Intrusion Detection,ID, to secure a medical application deployed onpervasive devices. ID Systems, IDSs, are used tomonitor a resource and notify someone in the event ofa specific occurrence for an appropriate response.Based on attack identification, they can be thosewhich implement misuse detection, matching againstknown attack patterns, and those which implementanomaly detection, deviation from normal patterns.Misuse detection is used for matching only knownpatterns of attacks while anomaly detection iscapable of identifying new attacks by matching withan alre...
In this work, we have dealt with Intrusion Detection,
ID, to secure a medical application deployed on
pervasive devices. ID Systems, IDSs, are used to
monitor a resource and notify someone in the event of
a specific occurrence for an appropriate response.
Based on attack identification, they can be those
which implement misuse detection, matching against
known attack patterns, and those which implement
anomaly detection, deviation from normal patterns.
Misuse detection is used for matching only known
patterns of attacks while anomaly detection is
capable of identifying new attacks by matching with
an already established normal profile. Based on
source of information for the IDS, it may be
host-based, network-based or application-based. For
our case, we deal with application based anomaly
detection modeling issues through building normal
users application usage profiles.
ID, to secure a medical application deployed on
pervasive devices. ID Systems, IDSs, are used to
monitor a resource and notify someone in the event of
a specific occurrence for an appropriate response.
Based on attack identification, they can be those
which implement misuse detection, matching against
known attack patterns, and those which implement
anomaly detection, deviation from normal patterns.
Misuse detection is used for matching only known
patterns of attacks while anomaly detection is
capable of identifying new attacks by matching with
an already established normal profile. Based on
source of information for the IDS, it may be
host-based, network-based or application-based. For
our case, we deal with application based anomaly
detection modeling issues through building normal
users application usage profiles.
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