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Qing Zhang 0012

dblp:68/1429-12 · DBLP profile ↗
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3ranked-venue papers
2as first author
0since 2021 · last 2014
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1 · 1 first-authorComputer networks · 1Security and privacy · 1 · 1 first-author

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.

Databases, data mining, and information retrieval
1 paper
Web and social media mining · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Web and social media mining
web spam detection
0.212014
DSpin: Detecting Automatically Spun Content on the Web · NDSS 2014
Web and social media mining › web mining
web content analysis
0.112014
DSpin: Detecting Automatically Spun Content on the Web · NDSS 2014

Methods — techniques the papers use, named apart from their topics

text similarity · 0.2machine learning · 0.2
YearPublicationVenuePosition
2014 DSpin: Detecting Automatically Spun Content on the Web
Qing Zhang 0012, David Y. Wang, Geoffrey M. Voelker
NDSS1
2010 Neon: system support for derived data management
abstract
Modern organizations face increasingly complex information management requirements. A combination of commercial needs, legal liability and regulatory imperatives has created a patchwork of mandated policies. Among these, personally identifying customer records must be carefully access-controlled, sensitive files must be encrypted on mobile computers to guard against physical theft, and intellectual property must be protected from both exposure and "poisoning." However, enforcing such policies can be quite difficult in practice since users routinely share data over networks and derive new files from these inputs--incidentally laundering any policy restrictions. In this paper, we describe a virtual machine monitor system called Neon that transparently labels derived data using byte-level "tints" and tracks these labels end to end across commodity applications, operating systems and networks. Our goal with Neon is to explore the viability and utility of transparent information flow tracking within conventional networked systems when used in the manner in which they were intended. We demonstrate that this mechanism allows the enforcement of a variety of data management policies, including data-dependent confinement, mandatory I/O encryption, and intellectual property management.
Qing Zhang 0012, John McCullough, Justin Ma, Nabil Schear, Michael Vrable, Amin Vahdat, Alex C. Snoeren, Geoffrey M. Voelker, Stefan Savage
VEE1
2006 Glavlit: Preventing Exfiltration at Wire Speed
Nabil Schear, Carmelo Kintana, Qing Zhang 0012, Amin Vahdat
HotNets3