Bekele, Dawit (PhD)Asfaw, Biniyam2018-06-182023-11-292018-06-182023-11-292007-07http://etd.aau.edu.et/handle/123456789/1162Pervasive computing is being applied to different areas of specialization. This is basically because of the features of pervasive computing like context-awareness, invisibility, nonintrusiveness, and mobility. The medical area is one where such devices are hugely deployed. In this case, the pervasive devices; PDA (Personal Digital Assistant), mobile phones and the like, are used for manipulating medical records on the move. The use of pervasive devices also comes with new challenges that did not exist with traditional computing systems. Among these challenges, security is probably the major one. In fact, insuring security with pervasive systems is difficult due to the use of wireless communication, the physical nature and the low processing and low power nature of the devices. In this research, we deal with intrusion detection, ID, to secure such systems. 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 profilesenPervasive; Computing Like Context-AwarenessThesis