• Corpus ID: 243986099

Detecting Fake Points of Interest from Location Data

@article{Bashir2021DetectingFP,
  title={Detecting Fake Points of Interest from Location Data},
  author={Syed Raza Bashir and Vojislav B. Mi{\vs}i{\'c}},
  journal={ArXiv},
  year={2021},
  volume={abs/2111.06003}
}
The pervasiveness of GPS-enabled mobile devices and the widespread use of location-based services have resulted in the generation of massive amounts of geo-tagged data. In recent times, the data analysis now has access to more sources, including reviews, news, and images, which also raises questions about the reliability of Point-of-Interest (POI) data sources. While previous research attempted to detect fake POI data through various security mechanisms, the current work attempts to capture the… 

Figures and Tables from this paper

References

SHOWING 1-10 OF 37 REFERENCES
How do they find us? A study of geolocation tracking techniques of malicious web sites
TLDR
An overview of the range of geolocation detection techniques which could potentially be used to estimate the location of a visiting user and perform geolocated cloaking attacks is provided.
Geolocation and Assisted GPS
TLDR
It is argued that assisted-GPS technology offers superior accuracy, availability, and coverage at a reasonable cost.
The Art and Craft of Fraudulent App Promotion in Google Play
TLDR
A Google site vulnerability is reported that enabled us to infer the mobile device models used to post more than 198 million reviews in Google Play, including 9,942 fake reviews.
Modeling future spread of infections via mobile geolocation data and population dynamics. An application to COVID-19 in Brazil
TLDR
This work investigates the most probable spreading patterns of the COVID-19 within states of Brazil, based on millions of anonymized mobile visits data, to help public administrators in action plans and resources allocation, whilst studying how mobile geolocation data may be employed as a measure of population mobility during an epidemic.
Geolocation of data in the cloud
TLDR
This work introduces and analyzes a general framework for authentically binding data to a location while providing strong assurances against cloud storage providers that (either accidentally or maliciously) attempt to re-locate cloud data, called constraint-based data geolocation (CBDG).
Pinning Down Abuse on Google Maps
TLDR
A new form of blackhat search engine optimization that targets local listing services like Google Maps is investigated, and how miscreants generated a profit from traffic that necessitates physical proximity to the victim is explored.
A cloud-edge based data security architecture for sharing and analysing cyber threat information
TLDR
A five-level trust model for a cloud-edge based data sharing infrastructure that allows the confidential sharing of CTI for analysis between collaborators and is designed to satisfy the broadest range of requirements for confidential CTI data sharing is proposed.
SMOTE: Synthetic Minority Over-sampling Technique
TLDR
A combination of the method of oversampling the minority (abnormal) class and under-sampling the majority class can achieve better classifier performance (in ROC space) and a combination of these methods and the area under the Receiver Operating Characteristic curve (AUC) and the ROC convex hull strategy is evaluated.
Use of K-Nearest Neighbor classifier for intrusion detection
TLDR
A new approach, based on the k-Nearest Neighbor (kNN) classifier, is used to classify program behavior as normal or intrusive, and seems to offer some computational advantages over those that seek to characterize program behavior with short sequences of system calls and generate individual program profiles.
Support vector machine classification and validation of cancer tissue samples using microarray expression data
TLDR
A new method to analyse tissue samples using support vector machines for mis-labeled or questionable tissue results and shows that other machine learning methods also perform comparably to the SVM on many of those datasets.
...
1
2
3
4
...