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.


Multi-stage Attack Detection and Signature Generation with ICS Honeypots

Author Emmanouil Vasilomanolakis, Shreyas Srinivasa, Carlos Garcia Cordero, Max Mühlhäuser
Date April 2016
Kind Inproceedings
Book titleIEEE/IFIP Workshop on Security for Emerging Distributed Network Technologies (DISSECT)
Pages1227 - 1232
Research Areas CASED, Telecooperation, - SSI - Area Secure Smart Infrastructures, Secure Services
Abstract New attack surfaces are emerging with the rise of Industrial Control System (ICS) devices exposed on the Internet. ICS devices must be protected in a holistic and efficient manner; especially when these are supporting critical infrastructure. Taking this issue into account, cyber-security research is recently being focused on providing early detection and warning mechanisms for ICSs. In this paper we present a novel honeypot capable of detecting multi-stage attacks targeting ICS networks. Upon detecting a multi-stage attack, our honeypot can generate signatures so that misuse Intrusion Detection Systems (IDSs) can subsequently thwart attacks of the same type. Our experimental results indicate that our honeypot and the signatures it generates provide good detection accuracy and that the Bro IDS can successfully use the signatures to prevent future attacks.
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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