#Malware Analysis

The analysis of malware improves IT security, protects privacy and supports the defence against IT attacks.

Projects

SBA Research

K1 competence center for Information Security

Josef Ressel Center for Blockchain-Technologies & Security management

The Josef Ressel Center for Blockchain-Technologies & Security management is a research institution operated by the St. Pölten University of Applied Sciences. The research objective is making secur...

EMRESS - Making Software protection quantifiable

EMRESS develops models to quantify the strength of software protection techniques.

Josef Ressel Center for Unified Threat Intelligence on Targeted Attacks (TARGET)

The Josef Ressel Center for Unified Threat Intelligence on Targeted Attacks (TARGET) is a research institution operated by the St. Pölten University of Applied Sciences. Its mission is to explore nov...

SoniControl 2.0 - The first Ultrasonic Firewall

Extending SoniControl, the first ultrasonic firewall, that detects and blocks unwanted acoustic tracking on mobile devices.

PriSAd -Privacy and Security in Online Advertisement

Integral analysis of privacy and security of online advertising networks

KAVA-Time – How man and machine analyze data

Knowledge-Assisted Visual Analytics Methods for Time-Oriented Data. New methods will take advantage of explicit expert knowledge in the Visual Analytics process of data.

upribox 2 -Usable Privacy Box 2

The usable privacy box (upribox) is a network tool that filters ads on all connected devices such as smartphones or laptops and ultimately protects the user’s privacy. The upribox 2.0 is even easier...

upribox - Usable Privacy Box

The project "usable privacy box" (upribox) developes a software and creates a device that protects internet privacy and ensures data security.

Smartphone Security

This research project focuses on more or less neglected topics of cyber security (IT security) concerning smartphones, tablet-PCs and BYOD (bring your own device).

Publications

Eresheim, S. (2020). Reinforcement Learning for Incident Protection in IT. Presented at the First Conference on Mathematics of Data Science (MDS20).
Eresheim, S. (2020). Cybersecurity Containment Agent. Presented at the Machine Learning Prague 2020.
Luh, R., & Schrittwieser, S. (2019). Advanced threat intelligence: detection and classification of anomalous behavior in system processes. E \& i Elektrotechnik Und Informationstechnik, Springer, 1–7.
Pirker, M. (2019, November). More Data - More Security? Invited Talk presented at the TOP Alumni Club, TU Wien.
Pirker, M. (2019, October). Digitale Probleme....für Alle! Presented at the PrivacyWeek, Wien.
Schrittwieser, S. (2019, September). Sicherheit von Container-Virtualisierung. Invited Talk presented at the IDC Security Roadshow Vienna, Wien.
Luh, R., Janicke, H., & Schrittwieser, S. (2019). AIDIS: Detecting and classifying anomalous behavior in ubiquitous kernel processes. Computers & Security, (84), 120–147. https://doi.org/https://doi.org/10.1016/j.cose.2019.03.015
Luh, R. (2019). Advanced Threat Intelligence: Interpretation of Anomalous Behavior in Ubiquitous Kernel Processes (Dissertation). De Monfort University Leicester.
Wenzl, M., Merzdovnik, G., Ullrich, J., & Weippl, E. (2019). From Hack to Elaborate Technique—A Survey on Binary Rewriting. ACM Computing Surveys, 52(3 / Artikel 49).
Pirker, M. (2019, March). (Big) Data (Science) für Security. Invited Talk presented at the Vienna Data Science Group, Wien.

News

06/19/2020

New Science Format: Science@Home

12/06/2019

re.searched: Peter Kieseberg

11/12/2019

St. Pölten UAS Students Attend CERN Screening Week