Location tracking technique for Regional ENF Classification Using ARIMA

Seohyun Kim, Ji Won Yoon

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Recently, a digital forensics technology has emerged that uses electrical network frequency (ENF) signals depending on the geographical environment for power supply. Through ENF data training, the technology finds the area where the signal occurred when any data was given. At this time, forecasts are usually made through interpolation based on trained data. In this paper, we proposed a location tracking method that does not require separate interpolation in the case of when trying to find the grid where the signal appears. The network frequency signal is collected from the streaming videos of the online multimedia services and the ENF signal is extracted using the secondary interpolation FFT (QIFFT) in the collected file. Subsequently, the extracted ENF signals are grouped into a constant size and trained through the Automatic Integrated Moving Average (ARIMA). Then, analyze the coefficients of regional ENF data to find meaningful sorting values in each region. This suggested how to track where online files are played and verified the accuracy of the predicted locations.

Original languageEnglish
Title of host publicationICTC 2020 - 11th International Conference on ICT Convergence
Subtitle of host publicationData, Network, and AI in the Age of Untact
PublisherIEEE Computer Society
Pages1321-1324
Number of pages4
ISBN (Electronic)9781728167589
DOIs
Publication statusPublished - 2020 Oct 21
Event11th International Conference on Information and Communication Technology Convergence, ICTC 2020 - Jeju Island, Korea, Republic of
Duration: 2020 Oct 212020 Oct 23

Publication series

NameInternational Conference on ICT Convergence
Volume2020-October
ISSN (Print)2162-1233
ISSN (Electronic)2162-1241

Conference

Conference11th International Conference on Information and Communication Technology Convergence, ICTC 2020
CountryKorea, Republic of
CityJeju Island
Period20/10/2120/10/23

Keywords

  • ARIMA
  • Data analysis
  • Data classification
  • ENF
  • Forecasting
  • SVM
  • Time series

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications

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