About
My name is Tom Ganz and I am currently living in London and working as a security engineer @Amazon. I am interested in computer security and machine learning. Feel free to send me an E-Mail using my PGP key.
Academical Merits
- PhD Machine Learning and IT Security @Technical University of Berlin
- Msc. Computer Science @University of Applied Sciences Karlsruhe
- Bsc. Applied Computer Science @Corporate State University Karlsruhe
Patents
- Directed fuzzing for vulnerability detection 2 US20240184892A1
- Directed fuzzing for vulnerability detection 1 US20240184891A1
Publications
- Tom Ganz: PhD Thesis: Software Defect Localization Using Explainable Deep Learning (TU Berlin 2024)
- Felix Weißberg, Jonas Möller, Tom Ganz, Erik Imgrund, Lukas Pirch, Lukas Seidel, Moritz Schloegel, Thorsten Eisenhofer and Konrad Rieck: SoK: Where to Fuzz? Assessing Target Selection Methods in Directed Fuzzing (ASIACCS 2024)
- Tom Ganz, Erik Imgrund, Martin Härterich, Konrad Rieck: PAVUDI: Patch-based Vulnerability Discovery using Machine Learning (ACSAC 2023)
- Erik Imgrund, Tom Ganz, Martin Härterich, Lukas Pirch, Niklas Risse, Konrad Rieck: Broken Promises: Measuring Confounding Effects in Learning-based Vulnerability Discovery (CCS AISec 2023)
- Tom Ganz, Erik Imgrund, Martin Härterich, Konrad Rieck: CodeGraphSMOTE - Data Augmentation for Vulnerability Discovery (DBSEC 2023)
- Tom Ganz, Philipp Rall, Martin Härterich, Konrad Rieck: Hunting for Truth: Analyzing Explanation Methods in Learning-based Vulnerability Discovery (Euro S&P 2023)
- Tom Ganz, Inaam Ashraf, Martin Härterich, Konrad Rieck: Detecting Backdoors in Collaboration Graphs of Software Repositories (CODASPY 2023)
- Tom Ganz, Martin Härterich, Alexander Warnecke, Konrad Rieck: Explaining Graph Neural Networks for Vulnerability Discovery (CCS AISec 2021)
Academic Services
- Reviews for IEEE Access
- Subreviews for S&P
- Reviews for CCS AISec
Other Stuff
- Master Thesis: Assessing and selecting Eps for differentially private Federated Learning with Inference Attacks
- ML powered Malware Scanner
- ML powered Binary analysis
- Autonomous System Spam Monitor
- Security Paper Aggregator
- AI-supported flash cards
- Device Fingerprinting
- Hash Collisions in Java
- My (inactive) Hackerrank
- Cruzzer
Awards
- AISec CCS Best Paper Award 2021
Invited Talks
- @Memgraph Graph-based vulnerability discovery 2024
- Cooperate State University Karlsruhe 2022: Lecturer for Compiler Engineering
- SAP Conference on Machine Learning 2022: Explainable Fuzzing
- SAP Conference on Machine Learning 2022: Graph Autoencoders - on the Hunt for Malicious Commits
- SAP Development Kick-Off Meeting: Automated Analysis of Source Code Repositories using Machine Learning
- SAP Conference on Machine Learning 2021: Intelligently Protect the Enterprise - What machines may learn about graphs in your software
- SAP Security Expert Summit 2021: Intelligently Protect the Enterprise - What machines may learn about graphs in your software
Check out my LinkedIn to see my current CV.