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.
? Tutorial for this page

Kyle Kauffman

dblp:35/9582 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 2011
—ORCID · none

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

Databases, data management, data science and information retrieval · 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.

Computer networks
1 paper
Internet of things and sensor networks · 100%
Network and information security
1 paper
Network security · 100%

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

TopicWeightPapersLastEvidence papers
Internet of things and sensor networks › wireless sensor network
in-network aggregation
0.112011
General secure sensor aggregation in the presence of malicious nodes · ICDE 2011
Internet of things and sensor networks › wireless sensor network › data aggregation
secure data aggregation
0.112011
General secure sensor aggregation in the presence of malicious nodes · ICDE 2011
Network security › wireless network security
malicious node resilience
0.012011
General secure sensor aggregation in the presence of malicious nodes · ICDE 2011

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

secure multiparty computation · 0.2aggregation tree to aggregation list conversion · 0.2
YearPublicationVenuePosition
2011 General secure sensor aggregation in the presence of malicious nodes
abstract
Sensor networks have the potential to allow users to “query the physical world” by querying the sensor nodes for an aggregate result. However, a concern with such aggregation is that a few corrupt nodes in the network may manipulate the results that the querier sees. There has been a substantial amount of work on providing integrity for sensor network computations. However to the best of our knowledge, this prior work has one or more of the following two limitations: i) the methods only work for a specific aggregation function, or ii) the methods do not consider adversaries whose goal is to prevent the base station and the querier from receiving the result. In this paper we present the first scheme that provides general aggregation for sensor networks in the presence of malicious adversaries. The generality of the scheme results from the ability to securely evaluate any algorithm in the streaming model of computation. The main idea of this paper is to convert the commonly used aggregation tree into an aggregation list, and a process for doing this conversion is also presented. This result is an interesting and important first step towards achieving the realization of general secure querying of a sensor network.
Keith B. Frikken, Kyle Kauffman, Aaron Steele
ICDE2