Overview of the ImageCLEFsecurity 2019: File Forgery Detection Tasks

Karampidis, Konstantinos and Vasillopoulos, Nikos and Cuevas Rodríguez, Carlos and Blanco Adán, Carlos Roberto del and Kavallieratou, Ergina and García Santos, Narciso (2019). Overview of the ImageCLEFsecurity 2019: File Forgery Detection Tasks. In: "Conference and Labs of the Evaluation Forum (CLEF 2019)", 09/09/2019 - 12/09/2019, Lugano, Switzerland. pp. 1-9.

Description

Title: Overview of the ImageCLEFsecurity 2019: File Forgery Detection Tasks
Author/s:
  • Karampidis, Konstantinos
  • Vasillopoulos, Nikos
  • Cuevas Rodríguez, Carlos
  • Blanco Adán, Carlos Roberto del
  • Kavallieratou, Ergina
  • García Santos, Narciso
Item Type: Presentation at Congress or Conference (Article)
Event Title: Conference and Labs of the Evaluation Forum (CLEF 2019)
Event Dates: 09/09/2019 - 12/09/2019
Event Location: Lugano, Switzerland
Title of Book: Conference and Labs of the Evaluation Forum (CLEF 2019)
Date: 2019
Subjects:
Freetext Keywords: File Forgery Detection; Digital Forensics; Forged Image; Stego Image
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Señales, Sistemas y Radiocomunicaciones
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

The File Forgery Detection tasks is in its first edition, in 2019. This year, it is composed by three subtasks: a) Forged file discovery, b) Stego image discovery and c) Secret message discovery. The data set contained 6,400 images and pdf files, divided into 3 sets. There were 61 participants and the majority of them participated in all the subtasks. This highlights the major concern the scientific community shows for security issues and the importance of each subtask. Submissions varied from a) 8, b) 31 and c) 14 submissions for each subtask, respectively. Although the datasets were small, most of the participants used deep learning techniques, especially in subtasks 2 & 3. The results obtained in subtask 3-which was the most difficult one-showed that there is room for improvement, as more advanced techniques are needed to achieve better results. Deep learning techniques adopted by many researchers is a preamble in that direction, and proved that they may provide a promising steganalysis tool to a digital forensics examiner.

Funding Projects

TypeCodeAcronymLeaderTitle
Government of SpainTEC2016-75981UnspecifiedUnspecifiedUnspecified

More information

Item ID: 65257
DC Identifier: http://oa.upm.es/65257/
OAI Identifier: oai:oa.upm.es:65257
Deposited by: Memoria Investigacion
Deposited on: 24 Apr 2021 07:57
Last Modified: 24 Apr 2021 07:57
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