Contact Details

nameCarlos Garcia Cordero
positionPhD 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

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 cybersecurity, 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 honours.


Additional Attributes


ID2T: a DIY dataset creation toolkit for Intrusion Detection Systems

Carlos Garcia Cordero, Emmanouil Vasilomanolakis, Nikolay Milanov, Christian Koch, David Hausheer, Max Mühlhäuser
In: IEEE Conference on Communications and Network Security (CNS), p. 739 - 740, September 2015

Community-based Collaborative Intrusion Detection

Carlos Garcia Cordero, Emmanouil Vasilomanolakis, Mathias Fischer, Max Mühlhäuser
In: International Workshop on Applications and Techniques in Cyber Security (ATCS) , International Conference on Security and Privacy in Communication Networks (SecureComm), Vol. 164, p. 665-681, 2015
Springer International Publishing

Security Perspectives for Collaborative Data Acquisition in the Internet of Things

Vangelis Gazis, Carlos Garcia Cordero, Emmanouil Vasilomanolakis, Panayotis Kikiras, Alexander Wiesmaier
In: International Conference on Safety and Security in Internet of Things, Vol. 151, p. 271-282, 2014
Springer International Publishing


1 Entries found

On the Analysis & Generation of Synthetic Attacks for Intrusion Detection Systems

Master Thesis


Intrusion Detection Systems (IDS) have established themselves as a mandatory line of defense for critical infrastructure. One main aspect during the development of an IDS is the evaluation and optimization of the detection algorithms. Currently there is no standardized model for the evaluation of the detection efficiency. A common approach has been the use of static datasets, but the publicly available datasets have flaws in many regards, like their actuality and the absence of up-to-date attacks.This creates challenges in terms of the reproducibility and the comparison of results.

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