@inbook {18521,
	title = {Runtime Classification of Mobile Malware for Resource-constrained Devices},
	booktitle = {Lecture Notes in Communications in Computer and Information Science},
	volume = {764},
	year = {2017},
	pages = {195-215},
	publisher = { Springer International Publishing AG},
	organization = { Springer International Publishing AG},
	doi = {https://doi.org/10.1007/978-3-319-67876-4_10},
	author = {Milosevic, Jelena and Malek, Miroslaw and Ferrante, Alberto}
}
@conference {18206,
	title = {A Resource-optimized Approach to Efficient Early Detection of Mobile Malware},
	booktitle = {3rd International Workshop on Security of Mobile Applications - IWSMA 2014},
	year = {2014},
	month = {09/2014},
	address = {Fribourg, Switzerland},
	author = {Milosevic, Jelena and Dittrich, Andreas and Ferrante, Alberto and Malek, Miroslaw}
}
@conference {18227,
	title = {Risk Assessment of Atrial Fibrillation: a Failure Prediction Approach},
	booktitle = {41st Computing in Cardiology Conference (CinC)},
	year = {2014},
	month = {09/2014},
	publisher = {IEEE Computer Society},
	organization = {IEEE Computer Society},
	address = {Cambridge, MA, USA},
	abstract = {We present a methodology for identifying patients who have experienced Paroxysmal Atrial Fibrillation (PAF) among a given subjects population. Our work is intended as an initial step towards the design of an unobtrusive system for concurrent detection and monitoring of chronic cardiac conditions.

Our methodology comprises two stages: off-line training and on-line analysis. During training the most significant features are selected using machine-learning methods, without relying on a manual selection based on previous knowledge. Analysis is based on two phases: feature extraction and detection of PAF patients. Light-weight algorithms are employed in the feature extraction phase, allowing the on-line implementation of this step on wearable and resource-constrained sensor nodes. The detection phase employs techniques borrowed from the field of failure prediction. While these algorithms have found extensive applications in diverse scenarios, their application to automated cardiac analysis has not been sufficiently investigated.

Obtained results, in terms of performance, are comparable to similar efforts in the field. Nonetheless, the proposed method employs computationally simpler and more efficient algorithms, which are compatible with the computational constraints of state-of-the-art body sensor nodes.},
	url = {http://andreas-dittrich.eu/2014/06/risk-assessment-of-atrial-fibrillation-a-failure-prediction-approach},
	author = {Milosevic, Jelena and Dittrich, Andreas and Ferrante, Alberto and Malek, Miroslaw and Rojas Quiros, Camilo and Braojos, Rub{\'e}n and Ansaloni, Giovanni and Atienza, David}
}
@conference {107.TaFe209,
	title = {Run-time Selection of Security Algorithms For Networked Devices},
	booktitle = {5th ACM International Symposium on QoS and Security for Wireless and Mobile Networks},
	year = {2009},
	address = {Tenerife, Canary Islands, Spain},
	abstract = {One of the most important challenges that need to be currently faced in securing resource-constrained embedded systems is optimizing the trade-off between resources used (energy consumption and computational capabilities required) and security requirements for cryptographic algorithms: any adopted security solutions should guarantee an adequate level of protection, yet respecting constraints on computational resources and consumed power. These constraints are given by the kind of system considered and by the foreseen applications. In this paper, a generic, efficient, and energy-aware mechanism is proposed to face the problem of determining a correct trade off between security requirements and resources consumed. The solution proposed relies on Analytic Hierarchy Process (AHP) to define priorities among different requirements and to compare different security solutions. A knapsack problem is formulated to select the most relevant algorithms based on their utility and on available resources.},
	keywords = {adaptive systems, algorithm selection, protocol, quality of service (QoS), security},
	doi = {http://dx.doi.org/10.1145/1641944.1641963},
	author = {Taddeo, Antonio Vincenzo and Ferrante, Alberto}
}
