MAGOS

Smart meters with enhanced capabilities of communication and control will contribute to adapt and tune energy delivery more efficiently. The road from a closed system to a highly complex interconnected ecosystem as the smart grids was driven by efficiency and resiliency. Now we require smart grids to be more cyber resilient, prepared to face the approaching cyber threats. Today’s trends situate risk management in the core of cybersecurity strategies: identification of threats, risk analysis on the potential impact on the assets, implementation of countermeasures, and tuning or establishing new security controls for better threat detection. The majority of the cyber threats include exploiting some vulnerability of the system, and new vulnerabilities are appearing, almost every day, specially favored by the increasing complexity and fast life cycles of firmware and software. That explains why vulnerability assessments require smart grid operator involvement, even with the help of vendors and manufacturers and the certification processes. The MAGOS project aims at helping operators to build secure environments where vulnerability assessments can be performed at lower costs, minimizing the exposure of system elements to faults and cyber threats. The MAGOS project will research on such testing environments, and will also research different security, privacy and performance aspects of protocols, networks and systems related to smart grids. Besides, there is a need to gather intelligence to help the risk assessment process, additive to the intelligence on consumption trends and predictions actually used by the operators to perform their planning operations. We aim at intelligence that can be found in open sources, from social networks, specialized blogs and sites, and data gathered by smart meters and other devices and systems, notably security information event monitoring systems (SIEMS) looking for information and comments that may be related to smart grid vulnerabilities and their corresponding exploits. A critical infrastructure such as the energy delivery system demands this intelligence to improve its readiness to execute the countermeasure processes. Multiple challenges appear to gather this intelligence preserving users’ privacy in a myriad of growing information. The MAGOS project will research on mining fusion and analysis techniques to discover and uncover knowledge for smart grid protection.

MEMBERS

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RESULTS

RTUCON2018: “Smart Grids Monitoring: A fog-computing strategy to detect anomalies” (accepted in IEEE 59th International Scientific Conference on Power and Electrical Engineering of Riga Technical University)

UCAMI2018: Florina Almenares, Lucía Alonso, Andrés Marín López, Daniel Díaz-Sánchez and Patricia Arias Cabarcos, “Assessment of Fitness Tracker Security: A case of study” (aceptada)

UCAMI2018: Daniel Díaz-Sánchez, Andrés Marín, Florina Almenarez and Patricia Arias Cabarcos, “DNS-based dynamic authentication for microservices in IoT” (aceptada)

MPS’18: Patricia Arias-Cabarcos, Florina Almenárez, Daniel Díaz-Sánchez, and Andrés Marín, “FRiCS: A Framework for Risk-driven Cloud Selection”. In 2nd International Workshop on Multimedia Privacy and Security (MPS ’18), in ACM SIGSAC Conference on Computer and Communications Security. October 15, 2018, Toronto, ON, Canada. ACM, New York, NY, USA, 9 pages. https://doi.org/10.1145/3267357.3267362

Rodriguez-Carrion, A.; Garcia-Rubio, C.; Campo, C. Detecting and Reducing Biases in Cellular-Based Mobility Data Sets. Entropy 2018, 20, 736. https://www.mdpi.com/1099-4300/20/10/736

PE-WASUN 2018: Multi Channel Allocation and Congestion Control for Smart Grid Neighborhood Area Networks, Juan Pablo Astudillo León and Luis J. de la Cruz Llopis. Proceedings of the 15th ACM International Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, & Ubiquitous Networks, pp. 1-8, Montreal, QC, Canada, 2018. DOI: 10.1145/3243046.3243050.

A Joint Multi-Path and Multi-Channel Protocol for Traffic Routing in Smart Grid Neighborhood Area Networks,  Juan Pablo Astudillo León and Luis J. de la Cruz Llopis. Sensors 18(11): 4052 (2018). DOI: 10.3390/s18114052. https://www.mdpi.com/1424-8220/18/11/4052.

CONTACT

Andrés Marín López

Tlf: (+34) 91-624-9947

amarin@it.uc3m.es

Universidad Carlos III de Madrid.

Avda. de la Universidad, 30, Leganés

Despacho 4.1C12

ADVISORY BOARD

Naturgy
Red Eléctrica España
INCIBE (Instituto Nacional de Ciberseguridad)
IOActive
ATOS España
Eleven Paths, the Telefónica cyber security unit
ATM-Barcelona
ABANCA
ZIV