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Multimedia Forensics

Information Theoretical Limit of Operation Forensics


Abstract—While more and more forensic techniques have been proposed to detect the processing history of multimedia content, one starts to wonder if there exists a fundamental limit on the capability of forensics. In other words, besides keeping on searching what investigators can do, it is also important to find out the limit of their capability and what they cannot do. In this work, we explore the fundamental limit of operation forensics by proposing an information theoretical framework.

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Authors:
Matthew C. Stamm
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23 February 2016 - 1:44pm
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[1] Matthew C. Stamm, "Information Theoretical Limit of Operation Forensics", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/147. Accessed: Aug. 20, 2017.
@article{147-15,
url = {http://sigport.org/147},
author = {Matthew C. Stamm },
publisher = {IEEE SigPort},
title = {Information Theoretical Limit of Operation Forensics},
year = {2015} }
TY - EJOUR
T1 - Information Theoretical Limit of Operation Forensics
AU - Matthew C. Stamm
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/147
ER -
Matthew C. Stamm. (2015). Information Theoretical Limit of Operation Forensics. IEEE SigPort. http://sigport.org/147
Matthew C. Stamm, 2015. Information Theoretical Limit of Operation Forensics. Available at: http://sigport.org/147.
Matthew C. Stamm. (2015). "Information Theoretical Limit of Operation Forensics." Web.
1. Matthew C. Stamm. Information Theoretical Limit of Operation Forensics [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/147

Compressive Sensing Forensics


Abstract—Identifying a signal’s origin and how it was acquired is an important forensic problem. While forensic techniques currently exist to determine a signal’s acquisition history, these techniques do not account for the possibility that a signal could be compressively sensed. This is an important problem since compressive sensing techniques have seen increased popularity in recent years. In this paper, we propose a set of forensic techniques to identify signals acquired by compressive sensing. We do this by first identifying the fingerprints left in a signal by compressive sensing.

double_AQ.pdf

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Authors:
Matthew C. Stamm
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23 February 2016 - 1:43pm
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[1] Matthew C. Stamm, "Compressive Sensing Forensics", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/146. Accessed: Aug. 20, 2017.
@article{146-15,
url = {http://sigport.org/146},
author = {Matthew C. Stamm },
publisher = {IEEE SigPort},
title = {Compressive Sensing Forensics},
year = {2015} }
TY - EJOUR
T1 - Compressive Sensing Forensics
AU - Matthew C. Stamm
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/146
ER -
Matthew C. Stamm. (2015). Compressive Sensing Forensics. IEEE SigPort. http://sigport.org/146
Matthew C. Stamm, 2015. Compressive Sensing Forensics. Available at: http://sigport.org/146.
Matthew C. Stamm. (2015). "Compressive Sensing Forensics." Web.
1. Matthew C. Stamm. Compressive Sensing Forensics [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/146

SP Cup 2016 Purdue Report


We report a multi-harmonic histogram method for extracting and analyzing electric network frequency (ENF) signals to identify power grids. Given a voltage-time measurement of a power grid with a base frequency f0, we compute the ENF signals at multiple harmonic locations f_0 and extract (i) a histogram of the magnitudes of the ENF; (ii) a histogram of the signal power and noise power surrounding the ENF; (iii) a histogram of the signal-to noise-ratio (SNR) of the ENF.

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[1] , "SP Cup 2016 Purdue Report", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1147. Accessed: Aug. 20, 2017.
@article{1147-16,
url = {http://sigport.org/1147},
author = { },
publisher = {IEEE SigPort},
title = {SP Cup 2016 Purdue Report},
year = {2016} }
TY - EJOUR
T1 - SP Cup 2016 Purdue Report
AU -
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1147
ER -
. (2016). SP Cup 2016 Purdue Report. IEEE SigPort. http://sigport.org/1147
, 2016. SP Cup 2016 Purdue Report. Available at: http://sigport.org/1147.
. (2016). "SP Cup 2016 Purdue Report." Web.
1. . SP Cup 2016 Purdue Report [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1147

IITH SPCUP Project Report


We present two contributions in this work: i)Novel electric network frequency (ENF) classification algorithm, and ii)Circuit for measuring power signals from the power grid.We first propose a novel ENF signal estimation algorithm.This algorithm explicitly makes use of the harmonic information present in the signal and estimates the nominal frequency based on the most reliable harmonic. The ENF signal is estimated from the most reliable harmonic by employing a Gaussian weighting window to mitigate the effects of noise. We

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Authors:
Chandra Prakash Konkimalla, Sristi Ram Dyuthi, Sukrutha Anumandla, Harshitha Machiraju, Pranavi Bajjuri, Wasim Akram, Pankaj Kumar, Ajinkya Mulay, Sushma Siddamsetty, Asvini R,Francis K. J. , Sumohana S. Channappayya
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16 June 2016 - 12:42am
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[1] Chandra Prakash Konkimalla, Sristi Ram Dyuthi, Sukrutha Anumandla, Harshitha Machiraju, Pranavi Bajjuri, Wasim Akram, Pankaj Kumar, Ajinkya Mulay, Sushma Siddamsetty, Asvini R,Francis K. J. , Sumohana S. Channappayya, "IITH SPCUP Project Report", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1123. Accessed: Aug. 20, 2017.
@article{1123-16,
url = {http://sigport.org/1123},
author = {Chandra Prakash Konkimalla; Sristi Ram Dyuthi; Sukrutha Anumandla; Harshitha Machiraju; Pranavi Bajjuri; Wasim Akram; Pankaj Kumar; Ajinkya Mulay; Sushma Siddamsetty; Asvini R;Francis K. J. ; Sumohana S. Channappayya },
publisher = {IEEE SigPort},
title = {IITH SPCUP Project Report},
year = {2016} }
TY - EJOUR
T1 - IITH SPCUP Project Report
AU - Chandra Prakash Konkimalla; Sristi Ram Dyuthi; Sukrutha Anumandla; Harshitha Machiraju; Pranavi Bajjuri; Wasim Akram; Pankaj Kumar; Ajinkya Mulay; Sushma Siddamsetty; Asvini R;Francis K. J. ; Sumohana S. Channappayya
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1123
ER -
Chandra Prakash Konkimalla, Sristi Ram Dyuthi, Sukrutha Anumandla, Harshitha Machiraju, Pranavi Bajjuri, Wasim Akram, Pankaj Kumar, Ajinkya Mulay, Sushma Siddamsetty, Asvini R,Francis K. J. , Sumohana S. Channappayya. (2016). IITH SPCUP Project Report. IEEE SigPort. http://sigport.org/1123
Chandra Prakash Konkimalla, Sristi Ram Dyuthi, Sukrutha Anumandla, Harshitha Machiraju, Pranavi Bajjuri, Wasim Akram, Pankaj Kumar, Ajinkya Mulay, Sushma Siddamsetty, Asvini R,Francis K. J. , Sumohana S. Channappayya, 2016. IITH SPCUP Project Report. Available at: http://sigport.org/1123.
Chandra Prakash Konkimalla, Sristi Ram Dyuthi, Sukrutha Anumandla, Harshitha Machiraju, Pranavi Bajjuri, Wasim Akram, Pankaj Kumar, Ajinkya Mulay, Sushma Siddamsetty, Asvini R,Francis K. J. , Sumohana S. Channappayya. (2016). "IITH SPCUP Project Report." Web.
1. Chandra Prakash Konkimalla, Sristi Ram Dyuthi, Sukrutha Anumandla, Harshitha Machiraju, Pranavi Bajjuri, Wasim Akram, Pankaj Kumar, Ajinkya Mulay, Sushma Siddamsetty, Asvini R,Francis K. J. , Sumohana S. Channappayya. IITH SPCUP Project Report [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1123

SP Cup technical report: Team UNStoppable, Serbia


The Electric network frequency (ENF) signal is a unique signal for different parts of the world. It is captured by electric devices, and can be used in authentication and automatic synchronization of digital media recordings. In this paper we propose an algorithm to extract ENF from power and audio recordings, and use ENF criterion to identify the region-of-recording. We also propose a design of a circuit to record the electrical power grid.

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Authors:
Milivoje Knežević, Željana Šarić, Tijana Zrnić, Anastazia Žunić, Tijana Delić
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13 June 2016 - 4:18pm
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[1] Milivoje Knežević, Željana Šarić, Tijana Zrnić, Anastazia Žunić, Tijana Delić, "SP Cup technical report: Team UNStoppable, Serbia", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1116. Accessed: Aug. 20, 2017.
@article{1116-16,
url = {http://sigport.org/1116},
author = {Milivoje Knežević; Željana Šarić; Tijana Zrnić; Anastazia Žunić; Tijana Delić },
publisher = {IEEE SigPort},
title = {SP Cup technical report: Team UNStoppable, Serbia},
year = {2016} }
TY - EJOUR
T1 - SP Cup technical report: Team UNStoppable, Serbia
AU - Milivoje Knežević; Željana Šarić; Tijana Zrnić; Anastazia Žunić; Tijana Delić
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1116
ER -
Milivoje Knežević, Željana Šarić, Tijana Zrnić, Anastazia Žunić, Tijana Delić. (2016). SP Cup technical report: Team UNStoppable, Serbia. IEEE SigPort. http://sigport.org/1116
Milivoje Knežević, Željana Šarić, Tijana Zrnić, Anastazia Žunić, Tijana Delić, 2016. SP Cup technical report: Team UNStoppable, Serbia. Available at: http://sigport.org/1116.
Milivoje Knežević, Željana Šarić, Tijana Zrnić, Anastazia Žunić, Tijana Delić. (2016). "SP Cup technical report: Team UNStoppable, Serbia." Web.
1. Milivoje Knežević, Željana Šarić, Tijana Zrnić, Anastazia Žunić, Tijana Delić. SP Cup technical report: Team UNStoppable, Serbia [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1116

Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics


Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics

In this paper, we present Discriminant Correlation Analysis (DCA), a feature level fusion technique that incorporates the class associations in correlation analysis of the feature sets. DCA performs an effective feature fusion by maximizing the pair-wise correlations across the two feature sets, and at the same time, eliminating the between-class correlations and restricting the correlations to be within classes.

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Authors:
Mohammad Haghighat, Mohamed Abdel-Mottaleb, Wadee Alhalabi
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16 July 2016 - 11:13pm
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[1] Mohammad Haghighat, Mohamed Abdel-Mottaleb, Wadee Alhalabi, "Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/828. Accessed: Aug. 20, 2017.
@article{828-16,
url = {http://sigport.org/828},
author = {Mohammad Haghighat; Mohamed Abdel-Mottaleb; Wadee Alhalabi },
publisher = {IEEE SigPort},
title = {Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics},
year = {2016} }
TY - EJOUR
T1 - Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics
AU - Mohammad Haghighat; Mohamed Abdel-Mottaleb; Wadee Alhalabi
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/828
ER -
Mohammad Haghighat, Mohamed Abdel-Mottaleb, Wadee Alhalabi. (2016). Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics. IEEE SigPort. http://sigport.org/828
Mohammad Haghighat, Mohamed Abdel-Mottaleb, Wadee Alhalabi, 2016. Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics. Available at: http://sigport.org/828.
Mohammad Haghighat, Mohamed Abdel-Mottaleb, Wadee Alhalabi. (2016). "Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics." Web.
1. Mohammad Haghighat, Mohamed Abdel-Mottaleb, Wadee Alhalabi. Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/828

AAC Encoding Detection and Bitrate Estimation using a Convolutional Neural Network

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Daniel Seichter, Luca Cuccovillo, Patrick Aichroth
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15 March 2016 - 1:20pm
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[1] Daniel Seichter, Luca Cuccovillo, Patrick Aichroth, "AAC Encoding Detection and Bitrate Estimation using a Convolutional Neural Network", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/694. Accessed: Aug. 20, 2017.
@article{694-16,
url = {http://sigport.org/694},
author = {Daniel Seichter; Luca Cuccovillo; Patrick Aichroth },
publisher = {IEEE SigPort},
title = {AAC Encoding Detection and Bitrate Estimation using a Convolutional Neural Network},
year = {2016} }
TY - EJOUR
T1 - AAC Encoding Detection and Bitrate Estimation using a Convolutional Neural Network
AU - Daniel Seichter; Luca Cuccovillo; Patrick Aichroth
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/694
ER -
Daniel Seichter, Luca Cuccovillo, Patrick Aichroth. (2016). AAC Encoding Detection and Bitrate Estimation using a Convolutional Neural Network. IEEE SigPort. http://sigport.org/694
Daniel Seichter, Luca Cuccovillo, Patrick Aichroth, 2016. AAC Encoding Detection and Bitrate Estimation using a Convolutional Neural Network. Available at: http://sigport.org/694.
Daniel Seichter, Luca Cuccovillo, Patrick Aichroth. (2016). "AAC Encoding Detection and Bitrate Estimation using a Convolutional Neural Network." Web.
1. Daniel Seichter, Luca Cuccovillo, Patrick Aichroth. AAC Encoding Detection and Bitrate Estimation using a Convolutional Neural Network [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/694

Open-set Microphone Classification via Blind Channel Analysis

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Luca Cuccovillo, Patrick Aichroth
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15 March 2016 - 1:06pm
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[1] Luca Cuccovillo, Patrick Aichroth, "Open-set Microphone Classification via Blind Channel Analysis", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/693. Accessed: Aug. 20, 2017.
@article{693-16,
url = {http://sigport.org/693},
author = {Luca Cuccovillo; Patrick Aichroth },
publisher = {IEEE SigPort},
title = {Open-set Microphone Classification via Blind Channel Analysis},
year = {2016} }
TY - EJOUR
T1 - Open-set Microphone Classification via Blind Channel Analysis
AU - Luca Cuccovillo; Patrick Aichroth
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/693
ER -
Luca Cuccovillo, Patrick Aichroth. (2016). Open-set Microphone Classification via Blind Channel Analysis. IEEE SigPort. http://sigport.org/693
Luca Cuccovillo, Patrick Aichroth, 2016. Open-set Microphone Classification via Blind Channel Analysis. Available at: http://sigport.org/693.
Luca Cuccovillo, Patrick Aichroth. (2016). "Open-set Microphone Classification via Blind Channel Analysis." Web.
1. Luca Cuccovillo, Patrick Aichroth. Open-set Microphone Classification via Blind Channel Analysis [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/693

Flicker Forensics for Camcorder Piracy


A. Hajj-Ahmad, S. Baudry, B. Chupeau, G. Do¨err, and M. Wu, “Flicker forensics for camcorder piracy,” submitted for journal publication.

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Authors:
Adi Hajj-Ahmad, Severine Baudry, Bertrand Chupeau, Gwenael Doerr, and Min Wu
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10 March 2016 - 9:23pm
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[1] Adi Hajj-Ahmad, Severine Baudry, Bertrand Chupeau, Gwenael Doerr, and Min Wu, "Flicker Forensics for Camcorder Piracy", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/610. Accessed: Aug. 20, 2017.
@article{610-16,
url = {http://sigport.org/610},
author = {Adi Hajj-Ahmad; Severine Baudry; Bertrand Chupeau; Gwenael Doerr; and Min Wu },
publisher = {IEEE SigPort},
title = {Flicker Forensics for Camcorder Piracy},
year = {2016} }
TY - EJOUR
T1 - Flicker Forensics for Camcorder Piracy
AU - Adi Hajj-Ahmad; Severine Baudry; Bertrand Chupeau; Gwenael Doerr; and Min Wu
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/610
ER -
Adi Hajj-Ahmad, Severine Baudry, Bertrand Chupeau, Gwenael Doerr, and Min Wu. (2016). Flicker Forensics for Camcorder Piracy. IEEE SigPort. http://sigport.org/610
Adi Hajj-Ahmad, Severine Baudry, Bertrand Chupeau, Gwenael Doerr, and Min Wu, 2016. Flicker Forensics for Camcorder Piracy. Available at: http://sigport.org/610.
Adi Hajj-Ahmad, Severine Baudry, Bertrand Chupeau, Gwenael Doerr, and Min Wu. (2016). "Flicker Forensics for Camcorder Piracy." Web.
1. Adi Hajj-Ahmad, Severine Baudry, Bertrand Chupeau, Gwenael Doerr, and Min Wu. Flicker Forensics for Camcorder Piracy [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/610

"Seeing the Invisibles: A Backstage Tour of Information Forensics" - Slides from IEEE Distinguished Lectures


IEEE Distinguished Lecture on
"Seeing the Invisibles: A Backstage Tour of Information Forensics"

(Given at the School of ICASSP 2015 in April 2015 and IEEE Signal Processing Chapters in Fall 2015)

by Prof. Min Wu
University of Maryland, College Park, USA

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18 July 2016 - 2:51pm
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[1] , ""Seeing the Invisibles: A Backstage Tour of Information Forensics" - Slides from IEEE Distinguished Lectures", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/602. Accessed: Aug. 20, 2017.
@article{602-16,
url = {http://sigport.org/602},
author = { },
publisher = {IEEE SigPort},
title = {"Seeing the Invisibles: A Backstage Tour of Information Forensics" - Slides from IEEE Distinguished Lectures},
year = {2016} }
TY - EJOUR
T1 - "Seeing the Invisibles: A Backstage Tour of Information Forensics" - Slides from IEEE Distinguished Lectures
AU -
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/602
ER -
. (2016). "Seeing the Invisibles: A Backstage Tour of Information Forensics" - Slides from IEEE Distinguished Lectures. IEEE SigPort. http://sigport.org/602
, 2016. "Seeing the Invisibles: A Backstage Tour of Information Forensics" - Slides from IEEE Distinguished Lectures. Available at: http://sigport.org/602.
. (2016). ""Seeing the Invisibles: A Backstage Tour of Information Forensics" - Slides from IEEE Distinguished Lectures." Web.
1. . "Seeing the Invisibles: A Backstage Tour of Information Forensics" - Slides from IEEE Distinguished Lectures [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/602

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