Demo Data from EDBT 2026 / reviewers in the wild / expert
Chehai Wu
dblp:07/7796
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2012
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 2
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
1 paper |
Systems and software security · 38% Malware analysis · 38% Hardware security and side channels · 23% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Systems and software security › platform security
host security |
0.1 | 1 | 2012 | Data-Provenance Verification For Secure Hosts · IEEE Trans. Dependable Secur. Comput. 2012 |
Malware analysis
malware defense |
0.1 | 1 | 2012 | Data-Provenance Verification For Secure Hosts · IEEE Trans. Dependable Secur. Comput. 2012 |
Hardware security and side channels
trusted execution environments |
0.0 | 1 | 2012 | Data-Provenance Verification For Secure Hosts · IEEE Trans. Dependable Secur. Comput. 2012 |
Hardware security and side channels › trusted execution environments
trusted platform module |
0.0 | 1 | 2012 | Data-Provenance Verification For Secure Hosts · IEEE Trans. Dependable Secur. Comput. 2012 |
Methods — techniques the papers use, named apart from their topics
graph-based policy analysis · 0.1cryptographic provenance verification · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | Data-Provenance Verification For Secure HostsabstractMalicious software typically resides stealthily on a user's computer and interacts with the user's computing resources. Our goal in this work is to improve the trustworthiness of a host and its system data. Specifically, we provide a new mechanism that ensures the correct origin or provenance of critical system information and prevents adversaries from utilizing host resources. We define data-provenance integrity as the security property stating that the source where a piece of data is generated cannot be spoofed or tampered with. We describe a cryptographic provenance verification approach for ensuring system properties and system-data integrity at kernel-level. Its two concrete applications are demonstrated in the keystroke integrity verification and malicious traffic detection. Specifically, we first design and implement an efficient cryptographic protocol that enforces keystroke integrity by utilizing on-chip Trusted Computing Platform (TPM). The protocol prevents the forgery of fake key events by malware under reasonable assumptions. Then, we demonstrate our provenance verification approach by realizing a lightweight framework for restricting outbound malware traffic. This traffic-monitoring framework helps identify network activities of stealthy malware, and lends itself to a powerful personal firewall for examining all outbound traffic of a host that cannot be bypassed. Kui Xu 0002, Huijun Xiong, Chehai Wu, Deian Stefan, Danfeng Yao |
IEEE Trans. Dependable Secur. Comput. | 3 |
| 2009 | User-Assisted Host-Based Detection of Outbound Malware Traffic
Huijun Xiong, Prateek Malhotra, Deian Stefan, Chehai Wu, Danfeng Yao |
ICICS | 4 |