Mario is enthusiastic about cyber security and data science and is currently working on methods that spot hackers in cloud-native environments. He is an experienced CTF player and previously worked on predicting performance events from large-scale time series data during his Computer Science studies at the Johannes Kepler University Linz.
Joining the Dynatrace team in February 2020 as a Data Scientist, he is now highly motivated to work on the interface between the application security needs that we see in the cloud-native space here at Dynatrace and enrich and contribute to the ongoing efforts within the academic research community.
As one of our first PhD students in the research lab, he will set a specific focus on detecting multi-step attacks in cloud-native environments with adaptive cyber deception.
Authored publications
Benchmarking Function Hook Latency in Cloud-Native Environments
Researchers and engineers are increasingly adopting cloud-native technologies for application development and performance evaluation. While this has improved the reproducibility of benchmarks in the cloud, the complexity of cloud-native environments makes it difficult to run benchmarks reliably. Cloud-native applications are often instrumented or a...
Mario Kahlhofer, Patrick Kern, Sören Henning, Stefan Rass
| Softwaretechnik-Trends | 2023
Context-Aware Security Intelligence of Vulnerability Scanners in Cloud-native Environments
Even as black-box web vulnerability scanners help identify security vulnerabilities of web applications, they still have problems with false alarms, as they lack insight into the context of applications. Without this supplemental information like the topology of the underlying application or the runtime, scanners cannot precisely assess a threat’s ...
Simon Ammer, Jens Krösche, Markus Gierlinger, Mario Kahlhofer
| ADAPTIVE 2022, The Fourteenth International Conference on Adaptive and Self-Adaptive Systems and Applications | 2022
An Approach for Ranking Feature-based Clustering Methods and its Application in Multi-System Infrastructure Monitoring
Companies need to collect and analyze time series data to continuously monitor the behavior of software systems during operation, which can in turn be used for performance monitoring, anomaly detection or identifying problems after system crashes. However, gaining insights into common data patterns in time series is challenging, in particular, when...
Andreas Schörgenhumer; Thomas Natschläger; Paul Grünbacher; Mario Kahlhofer; Peter Chalupar; Hanspeter Mössenböck
| 2021 47th Euromicro Conference on Software Engineering and Advanced Applications (SEAA) | 2021
Towards Reconstructing Multi-Step Cyber Attacks in Modern Cloud Environments with Tripwires
Rapidly-changing cloud environments that consist of heavily interconnected components are difficult to secure. Existing solutions often try to correlate many weak indicators to identify and reconstruct multi-step cyber attacks. The lack of a true, causal link between most of these indicators still leaves administrators with a lot of false-positives...
Mario Kahlhofer, Michael Hölzl, Andreas Berger
| Proceedings of the European Interdisciplinary Cybersecurity Conference (EICC) | 2021
Keep exploring ...
... and find out even more about engineering at Dynatrace.
