Demo Data from SIGIR 2026 / reviewers in the wild / expert
Raphael Isemann
dblp:232/2018
· DBLP profile ↗
4ranked-venue papers
1as first author
4since 2021 · last 2025
0009-0002-6224-9795ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 3 · 3 since 2021Software engineering, systems software and programming languages · 1 · 1 first-author · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Network and information security
4 papers |
Systems and software security · 64% Hardware security and side channels · 20% Privacy and data protection · 16% | |
| Software engineering, system software, and programming languages
2 papers |
Software testing · 36% Program analysis · 23% Concurrent programming · 23% | |
| Computer architecture, parallel and distributed computing, and storage systems
2 papers |
Electronic design automation · 90% Integrated circuit design · 10% |
Topics — the 16 heaviest of 16, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Privacy and data protection › information leakage
data leakage detection |
0.9 | 1 | 2025 | Phantom Trails: Practical Pre-Silicon Discovery of Transient Data Leaks · USENIX Security Symposium 2025 |
Systems and software security
operating system security |
0.9 | 1 | 2025 | Dynamic Detection of Vulnerable DMA Race Conditions · CCS 2025 |
Hardware security and side channels › microarchitectural attacks
transient execution attack |
0.9 | 1 | 2025 | Phantom Trails: Practical Pre-Silicon Discovery of Transient Data Leaks · USENIX Security Symposium 2025 |
Concurrent programming › concurrency bug detection
data race detection |
0.9 | 1 | 2025 | Dynamic Detection of Vulnerable DMA Race Conditions · CCS 2025 |
Program analysis
dynamic analysis |
0.9 | 1 | 2025 | Dynamic Detection of Vulnerable DMA Race Conditions · CCS 2025 |
Electronic design automation
hardware verification and test |
0.9 | 1 | 2025 | Phantom Trails: Practical Pre-Silicon Discovery of Transient Data Leaks · USENIX Security Symposium 2025 |
Electronic design automation › hardware verification and test › functional verification
pre-silicon verification |
0.9 | 1 | 2025 | Phantom Trails: Practical Pre-Silicon Discovery of Transient Data Leaks · USENIX Security Symposium 2025 |
Systems and software security › memory safety
memory error detection |
0.7 | 1 | 2023 | FloatZone: Accelerating Memory Error Detection using the Floating Point Unit · USENIX Security Symposium 2023 |
Systems and software security
memory safety |
0.7 | 1 | 2023 | FloatZone: Accelerating Memory Error Detection using the Floating Point Unit · USENIX Security Symposium 2023 |
Systems and software security › program analysis
undefined behavior detection |
0.7 | 1 | 2023 | Don't Look UB: Exposing Sanitizer-Eliding Compiler Optimizations · Proc. ACM Program. Lang. 2023 |
Systems and software security
vulnerability discovery |
0.7 | 1 | 2023 | Don't Look UB: Exposing Sanitizer-Eliding Compiler Optimizations · Proc. ACM Program. Lang. 2023 |
Compilers and program optimization › compiler correctness
compiler optimization correctness |
0.7 | 1 | 2023 | Don't Look UB: Exposing Sanitizer-Eliding Compiler Optimizations · Proc. ACM Program. Lang. 2023 |
Software testing
compiler testing |
0.7 | 1 | 2023 | Don't Look UB: Exposing Sanitizer-Eliding Compiler Optimizations · Proc. ACM Program. Lang. 2023 |
Software testing
differential testing |
0.7 | 1 | 2023 | Don't Look UB: Exposing Sanitizer-Eliding Compiler Optimizations · Proc. ACM Program. Lang. 2023 |
Hardware security and side channels › hardware attacks
DMA attacks |
0.3 | 1 | 2025 | Dynamic Detection of Vulnerable DMA Race Conditions · CCS 2025 |
Integrated circuit design › digital circuit design › arithmetic circuit design
floating-point unit |
0.2 | 1 | 2023 | FloatZone: Accelerating Memory Error Detection using the Floating Point Unit · USENIX Security Symposium 2023 |
Methods — techniques the papers use, named apart from their topics
taint tracking · 1.7information flow tracking · 1.7dynamic analysis · 1.7static analysis · 1.3fuzzing · 1.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Dynamic Detection of Vulnerable DMA Race ConditionsabstractThe drivers of modern operating systems use Direct Memory Access (DMA) to efficiently communicate with peripheral devices. Since the memory accessed by DMA is a shared resource between driver and device, it is a possible source of race conditions. Peripheral devices are also often untrusted, so these race conditions open up a new potential attack vector against a trusted OS kernel. In this paper, we present DMARacer, a dynamic detector called for these DMA-based race conditions in kernel code. DMARacer tracks memory accesses to DMA memory throughout the kernel's lifetime and analyses them for various indicators of race conditions. Additionally, upon detecting a race condition, DMARacer uses taint tracking to trace its impact and identify any potential vulnerabilities it may trigger, such as memory corruption or denial-of-service. We used DMARacer to search the drivers of the Linux kernel for DMA-based errors and find that DMA-based race conditions are a systemic issue in driver code. In total, DMARacer was able to detect 817 problematic memory accesses and 344 vulnerable operations in the scanned Linux kernel drivers. Brian Johannesmeyer, Raphael Isemann, Cristiano Giuffrida, Herbert Bos |
CCS | 2 |
| 2025 | Phantom Trails: Practical Pre-Silicon Discovery of Transient Data Leaks
Alvise de Faveri Tron, Raphael Isemann, Hany Ragab, Cristiano Giuffrida, Klaus von Gleissenthall, Herbert Bos |
USENIX Security Symposium | 2 |
| 2023 | FloatZone: Accelerating Memory Error Detection using the Floating Point Unit
Floris Gorter, Enrico Barberis, Raphael Isemann, Erik van der Kouwe, Cristiano Giuffrida, Herbert Bos |
USENIX Security Symposium | 3 |
| 2023 | Don't Look UB: Exposing Sanitizer-Eliding Compiler OptimizationsabstractSanitizers are widely used compiler features that detect undefined behavior and resulting vulnerabilities by injecting runtime checks into programs. For better performance, sanitizers are often used in conjunction with optimization passes. But doing so combines two compiler features with conflicting objectives. While sanitizers want to expose undefined behavior, optimizers often exploit these same properties for performance. In this paper, we show that this clash can have serious consequences: optimizations can remove sanitizer failures, thereby hiding the presence of bugs or even introducing new ones. We present LookUB, a differential-testing based framework for finding optimizer transformations that elide sanitizer failures. We used our method to find 17 such sanitizer-eliding optimizations in Clang. Next, we used static analysis and fuzzing to search for bugs in open-source projects that were previously hidden due to sanitizer-eliding optimizations. This led us to discover 20 new bugs in Linux Containers, libmpeg2, NTFS-3G, and WINE. Finally, we present an effective mitigation strategy based on a customization of the Clang optimizer with an overhead increase of 4%. Raphael Isemann, Cristiano Giuffrida, Herbert Bos, Erik van der Kouwe, Klaus von Gleissenthall |
Proc. ACM Program. Lang. | 1 |