Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.

Xujiewen Wang

dblp:52/11077 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 2014
—ORCID · none

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

Software engineering, systems software and programming languages · 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.

Software engineering, system software, and programming languages
1 paper
Program analysis · 91% Operating systems · 9%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Program analysis
dynamic analysis
0.212014
Make it work, make it right, make it fast: building a platform-neutral whole-system dynamic binary analysis platform · ISSTA 2014
Program analysis › binary analysis
dynamic binary analysis
0.212014
Make it work, make it right, make it fast: building a platform-neutral whole-system dynamic binary analysis platform · ISSTA 2014
Program analysis › static analysis
taint analysis
0.212014
Make it work, make it right, make it fast: building a platform-neutral whole-system dynamic binary analysis platform · ISSTA 2014
Operating systems › virtualization
virtual machine introspection
0.112014
Make it work, make it right, make it fast: building a platform-neutral whole-system dynamic binary analysis platform · ISSTA 2014

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

just-in-time virtual machine introspection · 0.2instruction-level tainting · 0.2event-driven programming · 0.2
YearPublicationVenuePosition
2014 Make it work, make it right, make it fast: building a platform-neutral whole-system dynamic binary analysis platform
abstract
Dynamic binary analysis is a prevalent and indispensable technique in program analysis. While several dynamic binary analysis tools and frameworks have been proposed, all suffer from one or more of: prohibitive performance degradation, semantic gap between the analysis code and the program being analyzed, architecture/OS specificity, being user-mode only, lacking APIs, etc. We present DECAF, a virtual machine based, multi-target, whole-system dynamic binary analysis framework built on top of QEMU. DECAF provides Just-In-Time Virtual Machine Introspection combined with a novel TCG instruction-level tainting at bit granularity, backed by a plugin based, simple-to-use event driven programming interface. DECAF exercises fine control over the TCG instructions to accomplish on-the-fly optimizations. We present 3 platform-neutral plugins - Instruction Tracer, Keylogger Detector, and API Tracer, to demonstrate the ease of use and effectiveness of DECAF in writing cross-platform and system-wide analysis tools. Implementation of DECAF consists of 9550 lines of C++ code and 10270 lines of C code and we evaluate DECAF using CPU2006 SPEC benchmarks and show average overhead of 605% for system wide tainting and 12% for VMI.
Andrew Henderson, Aravind Prakash, Lok-Kwong Yan, Xunchao Hu, Xujiewen Wang, Rundong Zhou, Heng Yin 0001
ISSTA5