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Kyle E. Stewart

dblp:33/7545 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none

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

Computer networks · 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 · 50% Authentication and access control · 50%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Distributed systems · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Authentication and access control › trust management
decentralized trust
0.312017
Dynamic, Privacy-Preserving Decentralized Reputation Systems · IEEE Trans. Mob. Comput. 2017
Privacy and data protection › privacy-preserving computation
privacy-preserving reputation
0.312017
Dynamic, Privacy-Preserving Decentralized Reputation Systems · IEEE Trans. Mob. Comput. 2017
Distributed systems
distributed coordination
0.112017
Dynamic, Privacy-Preserving Decentralized Reputation Systems · IEEE Trans. Mob. Comput. 2017

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

simulation · 0.6cryptographic protocols · 0.6
YearPublicationVenuePosition
2017 Dynamic, Privacy-Preserving Decentralized Reputation Systems
abstract
Reputation systems provide an important basis for judging whether to interact with others in a networked system. Designing such systems is especially interesting in decentralized environments such as mobile ad-hoc networks, as there is no trusted authority to manage reputation feedback information. Such systems also come with significant privacy concerns, further complicating the issue. Researchers have proposed privacy-preserving decentralized reputation systems (PDRS) which ensure individual reputation information is not leaked. Instead, aggregate information is exposed. Unfortunately, in existing PDRS, when a party leaves the network, all of the reputation information they possess about other parties in the network leaves too. This is a significant problem when applying such systems to the kind of dynamic networks we see in mobile computing. In this article, we introduce dynamic, privacy-preserving reputation systems (Dyn-PDRS) to solve the problem. We enumerate the features that a reputation system must support in order to be considered a Dyn-PDRS. Furthermore, we present protocols to enable these features and describe how our protocols are composed to form a Dyn-PDRS. We present simulations of our ideas to understand how a Dyn-PDRS impacts information availability in the network, and report on an implementation of our protocols, including timing experiments.
Michael R. Clark, Kyle E. Stewart, Kenneth M. Hopkinson
IEEE Trans. Mob. Comput.2