@article{(Open Science Index):https://publications.waset.org/pdf/13186,
	  title     = {Genetic-based Anomaly Detection in Logs of Process Aware Systems},
	  author    = {Hanieh Jalali and  Ahmad Baraani},
	  country	= {},
	  institution	= {},
	  abstract     = {Nowaday-s, many organizations use systems that
support business process as a whole or partially. However, in some
application domains, like software development and health care
processes, a normative Process Aware System (PAS) is not suitable,
because a flexible support is needed to respond rapidly to new
process models. On the other hand, a flexible Process Aware System
may be vulnerable to undesirable and fraudulent executions, which
imposes a tradeoff between flexibility and security. In order to make
this tradeoff available, a genetic-based anomaly detection model for
logs of Process Aware Systems is presented in this paper. The
detection of an anomalous trace is based on discovering an
appropriate process model by using genetic process mining and
detecting traces that do not fit the appropriate model as anomalous
trace; therefore, when used in PAS, this model is an automated
solution that can support coexistence of flexibility and security.},
	    journal   = {International Journal of Computer and Systems Engineering},
	  volume    = {4},
	  number    = {4},
	  year      = {2010},
	  pages     = {692 - 697},
	  ee        = {https://publications.waset.org/pdf/13186},
	  url   	= {https://publications.waset.org/vol/40},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 40, 2010},
	}