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Chehai Wu

dblp:07/7796 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Systems and software security › platform security
host security
0.112012
Data-Provenance Verification For Secure Hosts · IEEE Trans. Dependable Secur. Comput. 2012
Malware analysis
malware defense
0.112012
Data-Provenance Verification For Secure Hosts · IEEE Trans. Dependable Secur. Comput. 2012
Hardware security and side channels
trusted execution environments
0.012012
Data-Provenance Verification For Secure Hosts · IEEE Trans. Dependable Secur. Comput. 2012
Hardware security and side channels › trusted execution environments
trusted platform module
0.012012
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
YearPublicationVenuePosition
2012 Data-Provenance Verification For Secure Hosts
abstract
Malicious 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
ICICS4