In this paper, we propose a forensic technique that is able to detect the application of a median filter to 1D data. The method relies on deterministic mathematical properties of the median filter, which lead to the identification of specific relationships among the sample values that cannot be found in the filtered sequences. Hence, their presence in the analyzed 1D sequence allows excluding the application of the median filter. Owing to its deterministic nature, the method ensures 0% false negatives, and although false positives (sequences not filtered classified as filtered) are theoretically possible, experimental results show that the false alarm rate is null for sufficiently long sequences. Furthermore, the proposed technique has the capability to locate with good precision a median filtered part of 1-D data and provides a good estimate of the window size used.

A Deterministic Approach to Detect Median Filtering in 1D Data / Pasquini, Cecilia; Boato, Giulia; Alajlan, Naif; De Natale, Francesco. - In: IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY. - ISSN 1556-6013. - 11:7(2016), pp. 1425-1437. [10.1109/TIFS.2016.2530636]

A Deterministic Approach to Detect Median Filtering in 1D Data

Pasquini, Cecilia;Boato, Giulia;De Natale, Francesco
2016-01-01

Abstract

In this paper, we propose a forensic technique that is able to detect the application of a median filter to 1D data. The method relies on deterministic mathematical properties of the median filter, which lead to the identification of specific relationships among the sample values that cannot be found in the filtered sequences. Hence, their presence in the analyzed 1D sequence allows excluding the application of the median filter. Owing to its deterministic nature, the method ensures 0% false negatives, and although false positives (sequences not filtered classified as filtered) are theoretically possible, experimental results show that the false alarm rate is null for sufficiently long sequences. Furthermore, the proposed technique has the capability to locate with good precision a median filtered part of 1-D data and provides a good estimate of the window size used.
2016
7
Pasquini, Cecilia; Boato, Giulia; Alajlan, Naif; De Natale, Francesco
A Deterministic Approach to Detect Median Filtering in 1D Data / Pasquini, Cecilia; Boato, Giulia; Alajlan, Naif; De Natale, Francesco. - In: IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY. - ISSN 1556-6013. - 11:7(2016), pp. 1425-1437. [10.1109/TIFS.2016.2530636]
File in questo prodotto:
File Dimensione Formato  
median_final.pdf

accesso aperto

Tipologia: Post-print referato (Refereed author’s manuscript)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 2.73 MB
Formato Adobe PDF
2.73 MB Adobe PDF Visualizza/Apri
07407398.pdf

Solo gestori archivio

Tipologia: Versione editoriale (Publisher’s layout)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 4.62 MB
Formato Adobe PDF
4.62 MB Adobe PDF   Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/161311
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 29
  • ???jsp.display-item.citation.isi??? 21
social impact