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

Francis Fofie

dblp:129/5149 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 2012
—ORCID · none

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

Human-computer interaction and ubiquitous computing · 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.

Human-computer interaction and pervasive computing
1 paper
Ubiquitous computing and smart environments · 100%
Network and information security
1 paper
Privacy and data protection · 100%

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

TopicWeightPapersLastEvidence papers
Ubiquitous computing and smart environments › location-based services
location-based social networks
0.112012
Towards reliable spatial information in LBSNs · UbiComp 2012
Privacy and data protection
location privacy
0.012012
Towards reliable spatial information in LBSNs · UbiComp 2012
Privacy and data protection › location privacy
location proof
0.012012
Towards reliable spatial information in LBSNs · UbiComp 2012

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

simulation · 0.3location-proofs · 0.3
YearPublicationVenuePosition
2012 Towards reliable spatial information in LBSNs
abstract
The proliferation of Location-based Social Networks (LBSNs) has been rapid during the last year due to the number of novel services they can support. The main interaction between users in an LBSN is location sharing, which builds the spatial component of the system. The majority of the LBSNs make use of the notion of check-in, to enable users to volunteeringly share their whereabouts with their peers and the system. The flow of this spatial information is unidirectional and originates from the users' side. Given that currently there is no infrastructure in place for detecting fake checkins, the quality of the spatial information plane of an LBSN is solely based on the honesty of the users. In this paper, we seek to raise the awareness of the community for this problem, by identifying and discussing the effects of the presence of fake location information. We further present a preliminary design of a fake check-in detection scheme, based on location-proofs. Our initial simulation results show that if we do not consider the infrastructural constraints, location-proofs can form a viable technical solution.
Ke Zhang 0013, Wei Jeng, Francis Fofie, Konstantinos Pelechrinis, Prashant Krishnamurthy
UbiComp3