Demo Data from VLDB 2026 / reviewers in the wild / expert
John S. Bucy
dblp:66/2700
· DBLP profile ↗
3ranked-venue papers
0as first author
0since 2021 · last 2010
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 2Databases, data management, data science and information retrieval · 2Security and privacy · 1
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.
| Computer architecture, parallel and distributed computing, and storage systems
2 papers |
Storage systems · 57% Electronic design automation · 43% | |
| Software engineering, system software, and programming languages
1 paper |
Operating systems · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Electronic design automation › hardware verification and test › functional verification › emulation
storage emulation |
0.0 | 1 | 2002 | Timing-Accurate Storage Emulation · FAST 2002 |
Operating systems › resource management
storage management |
0.0 | 1 | 2004 | A Framework for Building Unobtrusive Disk Maintenance Applications (Awarded Best Student Paper!) · FAST 2004 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | Storage-Based Intrusion DetectionabstractStorage-based intrusion detection consists of storage systems watching for and identifying data access patterns characteristic of system intrusions. Storage systems can spot several common intruder actions, such as adding backdoors, inserting Trojan horses, and tampering with audit logs. For example, examination of 18 real intrusion tools reveals that most (15) can be detected based on their changes to stored files. Further, an Intrusion Detection System (IDS) embedded in a storage device continues to operate even after client operating systems are compromised. We describe and evaluate a prototype storage IDS, built into a disk emulator, to demonstrate both feasibility and efficiency of storage-based intrusion detection. In particular, both the performance overhead (< 1%) and memory required (1.62MB for 13995 rules) are minimal. Adam G. Pennington, John Linwood Griffin, John S. Bucy, John D. Strunk, Gregory R. Ganger |
ACM Trans. Inf. Syst. Secur. | 3 |
| 2004 | A Framework for Building Unobtrusive Disk Maintenance Applications (Awarded Best Student Paper!)
Eno Thereska, Jiri Schindler, John S. Bucy, Brandon Salmon, Christopher R. Lumb, Gregory R. Ganger |
FAST | 3 |
| 2002 | Timing-Accurate Storage Emulation
John Linwood Griffin, Jiri Schindler, Steven W. Schlosser, John S. Bucy, Gregory R. Ganger |
FAST | 4 |