@conference {18582,
	title = {Predictive Analytics: A Shortcut to Dependable Computing},
	booktitle = {Software Engineering for Resilient Systems},
	year = {2017},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {The paper lists three major issues: complexity, time and uncertainty, and identifies dependability as the permanent challenge. In order to enhance dependability, the paradigm shift is proposed where focus is on failure prediction and early malware detection. Failure prediction methodology, including modeling and failure mitigation, is presented and two case studies (failure prediction for computer servers and early malware detection) are described in detail. The proposed approach, using predictive analytics, may increase system availability by an order of magnitude or so.},
	isbn = {978-3-319-65948-0},
	author = {Malek, Miroslaw},
	editor = {Romanovsky, Alexander and Troubitsyna, Elena A.}
}
@conference {18379,
	title = {Proactive Failure Management in Smart Grids for Improved Resilience (A Methodology for Failure Prediction and Mitigation)},
	booktitle = {IEEE GLOBECOM SmartGrid Resilience (SGR) Workshop},
	year = {2015},
	month = {12/2015},
	address = {San Diego, CA, USA},
	abstract = {A gradual move in the electric power industry towards Smart Grids brings several challenges to the system operation such as preserving its resilience and ensuring security. As the system complexity grows and a number of failures increases, the need for grid management paradigm shift from reactive to proactive is apparent and can be realized by employing advanced monitoring instruments, data analytics and prediction methods. In order to improve resilience of the Smart Grid and to contribute to efficient system operation, we present a blueprint of a comprehensive methodology for proactive failure management that may also be applied to manage other types of disturbances and undesirable changes. The methodology is composed of three main steps: (i) continuous monitoring of the most indicative features, (ii) prediction of failures and (iii) their mitigation. The approach is complementary to the existing ones that are mainly based on fast detection and localization of grid disturbances, and reactive corrective actions.},
	keywords = {Failure Prediction, Proactive Management, Resilience, security, smart grid, Synchrophasor},
	author = {Kaitovi{\'c}, Igor and Lukovi{\'c}, Slobodan and Malek, Miroslaw}
}
