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Eric Hennigan

dblp:130/8256 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2013
—ORCID · none

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

Systems, architecture and hardware · 1Security and privacy · 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.

Network and information security
1 paper
Systems and software security · 87% Web and mobile security · 13%
Software engineering, system software, and programming languages
1 paper
Runtime systems and virtual machines · 100%

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

TopicWeightPapersLastEvidence papers
Systems and software security
information flow tracking
0.212013
Information flow tracking meets just-in-time compilation · ACM Trans. Archit. Code Optim. 2013
Systems and software security
javascript engine
0.212013
Information flow tracking meets just-in-time compilation · ACM Trans. Archit. Code Optim. 2013
Runtime systems and virtual machines › dynamic compilation
just-in-time compilation
0.212013
Information flow tracking meets just-in-time compilation · ACM Trans. Archit. Code Optim. 2013
Web and mobile security › web security
cross-site scripting
0.012013
Information flow tracking meets just-in-time compilation · ACM Trans. Archit. Code Optim. 2013

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

just-in-time compilation · 0.3information flow tracking · 0.3
YearPublicationVenuePosition
2013 CrowdFlow: Efficient Information Flow Security
Christoph Kerschbaumer, Eric Hennigan, Per Larsen, Stefan Brunthaler 0001, Michael Franz
ISC2
2013 Information flow tracking meets just-in-time compilation
abstract
Web applications are vulnerable to cross-site scripting attacks that enable data thefts. Information flow tracking in web browsers can prevent communication of sensitive data to unintended recipients and thereby stop such data thefts. Unfortunately, existing solutions have focused on incorporating information flow into browsers’ JavaScript interpreters, rather than just-in-time compilers, rendering the resulting performance noncompetitive. Few users will switch to a safer browser if it comes at the cost of significantly degrading web application performance. We present the first information flow tracking JavaScript engine that is based on a true just-in-time compiler, and that thereby outperforms all previous interpreter-based information flow tracking JavaScript engines by more than a factor of two. Our JIT-based engine (i) has the same coverage as previous interpreter- based solutions, (ii) requires reasonable implementation effort, and (iii) introduces new optimizations to achieve acceptable performance. When evaluated against three industry-standard JavaScript benchmark suites, there is still an average slowdown of 73% over engines that do not support information flow, but this is now well within the range that many users will find an acceptable price for obtaining substantially increased security.
Christoph Kerschbaumer, Eric Hennigan, Per Larsen, Stefan Brunthaler 0001, Michael Franz
ACM Trans. Archit. Code Optim.2