EDBT 2026 Demo / reviewers in the wild / expert
Josh Dafoe
dblp:332/2962
· DBLP profile ↗
4ranked-venue papers
2as first author
4since 2021 · last 2025
0000-0001-7303-7945ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 4 · 2 first-author · 4 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Hardware-Assisted Secure Decentralized Cloud Storage via Self-audit and Self-repair
Josh Dafoe, Niusen Chen, Bo Chen 0028 |
SecureComm (5) | 1 |
| 2024 | Poster: A Full-stack Secure Deletion Framework for Modern Computing DevicesabstractSecure data deletion is of critical importance for complying with retention regulations and safeguarding user privacy. In this work, we have proposed the first full-stack secure deletion design addressing both external storage and internal memory for secure deletion. Preliminary experimental results are provided to justify feasibility of the proposed design. Bo Chen 0028, Caleb Rother, Josh Dafoe |
CCS | 3 |
| 2024 | Enabling per-file data recovery from ransomware attacks via file system forensics and flash translation layer data extractionabstractAbstract Ransomware attacks are increasingly prevalent in recent years. Crypto-ransomware corrupts files on an infected device and demands a ransom to recover them. In computing devices using flash memory storage (e.g., SSD, MicroSD, etc.), existing designs recover the compromised data by extracting the entire raw flash memory image, restoring the entire external storage to a good prior state. This is feasible through taking advantage of the out-of-place updates feature implemented in the flash translation layer (FTL). However, due to the lack of “file” semantics in the FTL, such a solution does not allow a fine-grained data recovery in terms of files. Considering the file-centric nature of ransomware attacks, recovering the entire disk is mostly unnecessary. In particular, the user may just wish a speedy recovery of certain critical files after a ransomware attack. In this work, we have designed $$\textsf{FFRecovery}$$ FFRecovery , a new ransomware defense strategy that can support fine-grained per file data recovery after the ransomware attack. Our key idea is that, to restore a file corrupted by the ransomware, we (1) restore its file system metadata via file system forensics, and (2) extract its file data via raw data extraction from the FTL, and (3) assemble the corresponding file system metadata and the file data. Another essential aspect of $$\textsf{FFRecovery}$$ FFRecovery is that we add a garbage collection delay and freeze mechanism into the FTL so that no raw data will be lost prior to the recovery and, additionally, the raw data needed for the recovery can be always located. A prototype of $$\textsf{FFRecovery}$$ FFRecovery has been developed and our experiments using real-world ransomware samples demonstrate the effectiveness of $$\textsf{FFRecovery}$$ FFRecovery . We also demonstrate that $$\textsf{FFRecovery}$$ FFRecovery has negligible storage cost and performance impact. Josh Dafoe, Niusen Chen, Bo Chen 0028, Zhenlin Wang 0003 |
Cybersecur. | 1 |
| 2022 | Poster: Data Recovery from Ransomware Attacks via File System Forensics and Flash Translation Layer Data ExtractionabstractRansomware is increasingly prevalent in recent years. To defend against ransomware in computing devices using flash memory as external storage, existing designs extract the entire raw flash memory data to restore the external storage to a good state. However, they cannot allow a fine-grained recovery in terms of user files as raw flash memory data do not have the semantics of "files''. Niusen Chen, Josh Dafoe, Bo Chen 0028 |
CCS | 2 |