Contact Details

nameCarlos Garcia Cordero
positionResearcher at GRK: Privacy and Trust for mobile Users

garcia (AT) tk(DOT)tu-darmstadt(DOT)de

phone+49 (6151) 16 - 23205
fax+49 (6151) 16 - 23202
officeS2|02 A 316
postal addressTU Darmstadt - FB 20
FG Telekooperation
Hochschulstraße 10
D-64289 Darmstadt

Research Interests

  • Machine learning

    • Anomaly Detection
    • Bayesian Networks
    • Deep Learning

  • Network Intrusion Detection

    • Collaborative Intrusion Detection
    • Distributed Intrusion Detection

  • Human Computer Interaction

    • 3D printing, computer graphics and 3D modeling tools

Short Biography

Carlos García Cordero is a scientist, systems engineer, mathematician, musician and thinker.

Carlos' research experience and interests are wide and cover diverse topics such as cyber-security, artificial intelligence, programming languages, compilers, machine learning and computer graphics, among others. 

Carlos is currently studying a PhD in Cyber Security and Distributed Machine Learning at TU Darmstadt. He has an MSc in Artificial Intelligence from The University of Edinburgh and a BSc in Computer Systems Engineering from the ITESM CSF in Mexico, both achieved with the highest honors.


SkipMon: a Locality-Aware Collaborative Intrusion Detection System

Author Emmanouil Vasilomanolakis, Matthias Kruegl, Carlos Garcia Cordero, Mathias Fischer, Max Mühlhäuser
Date December 2015
Kind Inproceedings
Book titleInternational Performance Computing and Communications Conference (IPCCC)
Pages1 - 8
LocationNanjing, China
Research Areas CASED, Telecooperation, Secure Services, - SSI - Area Secure Smart Infrastructures
Abstract Due to the increasing quantity and sophistication of cyber-attacks, Intrusion Detection Systems (IDSs) are nowadays considered mandatory security mechanisms for protecting critical networks. Research on cyber-security is moving from such isolated IDSs towards Collaborative IDSs (CIDSs) in order to protect large-scale networks. In CIDSs, a number of IDS sensors work together for creating a holistic picture of the monitored network. Our contribution in this paper is a novel distributed and scalable CIDS, called SkipMon. Our system supports, both, the idea of locality and privacy preserving communication by means of exchanging compact alert data. Furthermore, we propose a mechanism for interconnecting sensors that experience similar traffic patterns. The experimental results suggest that our CIDS, with our technique of connecting monitoring nodes that experience similar traffic, is scalable and offers a good accuracy rate compared to a centralized system with full knowledge of the participating sensors’ data.
Full paper (pdf)
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2 Entries found


Optimizing holon-based energy networks using Particle Swarm Optimization

Bachelor Thesis

in progress


Predicting vulnerabilities in software

Master Thesis

in progress

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