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James Hester

dblp:179/8592 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2016
—ORCID · unresolved

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.

Network and information security
1 paper
Privacy and data protection · 100%
Software engineering, system software, and programming languages
1 paper
Program analysis · 100%

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

TopicWeightPapersLastEvidence papers
Privacy and data protection
privacy policy
0.212016
Toward a framework for detecting privacy policy violations in android application code · ICSE 2016
Program analysis › static analysis
information flow analysis
0.112016
Toward a framework for detecting privacy policy violations in android application code · ICSE 2016

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

ontology mapping · 0.5API method mapping · 0.5
YearPublicationVenuePosition
2016 Toward a framework for detecting privacy policy violations in android application code
abstract
Mobile applications frequently access sensitive personal information to meet user or business requirements. Because such information is sensitive in general, regulators increasingly require mobile-app developers to publish privacy policies that describe what information is collected. Furthermore, regulators have fined companies when these policies are inconsistent with the actual data practices of mobile apps. To help mobile-app developers check their privacy policies against their apps' code for consistency, we propose a semi-automated framework that consists of a policy terminology-API method map that links policy phrases to API methods that produce sensitive information, and information flow analysis to detect misalignments. We present an implementation of our framework based on a privacy-policy-phrase ontology and a collection of mappings from API methods to policy phrases. Our empirical evaluation on 477 top Android apps discovered 341 potential privacy policy violations.
Rocky Slavin, Xiaoyin Wang, Mitra Bokaei Hosseini, James Hester, Ram Krishnan, Jaspreet Bhatia, Travis D. Breaux, Jianwei Niu 0001
ICSE4