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Konrad Rieck

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Name	Konrad Rieck
Zeit	2004- (Wirkungsdaten)
Ort	Wien (Wirkungsort) Berlin (Wirkungsort) Göttingen (Wirkungsort) Deutschland Österreich
Geschlecht	männlich
Akademischer Grad bzw. Titel	Prof. Dr.
Beruf	Informatiker (charakteristischer Beruf)
Beziehung	Georg-August-Universität Göttingen Technische Universität Berlin Technische Universität Wien. Fakultät für Informatik
Weitere Angaben	Dissertation 2004 ; Universitätsprofessor TU Berlin Fakultät für Informatik ; Gastprofessor TU Wien Fakultät für Informatik
Quelle	Internet: http://user.informatik.uni-goettingen.de/~krieck/ https://orcid.org/0000-0002-5054-8758670 (Stand: 17.05.2024) https://tiss.tuwien.ac.at/person/408365.html (Stand: 17.05.2024)
Datensatztyp	Person
GND-Nummer	1045255491
Datensatz-ID	1045255491
Beteiligt an alle anzeigen On the Security of Machine Learning Beyond the Feature Space Automatic Analysis of Malware Behavior using Machine Learning Cujo: Efficient Detection and Prevention of Drive-by-Download Attacks Defending Against Targeted Attacks with Pattern Recognition Efficient and Explainable Detection of Mobile Malware with Machine Learning Efficient Machine Learning for Attack Detection Compiler assisted vulnerability assessment Accelerated secure GUI for virtualized mobile handsets Detection of intrusions and malware, and vulnerability assessment : 10th international conference ; proceedings Detection of Intrusions and Malware, and Vulnerability Assessment : 10th International Conference, DIMVA 2013, Berlin, Germany, July 18-19, 2013. Proceedings ASAP : automatic semantics-aware analysis of network payloads ASAP: automatic semantics-aware analysis of network payloads Cujo: efficient detection and prevention of drive-by-download attacks A malware instruction set for behavior-based analysis Automatic analysis of malware behavior using machine learning Machine learning for application layer intrusion detection

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Katalog der Deutschen Nationalbibliothek

Konrad Rieck

On the Security of Machine Learning Beyond the Feature Space

Automatic Analysis of Malware Behavior using Machine Learning

Cujo: Efficient Detection and Prevention of Drive-by-Download Attacks

Defending Against Targeted Attacks with Pattern Recognition

Efficient and Explainable Detection of Mobile Malware with Machine Learning

Efficient Machine Learning for Attack Detection

Compiler assisted vulnerability assessment

Accelerated secure GUI for virtualized mobile handsets

Detection of intrusions and malware, and vulnerability assessment : 10th international conference ; proceedings

Detection of Intrusions and Malware, and Vulnerability Assessment : 10th International Conference, DIMVA 2013, Berlin, Germany, July 18-19, 2013. Proceedings

ASAP : automatic semantics-aware analysis of network payloads

ASAP: automatic semantics-aware analysis of network payloads

Cujo: efficient detection and prevention of drive-by-download attacks

A malware instruction set for behavior-based analysis

Automatic analysis of malware behavior using machine learning

Machine learning for application layer intrusion detection