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Summary

Nowadays, mobile devices and networks allow us to be constantly connected anywhere. Often, these interactions leave a digital footprint that we are not aware of. Data, such as location information linked to our posts or searches in our browser may be processed by ML techniques that might allow a third party to infer sensitive information about our lives, such as location footprint. Consequently, there is a growing concern about the loss of control over personal data and the potential negative impact in our lives. Technology is now at a crossroads: trying to balance privacy and utility in scenarios that combine massive exchange communications, big databases and distributed and collaborative ML techniques towards the network edge. Precisely, the COMPROMISE project combines our knowledge in the areas of security, privacy, communication protocols, quality of service and ML, to face privacy improvements in network protocols and prevent privacy attacks, protecting communications with mechanisms that balance the trade-off between utility and privacy.

Our proposals seek a suitable compromise between utility and privacy, i.e., between the utility obtained by the user from the use of the service and the utility of gathered data after privacy enhancement techniques (PET) have been applied. The proposed advances in these topics are at the intersection of the following technologies: ML, fog computing, security protocols, vehicular networks, sensing networks, massive and distributed storage systems and dynamic databases. Consequently, the combination of these technologies constitutes the skeleton of current and future applications: distributed data and computation over wireless networks and protocols. The different research teams participating in this proposal have extensive experience in some of those complementary technologies and in the provision of privacy:

UPC group. (i) Anonymization of dynamic stream databases with high utility and high protection guarantees for both syntactic and differential privacy models; (ii) Development of theory and methods of collaborative anonymization; (iii) Design mechanisms and algorithms to protect the privacy of sensitive data exchanged on mobile wireless networks (MWNs) during the operation of network protocols; (iv) Enhancing privacy-aware services over MWNs (e.g., vehicular networks and mesh networks).

UC3M group. (i) Confidentiality vulnerabilities in HTTPS over TLS 1.3 and QUIC, and develop improvements; (ii) Confidentiality vulnerabilities in DNS and develop improvements; (iii) Study attacks based on machine learning techniques in IoT protocols and develop improvements; (iv) Study the privacy threats related to the location of users and propose improvements.

UVIGO group. (i) Smart data sample and smart exchange for ML training; (ii) Models for collaborative & distributed inference; (iii) Optimal & scalable ML architecture; (iv) Discovering privacy vulnerabilities in a collaborative ML architecture.

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Team

COMPROMISE is a coordinated project which consists of three subprojects, involving the following partners and team members:

COMPROMISE. Data privacy for communication networks and dynamic databases (PID2020-113795RB-C31) - UPC

COMPROMISE. Improving confidentiality and privacy in communication protocols (PID2020-113795RB-C32) - UC3M

COMPROMISE. Privacy resilience in collaborative and distributed machine learning under utility and performance requirements (PID2020-113795RB-C33) - UVIGO

Advisory board

News & Events

  • 16th Nov 2021. Kick-off Project meeting (Online). First meeting of the COMPROMISE Academic research team. We introduced our project website, email list, and social media. We agreed to several work meetings
    for the next few months. We reviewed the start of the work packages and we discussed the presentation of project applications in imminent calls.
  • 17th-18th Jan 2022. PhD Workshop meeting (Online). Our PhD students briefly presented their research work. The goal is to foresee possible future collaborations for the COMPROMISE project.
    PhD presentations (15 minutes) + 5 min Q&A (questions+answers).
  • 15th May 2022. Press interview . Ana Fernández Vilas, Manuel Fernández Veiga, Rebeca Díaz Redondo, "Cómo conseguir que las aplicaciones funcionen respetando la privacidad", entrevista realizada por Ángel Paniagua en La Voz de Galicia.
  • 30th Sep 2022 Press interview . Ana Fernández Vilas, Manuel Fernández Veiga, Rebeca Díaz Redondo, "A encrucillada tecnolóxica: fragmentar a nosa pegada dixital para preservar a privacidade", entrevista realizada por Lorena Bustabad en GCiencia Xornalismo + Divulgación.
  • 29th-30th Nov 2022 Second Project meeting (Presential at UC3M). Second global meeting of the COMPROMISE Academic research team. We reviewed the status of each work package, we discussed our internal collaborations, we planned short stays for our doctoral students at each University. In addition, we scheduled a series of talks until July 2023 by our doctoral students. Tweet meeting.
  • 2nd March 2023 1st PhD talk 2023 (online). Our PhD student Martín González Soto, supervided by Rebeca Díaz and Manuel Fernádez (UVigo) presented his Thesis topic: Application of Incremental learning and eXplanaible AI to Industry 4.0 Meeting tweet.
  • 27th Feb - 3rd March 2023. We have presented our projects MobilitApp and ANEM in the UPC booth of the Mobile World Congress 2023. Both are related to the COMPROMISE project. Tweet MobilitApp and Tweet ANEM.
  • 17th March 2023 2nd PhD talk 2023 (online). Our PhD student Juan José López Escobar, supervided by Rebeca Díaz (UVigo) presented his Thesis topic: Design of a new distributed mist, edge and fog architecture in beyond-5G environments for the Internet of Things.
  • 17th-18th Jan 2022
  • 17th-18th Jan 2022
  • 17th-18th Jan 2022
  • 17th-18th Jan 2022
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Publications

2023 - Articles

  1. Jaime Pérez Díaz, Florina Almenares, "Integrating an optimised PUF-based authentication scheme in OSCORE", Ad Hoc Networks, DOI: 10.1016/j.adhoc.2022.103038 , Volume 140, 2023.
  2. María Isabel Rojo-Rivas, Daniel Díaz-Sánchez, Florina Almenarez, Andrés Marín-López, "Kriper: A blockchain network with permissioned storage", Future Generation Computer Systems, DOI: 10.1016/j.future.2022.08.006 , Volume 138, pp. 160-17, 2023.

2022 - Articles

  1. Wunderlich, D., Bernau, D., Parra-Arnau, J., Aldà, F., Strufe, T., "On the privacy-utility trade-off in differentially private hierarchical text classification", Applied Sciences, November 2022, DOI: 10.3390/app122111177
  2. López Escobar, J. J., Díaz Redondo, R. P., Gil-Castiñeira, F., "In-depth analysis and open challenges of Mist Computing forums", Computational Intelligence and Neuroscience, November 2022, DOI: 10.1186/s13677-022-00354-x
  3. Mabrouk, A. Dahou, A. Abd Elaziz, M, Díaz Redondo, R., Kayed, M., "Medical Image Classification Using Transfer Learning and Chaos Game Optimization on the Internet of Medical Things", Computational Intelligence and Neuroscience, July 2022, DOI: 10.1155/2022/9112634
  4. Ahmad Mohamad Mezher, Mónica Aguilar Igartua, "G-3MRP: A game-theoretical multimedia multimetric map-aware routing protocol for vehicular ad hoc networks", DOI: 10.1016/j.comnet.2022.109086 , Computer Networks, ISSN: 1389-1286, Vol. 213, pp. 1-17, August 2022. (IF 2021 = 5.493; 20/94; Telecommunications; Q1)
  5. Mabrouk, A., Díaz Redondo, R., Dahou, A. Abd Elaziz, M, Kayed, M. , "Pneumonia Detection on Chest-XRay images Using Ensemble of Deep Convolutional Neural Networks", Applied Sciencies, June 2022, DOI: 10.3390/app12136448
  6. J. Parra-Arnau, T. Strufe, J. Domingo-Ferrer, "Differentially private publication of database streams via hybrid video coding", Elsevier Knowledge-Based Systems, Vol. 247, July 2022, DOI: 10.1016/j.knosys.2022.10877 . Impact factor (SCI 2020): 8.038. Q1 (16th out of 139) in Computer Science, Artificial Intelligence.
  7. de la Cruz Severiche Maury, Z., Fernández Vilas, A., Díaz Redondo, R., "Low-Cost HEM with Arduino and Zigbee Technologies in the Energy Sector in Colombia", Energies, DOI: 10.3390/en15103819
  8. Marta Moure-Garrido, Celeste Campo, Carlos García-Rubio, "Entropy-Based Anomaly Detection in Household Electricity Consumption", Energies, DOI: 10.3390/en15051837 , March 2022.
  9. Pablo Barbecho Bautista, Luis Urquiza Aguiar, Mónica Aguilar Igartua, "How does the traffic behavior change by using SUMO traffic generation tools", DOI: 10.1016/j.comcom.2021.09.023 , Computer Communications, ISSN: 0140-3664, Vol. 181, pp. 1-13, January 2022. (IF 2021 = 5.047; 61/276; Engineering, Electrical & Electronic; Q1)

2022 - Conferences

  1. Carlos Garcia-Rubio, Celeste Campo, Marta Moure-Garrido, "Synthetic Generation of Electrical Consumption Traces in Smart Homes", International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2022). Lecture Notes in Networks and Systems, vol 594. Springer, Cham, DOI: 10.1007/978-3-031-21333-5_68
  2. Daniel Díaz-Sanchez, Florina Almenarez Mendoza, Andrés Marán López, María Isabel Rojo Rivas, "A Hybrid Approach to Ephemeral PKI Credentials Validation and Auditing", International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2022). Lecture Notes in Networks and Systems, vol 594. Springer, Cham, DOI: 10.1007/978-3-031-21333-5_104
  3. Marta Moure-Garrido, Celeste Campo, and Carlos Garcia-Rubio, "Detecting Malicious Use of DoH Tunnels Using Statistical Traffic Analys", 19th ACM International Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, and Ubiquitous Networks (PE-WASUN 2022), DOI: 10.1145/3551663.3558605, October 2022, Montreal, Canada.
  4. González Soto, M., Fernández Castro, B., Díaz Redondo, R. and Fernández Veiga, M., "XuILVQ: A River Implementation of the Incremental Learning Vector Quantization for IoT", 19th ACM International Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, and Ubiquitous Networks (PE-WASUN 2022), DOI: 10.1145/3551663.3558676, October 2022, Montreal, Canada.
  5. García Santaclara, P., Fernández Vilas, A., and Díaz Redondo, R., "Prototype of deployment of Federated Learning with IoT devices", 19th ACM International Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, and Ubiquitous Networks (PE-WASUN 2022), DOI: 10.1145/3551663.3558681, October 2022, Montreal, Canada.
  6. El-Moaty Saleh, H., Fernández Vilas, A., Fernández Veiga, M., El-Sonbaty, Y., El-Bendary, N., "Using Decentralized Aggregation for Federated Learning with Differential Privacy", 19th ACM International Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, and Ubiquitous Networks (PE-WASUN 2022), DOI: 10.1145/3551663.3558682, October 2022, Montreal, Canada.
  7. Emmanuel Lomba, Ricardo Severino, Ana Fernández Vilas, "Towards Adaptive RF Fingerprint-based Authentication of IoT devices", 27th International Conference on Emerging Technologies and Factory Automation (ETFA 2022). IEEE Industrial Electronics Society (IES). September 2022. Stuttgart, Germany.
  8. Sergio Chica Manjárrez, Andrés Marín, David Arroyo Guardeño, Jesús Díaz, Florina Almenares, Daniel Díaz-Sánchez, "Enhancing the anonymity and auditability of whistleblowers protection", 4th International Congress on Blockchain and Applications. Workshop on Beyond the promises of web3.0: foundations and challenges of trust decentralization (WEB3-TRUST), DOI: 10.20350/digitalCSIC/14702, 13th-15th July, 2022, L'Aquila (Italy).
  9. Marta Moure-Garrido, Celeste Campo, Carlos García Rubio, "Análisis estadístico del tráfico DoH para la detección del uso malicioso de túneles", VII Jornadas Nacionales de Investigación en Ciberseguridad (JNIC), PDF, Bilbao, Spain, 27th- 29th June 2022.
  10. P. Guerra-Balboa, À. Miranda Pascual, J. Parra-Arnau, J. Forné T. Strufe, "Anonymizing trajectory data: limitations and opportunities", AAAI Workshop on Privacy-Preserving Artificial Intelligence (PPAI), PDF, Vancouver, Canada, March 2022.
  11. A. Tobar Nicolau, J. Parra-Arnau, J. Forné, "a,m-warden: A syntactic privacy notion for continuous data publishing against probabilistic attacks", Privacy in Statistical Databases (PSD) conference, 2022
  12. O. Zari, J. Parra-Arnau, A. Ünsal, T. Strufe, M. Önen, "Membership inference attack against principal component analysis", Privacy in Statistical Databases (PSD), Paris, France, pp. 269-282, DOI: 10.1007/978-3-031-13945-1_19, September 2022.

2021 - Conferences

  1. Pablo Barbecho Bautista, Luis F. Urquiza-Aguiar, Mónica Aguilar Igartua, An Evaluation of OMNeT++-based V2X Communication Frameworks: On the Path Towards 5G-V2X Simulations , 24th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWIM 2021), pp. 75-78, DOI:10.1145/3479239.3485723. Alicante, Spain. 22nd-26th November 2021.
  2. Pablo Barbecho Bautista, Luis Urquiza-Aguiar, Mónica Aguilar Igartua, STGT: SUMO-Based Traffic Mobility Generation Tool for Evaluation of Vehicular Networks , 18th ACM Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, & Ubiquitous Networks (PE-WASUN 2021), pp. 17-24, DOI:10.1145/3479240.3488523. Alicante, Spain. 22nd-26th November 2021.
  3. Leticia Lemus Cárdenas, Ahmad Mohamad Mezher, Juan Pablo Astudillo León, Mónica Aguilar Igartua, DTMR: A decision tree-based multimetric routing protocol for vehicular ad hoc networks , 18th ACM Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, & Ubiquitous Networks (PE-WASUN 2021), pp. 57-63, DOI:10.1145/3479240.3488525. Alicante, Spain. 22nd-26th November 2021.
  4. Xavier Calle Heredia, Pablo Barbecho Bautista, Mónica Aguilar Igartua, Performance Evaluation of Heterogeneous Vehicular Networks , 18th ACM Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, & Ubiquitous Networks (PE-WASUN 2021), pp. 25-32, DOI:10.1145/3479240.3488528. Alicante, Spain. 22nd-26th November 2021.
  5. Jaime Pérez, Florina Almenares, A PUF-based Authentication Mechanism for OSCORE , 18th ACM Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, & Ubiquitous Networks (PE-WASUN 2021), pp. 65-72, DOI:10.1145/3479240.3488526. Alicante, Spain. 22nd-26th November 2021.
  6. Mónica Aguilar Igartua, Luis Javier de la Cruz Llopis, Jordi Forné Muñoz, Esteve Pallarès Segarra, Francisco José Rico Novella, SISCOM: Smart Services for Information Systems and Communication Networks , XIII Jornadas de Ingeniería Telemática (JITEL 2021), Proceedings, p. 71, A Coruña, Spain. 27th-29th October 2021.
  7. Prashanth Kannan, Yaqoob Al-Zuhairi, Mónica Aguilar Igartua, "Hybrid Autonomous Connected Vehicle platooning with Federated Learning: State of the art and simulation Framework , XIII Jornadas de Ingeniería Telemática (JITEL 2021), Proceedings, p. 277-280, A Coruña, Spain. 27th-29th October 2021.
  8. Yaqoob Al-Zuhairi, Prashanth Kannan, Mónica Aguilar Igartua, Federated learning for smart charging of connected electric vehicles , XIII Jornadas de Ingeniería Telemática (JITEL 2021), Proceedings, p. 212-2150, A Coruña, Spain. 27th-29th October 2021.

Apps

MobilitApp is a tool to help to analyse the urban mobility in our cities. MobilitApp periodically records 3 sensors (accelerometer, magnetometer and gyroscope) from its users' smartphones. The information obtained is processed using machine learning techniques to predict the transportation mode used by the user, i.e. bicycle, bus, car, e-bicycle, e-scooter, metro, motorbike, run, stationary, train, tram and walk. The user's information is treated completely anonymously.

Data Sets

DataSet 5RoutingMetrics VANET BCN. Dataset composed by five routing metrics (available bandwidth, distance to destination, vehicles' density, MAC layer losses, and vehicle' trajectory) gathered from vehicular network simulations in urban scenarios in Barcelona. The dataset is used to train and test a machine learning-based forwarding algorithm.

Contact

Mónica Aguilar Igartua Coordinator

Acknowledges

Copyright © 2021 COMPROMISE. Template by W3layouts


  • Este trabajo es parte del proyecto de I+D+i ``Enhancing Communication Protocols with Machine Learning while Protecting Sensitive Data (COMPROMISE)" PID2020-113795RB-C3X, financiado por MCIN/AEI/10.13039/501100011033.
  • This work was supported by the Spanish Government under research project ``Enhancing Communication Protocols with Machine Learning while Protecting Sensitive Data (COMPROMISE)" PID2020-113795RB-C3X, funded by MCIN/AEI/10.13039/501100011033.
  • C3X = C31 (UPC), C32 (UC3M), C33 (UVigo)