    @inproceedings {1846,
	title = {Distributed Detection of APTs: Consensus vs. Clustering},
	booktitle = {25th European Symposium on Research in Computer Security (ESORICS 2020)},
	volume = {12308},
	year = {2020},
	month = {09/2020},
	pages = {174-192},
	keywords = {Advanced Persistent Threat, clustering, consensus, distributed detection, Opinion Dynamics, Traceability},
	isbn = {978-3-030-58951-6},
	doi = {https://doi.org/10.1007/978-3-030-58951-6_9},
	author = {Juan E. Rubio and Cristina Alcaraz and Ruben Rios and Rodrigo Roman and Javier Lopez}
}
@article {Rubio2020IIoT,
	title = {Integration of a Threat Traceability Solution in the Industrial Internet of Things},
	journal = {IEEE Transactions on Industrial Informatics},
	volume = {16},
	number = {6575-6583},
	year = {2020},
	month = {10/2020},
	publisher = {IEEE},
	abstract = {In Industrial Internet of Things (IIoT) scenarios, where a plethora of IoT technologies coexist with consolidated industrial infrastructures, the integration of security mechanisms that provide protection against cyber-security attacks becomes a critical challenge. Due to the stealthy and persistent nature of some of these attacks, such as Advanced Persistent Threats, it is crucial to go beyond traditional Intrusion Detection Systems for the traceability of these attacks. In this sense, Opinion Dynamics poses a novel approach for the correlation of anomalies, which has been successfully applied to other network security domains. In this paper, we aim to analyze its applicability in the IIoT from a technical point of view, by studying its deployment over different IIoT architectures and defining a common framework for the acquisition of data considering the computational constraints involved. The result is a beneficial insight that demonstrates the feasibility of this approach when applied to upcoming IIoT infrastructures.
},
	keywords = {Detection, Dynamics, IIoT, Industry, Intrusion, Opinion, Traceability},
	issn = {1551-3203},
	doi = {10.1109/TII.2020.2976747},
	author = {Juan E. Rubio and Rodrigo Roman and Javier Lopez}
}
@inproceedings {RubioRomanAlcarazZhang2018,
	title = {Tracking Advanced Persistent Threats in Critical Infrastructures through Opinion Dynamics},
	booktitle = {European Symposium on Research in Computer Security (ESORICS 2018)},
	volume = {11098},
	year = {2018},
	month = {08/2018},
	pages = {555-574},
	publisher = {Springer},
	organization = {Springer},
	address = {Barcelona, Spain},
	abstract = {<p class="rtejustify">Advanced persistent threats pose a serious issue for modern industrial environments, due to their targeted and complex attack vectors that are difficult to detect. This is especially severe in critical infrastructures that are accelerating the integration of IT technologies. It is then essential to further develop effective monitoring and response systems that ensure the continuity of business to face the arising set of cyber-security threats. In this paper, we study the practical applicability of a novel technique based on opinion dynamics, that permits to trace the attack throughout all its stages along the network by correlating different anomalies measured over time, thereby taking the persistence of threats and the criticality of resources into consideration. The resulting information is of essential importance to monitor the overall health of the control system and correspondingly deploy accurate response procedures.</p>
},
	keywords = {Advanced Persistent Threat, Detection, Opinion Dynamics, Traceability},
	doi = {10.1007/978-3-319-99073-6_27},
	url = {https://link.springer.com/chapter/10.1007/978-3-319-99073-6_27},
	author = {Juan E. Rubio and Rodrigo Roman and Cristina Alcaraz and Yan Zhang}
}
