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

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
PublisherIEEE
Book titleIEEE/IFIP Workshop on Security for Emerging Distributed Network Technologies (DISSECT)
Pages1227 - 1232
ISBN978-1-5090-0223-8
ISSN2374-9709
DOI10.1109/NOMS.2016.7502992
KeyTUD-CS-2016-0033
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.
Website http://www.dissect.vcu.edu/2016
Full paper (pdf)
[Export this entry to BibTeX]

Important Copyright Notice:

The documents contained in these directories are included by the contributing authors as a means to ensure timely dissemination of scholarly and technical work on a non-commercial basis. Copyright and all rights therein are maintained by the authors or by other copyright holders, notwithstanding that they have offered their works here electronically. It is understood that all persons copying this information will adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

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.


A A A | Drucken Print | Impressum Impressum | Sitemap Sitemap | Suche Search | Kontakt Contact | Website Analysis: More Information
zum Seitenanfangzum Seitenanfang