Contact Details

nameCarlos Garcia Cordero
positionPhD at GRK Privacy and Trust for mobile Users
email

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
Germany

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.

Publications

On Probe-Response Attacks in Collaborative Intrusion Detection Systems

Author Emmanouil Vasilomanolakis, Michael Stahn, Carlos Garcia Cordero, Max Mühlhäuser
Date October 2016
Kind Inproceedings
PublisherIEEE
Book titleIEEE Conference on Communications and Network Security
Pages279 - 286
LocationPhiladelphia, USA
ISBN978-1-5090-3065-1
DOI10.1109/CNS.2016.7860495
KeyTUD-CS-2016-0164
Research Areas Telecooperation, CROSSING, CRISP, - SSI - Area Secure Smart Infrastructures, Fachbereich Informatik, SPIN: Smart Protection in Infrastructures and Networks, CYSEC
Abstract Cyber-attacks are steadily increasing in both their size and sophistication. To cope with this, Intrusion Detection Systems (IDSs) are considered mandatory for the protection of critical infrastructure. Furthermore, research is currently focusing on collaborative architectures for IDSs, creating a Collaborative IDS (CIDS). In such a system a number of IDS monitors work together towards creating a holistic picture of the monitored network. Nevertheless, a class of attacks exists, called probe-response, which can assist adversaries to detect the network position of CIDS monitors. This can significantly affect the advantages of a CIDS. In this paper, we introduce PREPARE, a framework for deploying probe-response attacks and also for studying methods for their mitigation. Moreover, we present significant improvements on both the effectiveness of probe-response attacks as well as on mitigation techniques for detecting them. We evaluate our approach via an extensive simulation and a real-world attack deployment that targets two CIDSs. Our results show that our framework can be practically utilized, that our proposals significantly improve probe-response attacks and, lastly, that the introduced detection and mitigation techniques are effective.
Website http://cns2016.ieee-cns.org/
Full paper (pdf)
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Theses

1 Entries found


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

Master Thesis

finished


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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