203 citations · 335 across the 16 of their papers we have counts for
18 papers
Just Testing, Move Along: Evasion of LLM-based System Log Interpretation by Prompt Injection
Max Landauer, Florian Skopik, Markus Wurzenberger +2
Large Language Models (LLMs) are increasingly integrated into Security Operations Center (SOC) workflows, where they support analysts in tasks such as the interpretation of system…
Beyond RAG for Cyber Threat Intelligence: A Systematic Evaluation of Graph-Based and Agentic Retrieval
Dzenan Hamzic, Florian Skopik, Max Landauer +2
Cyber threat intelligence (CTI) analysts must answer complex questions over large collections of narrative security reports. Retrieval-augmented generation (RAG) systems help langu…
CAM-LDS: Cyber Attack Manifestations for Automatic Interpretation of System Logs and Security Alerts
Max Landauer, Wolfgang Hotwagner, Thorina Boenke +2
Log data are essential for intrusion detection and forensic investigations. However, manual log analysis is tedious due to high data volumes, heterogeneous event formats, and unstr…
Resource-Aware Deployment Optimization for Collaborative Intrusion Detection in Layered Networks
André García Gómez, Ines Rieger, Wolfgang Hotwagner +4
Collaborative Intrusion Detection Systems (CIDS) are increasingly adopted to counter cyberattacks, as their collaborative nature enables them to adapt to diverse scenarios across h…
AlertBERT: A noise-robust alert grouping framework for simultaneous cyber attacks
Lukas Karner, Max Landauer, Markus Wurzenberger +1
Automated detection of cyber attacks is a critical capability to counteract the growing volume and sophistication of cyber attacks. However, the high numbers of security alerts iss…
AttackMate: Realistic Emulation and Automation of Cyber Attack Scenarios Across the Kill Chain
Max Landauer, Wolfgang Hotwagner, Thorina Boenke +2
Adversary emulation tools facilitate scripting and automated execution of cyber attack chains, thereby reducing costs and manual expert effort required for security testing, cyber…
StealthCup: Realistic, Multi-Stage, Evasion-Focused CTF for Benchmarking IDS
Manuel Kern, Dominik Steffan, Felix Schuster +5
Intrusion Detection Systems (IDS) are critical to defending enterprise and industrial control environments, yet evaluating their effectiveness under realistic conditions remains an…
System Log Parsing with Large Language Models: A Review
Viktor Beck, Max Landauer, Markus Wurzenberger +2
Log data provides crucial insights for tasks like monitoring, root cause analysis, and anomaly detection. Due to the vast volume of logs, automated log parsing is essential to tran…
DIN-CTS: Low-Complexity Depthwise-Inception Neural Network with Contrastive Training Strategy for Deepfake Speech Detection
Lam Pham, Dat Tran, Phat Lam +5
In this paper, we propose a deep neural network approach for deepfake speech detection (DSD) based on a lowcomplexity Depthwise-Inception Network (DIN) trained with a contrastive t…
Trace of the Times: Rootkit Detection through Temporal Anomalies in Kernel Activity
Max Landauer, Leonhard Alton, Martina Lindorfer +3
Kernel rootkits provide adversaries with permanent high-privileged access to compromised systems and are often a key element of sophisticated attack chains. At the same time, they…
Towards Improving IDS Using CTF Events
Manuel Kern, Florian Skopik, Max Landauer +1
In cybersecurity, Intrusion Detection Systems (IDS) serve as a vital defensive layer against adversarial threats. Accurate benchmarking is critical to evaluate and improve IDS effe…
Red Team Redemption: A Structured Comparison of Open-Source Tools for Adversary Emulation
Max Landauer, Klaus Mayer, Florian Skopik +2
Red teams simulate adversaries and conduct sophisticated attacks against defenders without informing them about used tactics in advance. These interactive cyber exercises are highl…
A Critical Review of Common Log Data Sets Used for Evaluation of Sequence-based Anomaly Detection Techniques
Max Landauer, Florian Skopik, Markus Wurzenberger
Log data store event execution patterns that correspond to underlying workflows of systems or applications. While most logs are informative, log data also include artifacts that in…
Introducing a New Alert Data Set for Multi-Step Attack Analysis
Max Landauer, Florian Skopik, Markus Wurzenberger
Intrusion detection systems (IDS) reinforce cyber defense by autonomously monitoring various data sources for traces of attacks. However, IDSs are also infamous for frequently rais…
Deep Learning for Anomaly Detection in Log Data: A Survey
Max Landauer, Sebastian Onder, Florian Skopik +1
Automatic log file analysis enables early detection of relevant incidents such as system failures. In particular, self-learning anomaly detection techniques capture patterns in log…
Maintainable Log Datasets for Evaluation of Intrusion Detection Systems
Max Landauer, Florian Skopik, Maximilian Frank +3
Intrusion detection systems (IDS) monitor system logs and network traffic to recognize malicious activities in computer networks. Evaluating and comparing IDSs with respect to thei…
Applying High-Performance Bioinformatics Tools for Outlier Detection in Log Data
Markus Wurzenberger, Florian Skopik, Roman Fiedler +1
Most of today's security solutions, such as security information and event management (SIEM) and signature based IDS, require the operator to evaluate potential attack vectors and…
Towards a Layered Architectural View for Security Analysis in SCADA Systems
Zhendong Ma, Paul Smith, Florian Skopik
Supervisory Control and Data Acquisition (SCADA) systems support and control the operation of many critical infrastructures that our society depend on, such as power grids. Since S…