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Karl Leidl

Centre for Applied Research

Technology Campus Teisnach Sensor Technology I 4.0

Operative Manager

TCTS O 05

09923/80108-510

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Zeitungsartikel

  • Karl Leidl

Digitalisierung - aber sicher ... von Anfang an!

In: Niederbayerische Wirtschaft der IHK Passau vol. 2021 pg. 36-37.

  • 2021 (2021)

  • 30 S: TC Vilshofen S_EN: TC Vilshofen
  • Institut ProtectIT
  • DIGITAL
Vortrag

  • Karl Leidl
  • R. Habermann

Intelligente Anlagenüberwachung - Digitalisierung sicher meistern

In: MES im Fokus

Heidelberg

  • 23.01.2020 (2020)
  • Institut ProtectIT
  • 30 S: TC Vilshofen S_EN: TC Vilshofen
  • DIGITAL
Vortrag

  • Karl Leidl

Anomalieerkennung in industriellen Netzwerken - Cybersicherheit mit Machine Learning

In: Forum Künstliche Intelligenz

Stuttgart

  • 14.05.2019 (2019)
  • TC Teisnach Sensorik
  • Institut ProtectIT
  • 30 S: TC Vilshofen S_EN: TC Vilshofen
  • Elektrotechnik und Medientechnik
  • DIGITAL
Zeitschriftenartikel

  • Karl Leidl
  • Andreas Grzemba

Secure per Machine Learning - Wie KI die Informationssicherheit verbessern kann

In: Computer & Automation (Sonderheft Safety & Security)

  • (2019)

  • Institut ProtectIT
  • TC Teisnach Sensorik
  • 30 S: TC Vilshofen S_EN: TC Vilshofen
  • Elektrotechnik und Medientechnik
  • DIGITAL
Beitrag in Sammelwerk/Tagungsband

  • Karl Leidl
  • Andreas Grzemba

Cybersicherheit in industriellen Netzwerken - Intrusion Detection mit Machine Learning

  • (2019)
  • Elektrotechnik und Medientechnik
  • 30 S: TC Vilshofen S_EN: TC Vilshofen
  • TC Teisnach Sensorik
  • Institut ProtectIT
  • DIGITAL
Beitrag in Sammelwerk/Tagungsband

  • Robert Wildenauer
  • Karl Leidl
  • Martin Schramm

Hacking an optics manufacturing machine: You don't see it coming?!

pg. 11171071-11171076.

Bellingham, WA, USA

  • (2019)

DOI: 10.1117/12.2526691

With more and more industrial devices getting inter-connected the attack surface for cyber attacks is increasing steadily. In this paper the possible approach of an attacker who got access to the office network at the Institute for Precision Manufacturing and High-Frequency Technology (IPH) to attack one of the optic machines that reside in another network segment is presented. Based on known vulnerabilities from the Common Vulnerabilities and Exposures (CVE), like the shellshock exploit or remote code execution with PsExec, for devices identified in the network, an attacker can bypass the firewall between the office network and the laboratory network and get full access to the HMI of the target machine.
  • Elektrotechnik und Medientechnik
  • TC Teisnach Sensorik
  • 30 S: TC Vilshofen S_EN: TC Vilshofen
  • Institut ProtectIT
  • DIGITAL
Vortrag

  • Karl Leidl

Cybersicherheit in industriellen Netzwerken - Intrusion Detection mit Machine Learning

In: Forum Safety & Security

Sindelfingen

  • 08.-10.07.2019 (2019)
  • TC Teisnach Sensorik
  • 30 S: TC Vilshofen S_EN: TC Vilshofen
  • Institut ProtectIT
  • Elektrotechnik und Medientechnik
  • DIGITAL
Zeitschriftenartikel

  • Nari Arunraj
  • Robert Hable
  • Michael Fernandes
  • Karl Leidl
  • Michael Heigl

Comparison of Supervised, Semi-supervised and Unsupervised Learning Methods in Network Intrusion Detection Systems (NIDS) Application

In: Anwendungen und Konzepte in der Wirtschaftsinformatik (AKWI) pg. 10-19.

  • (2017)
With the emergence of the fourth industrial revolution (Industrie 4.0) of cyber physical systems, intrusion detection systems are highly necessary to detect industrial network attacks. Recently, the increase in application of specialized machine learning techniques is gaining critical attention in the intrusion detection community. A wide variety of learning techniques proposed for different network intrusion detection system (NIDS) problems can be roughly classified into three broad categories: supervised, semi-supervised and unsupervised. In this paper, a comparative study of selected learning methods from each of these three kinds is carried out. In order to assess these learning methods, they are subjected to investigate network traffic datasets from an Airplane Cabin Demonstrator. In addition to this, the imbalanced classes (normal and anomaly classes) that are present in the captured network traffic data is one of the most crucial issues to be taken into consideration. From this investigation, it has been identified that supervised learning methods (logistic and lasso logistic regression methods) perform better than other methodswhen historical data on former attacks are available. The results of this study have also showed that the performance of semi-supervised learning method (One class support vector machine) is comparatively better than unsupervised learning method (Isolation Forest) when historical data on former attacks are not available.
  • TC Grafenau
  • TC Teisnach Sensorik
  • Institut ProtectIT
  • 30 S: TC Vilshofen S_EN: TC Vilshofen
  • DIGITAL
Vortrag

  • Karl Leidl
  • Martin Aman
  • Michael Heigl
  • Andreas Grzemba

Intrusion Detection Sensoren für industrielle Netzwerke

In: CYBICS - Cyber Security for Industrial Control Systems (Workshop & Konferenz für IT-Sicherheit in der Industrie)

Würzburg

  • 22.-23.06.2016 (2016)
  • TC Teisnach Sensorik
  • 30 S: TC Vilshofen S_EN: TC Vilshofen
  • Elektrotechnik und Medientechnik
  • Institut ProtectIT
Vortrag

  • Peter Semmelbauer
  • Karl Leidl
  • Martin Aman
  • Laurin Dörr
  • Andreas Grzemba

Schwachstellen, Angriffsszenarien und Schutzmaßnahmen bei industriellen Protokollen am Beispiel Profinet IO

In: Automation 2016 - Secure & reliable in the digital world

Baden-Baden

  • 07.-08.06.2016 (2016)
  • TC Teisnach Sensorik
  • Institut ProtectIT
  • Elektrotechnik und Medientechnik
  • 30 S: TC Vilshofen S_EN: TC Vilshofen
Vortrag

  • Karl Leidl

Cyber Security for Process Control Networks

In: 1st European Seminar on Precision Optics Manufacturing

Technische Hochschule Deggendorf/Technologie Campus Teisnach Teisnach

  • 01.04.2014 (2014)
  • Elektrotechnik und Medientechnik
  • 30 S: TC Vilshofen S_EN: TC Vilshofen
  • TC Teisnach Sensorik
  • Institut ProtectIT
Vortrag

  • Karl Leidl
  • Andreas Grzemba
  • Laurin Dörr

Live Hacking

In: it-sa

Nürnberg

  • 8.-10. Oktober 2013 (2013)
  • 30 S: TC Vilshofen S_EN: TC Vilshofen
  • TC Teisnach Sensorik
  • Elektrotechnik und Medientechnik
  • Institut ProtectIT
Vortrag

  • Karl Leidl

Cyber Security for Industrial Control Systems

In: IHS Industrial Automation Conference

Wien, Österreich

  • 02.10.2013 (2013)
  • Institut ProtectIT
  • 30 S: TC Vilshofen S_EN: TC Vilshofen
  • TC Teisnach Sensorik
  • Elektrotechnik und Medientechnik
Vortrag

  • Karl Leidl
  • Peter Fröhlich
  • Andreas Grzemba

Embedded Security with Respect to Industrial Control Systems . Workshop

In: Embedded World Conference 2013

Nürnberg

  • 26.-28.02.2013 (2013)
  • Institut ProtectIT
  • TC Teisnach Sensorik
  • 30 S: TC Vilshofen S_EN: TC Vilshofen
  • Elektrotechnik und Medientechnik
Vortrag

  • Martin Schramm
  • Karl Leidl
  • Andreas Grzemba
  • N. Kuntze

Enhanced Embedded Device Security by Combining Hardware-Based Trust Mechanisms . Poster-Session

In: ACM Conference on Computer and Communications Security

Berlin

  • 04.-08.11.2013 (2013)
  • Elektrotechnik und Medientechnik
  • TC Teisnach Sensorik
  • 30 S: TC Vilshofen S_EN: TC Vilshofen
  • Institut ProtectIT
Vortrag

  • Karl Leidl
  • Martin Schramm
  • Andreas Grzemba

The Establishment of High Degrees of Trust in a Linux Environment

In: Embedded World International Conference 2012

Nürnberg

  • 28.02.-01.03.2012 (2012)
  • 30 S: TC Vilshofen S_EN: TC Vilshofen
  • Elektrotechnik und Medientechnik
  • Institut ProtectIT
  • TC Teisnach Sensorik