Demo Data from VLDB 2026 / reviewers in the wild / expert
Hans Stammler
dblp:393/9207
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0006-4770-4197ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 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.
| Software engineering, system software, and programming languages
1 paper |
Program verification · 50% Program analysis · 50% | |
| Network and information security
1 paper |
Blockchain and cryptocurrency security · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Blockchain and cryptocurrency security
smart contract security |
0.8 | 1 | 2024 | HighGuard: Cross-Chain Business Logic Monitoring of Smart Contracts · ASE 2024 |
Program analysis › dynamic analysis
runtime monitoring |
0.8 | 1 | 2024 | HighGuard: Cross-Chain Business Logic Monitoring of Smart Contracts · ASE 2024 |
Program verification › dynamic verification
runtime verification |
0.8 | 1 | 2024 | HighGuard: Cross-Chain Business Logic Monitoring of Smart Contracts · ASE 2024 |
Methods — techniques the papers use, named apart from their topics
formal specification · 1.5dynamic condition response graphs · 1.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | HighGuard: Cross-Chain Business Logic Monitoring of Smart ContractsabstractLogical flaws in smart contracts are often exploited, leading to significant financial losses. Our tool, HighGuard, detects transactions that violate business logic specifications of smart contracts. HighGuard employs dynamic condition response (DCR) graph models as formal specifications to verify contract execution against these models. It is capable of operating in a cross-chain environment for detecting business logic flaws across different blockchain platforms. We demonstrate HighGuard's effectiveness in identifying deviations from specified behaviors in smart contracts without requiring code instrumentation or incurring additional gas costs. By using precise specifications in the monitor, HighGuard achieves detection without false positives. Our evaluation, involving 54 exploits, confirms HighGuard's effectiveness in detecting business logic vulnerabilities. Mojtaba Eshghie, Cyrille Artho, Hans Stammler, Wolfgang Ahrendt, Thomas T. Hildebrandt, Gerardo Schneider |
ASE | 3 |