Pub Date : 2012-12-01DOI: 10.1109/WIFS.2012.6412630
M. Schott, R. Merkel, J. Dittmann
This paper presents a novel approach for sequence detection of overlapping latent fingerprints for crime scene forensics. The approach involves a contactless and nondestructive acquisition of untreated fingerprints by using a Chromatic White Light (CWL) sensor. Based on 40 time series with 1160 samples, our approach shows how an aging feature called Binary Pixel for measuring the short-term decay of fingerprint samples can be used in combination with overlapping fingerprint separation methods for sequence detection. This allows differentiating which latent fingerprint was placed first and which later and thus provides contextual information for criminal investigations. Our experiments show promising results with a detection accuracy of at least 70%, regardless of the initial age of both the older and newer fingerprint.
{"title":"Sequence detection of overlapping latent fingerprints using a short-term aging feature","authors":"M. Schott, R. Merkel, J. Dittmann","doi":"10.1109/WIFS.2012.6412630","DOIUrl":"https://doi.org/10.1109/WIFS.2012.6412630","url":null,"abstract":"This paper presents a novel approach for sequence detection of overlapping latent fingerprints for crime scene forensics. The approach involves a contactless and nondestructive acquisition of untreated fingerprints by using a Chromatic White Light (CWL) sensor. Based on 40 time series with 1160 samples, our approach shows how an aging feature called Binary Pixel for measuring the short-term decay of fingerprint samples can be used in combination with overlapping fingerprint separation methods for sequence detection. This allows differentiating which latent fingerprint was placed first and which later and thus provides contextual information for criminal investigations. Our experiments show promising results with a detection accuracy of at least 70%, regardless of the initial age of both the older and newer fingerprint.","PeriodicalId":396789,"journal":{"name":"2012 IEEE International Workshop on Information Forensics and Security (WIFS)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133311846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-01DOI: 10.1109/WIFS.2012.6412659
Sabrina Gerbracht, Eduard Axel Jorswieck, G. Zheng, B. Ottersten
In this paper, we analyze the achievable secrecy rates in the two-hop wiretap channel with four nodes, where the transmitter and the receiver have multiple antennas while the relay and the eavesdropper have only a single antenna each. The relay is operating in amplify-and-forward mode and all the channels between the nodes are known perfectly by the transmitter. We discuss different transmission and protection schemes like artificial noise (AN). Furthermore, we introduce interference neutralization (IN) as a new protection scheme. We compare the different schemes regarding the high-SNR slope and the high-SNR power offset and illustrate the performance by simulation results. It is shown analytically as well as by numerical simulations that the high SNR performance of the proposed IN scheme is better than the one of AN.
{"title":"Non-regenerative two-hop wiretap channels using interference neutralization","authors":"Sabrina Gerbracht, Eduard Axel Jorswieck, G. Zheng, B. Ottersten","doi":"10.1109/WIFS.2012.6412659","DOIUrl":"https://doi.org/10.1109/WIFS.2012.6412659","url":null,"abstract":"In this paper, we analyze the achievable secrecy rates in the two-hop wiretap channel with four nodes, where the transmitter and the receiver have multiple antennas while the relay and the eavesdropper have only a single antenna each. The relay is operating in amplify-and-forward mode and all the channels between the nodes are known perfectly by the transmitter. We discuss different transmission and protection schemes like artificial noise (AN). Furthermore, we introduce interference neutralization (IN) as a new protection scheme. We compare the different schemes regarding the high-SNR slope and the high-SNR power offset and illustrate the performance by simulation results. It is shown analytically as well as by numerical simulations that the high SNR performance of the proposed IN scheme is better than the one of AN.","PeriodicalId":396789,"journal":{"name":"2012 IEEE International Workshop on Information Forensics and Security (WIFS)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122745475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-01DOI: 10.1109/WIFS.2012.6412618
C. Huang, B. Efraty, U. Kurkure, E. Papadakis, S. Shah, I. Kakadiaris
In this paper, we present two methods to improve the performance of landmark detection algorithms that are designed to detect individual landmarks. We focus on the landmark configuration module that takes the output of the individual landmark detectors and searches for a configuration of optimal landmark locations based on appropriate shape constraints. We design two configuration search approaches: (i) a multivariate conditional Gaussian-based model, and (ii) a MRF-based formulation with higher-order potentials. We evaluated the performance of our proposed methods using several state-of-the-art detectors, and consistently obtained improved performance.
{"title":"Facial landmark configuration for improved detection","authors":"C. Huang, B. Efraty, U. Kurkure, E. Papadakis, S. Shah, I. Kakadiaris","doi":"10.1109/WIFS.2012.6412618","DOIUrl":"https://doi.org/10.1109/WIFS.2012.6412618","url":null,"abstract":"In this paper, we present two methods to improve the performance of landmark detection algorithms that are designed to detect individual landmarks. We focus on the landmark configuration module that takes the output of the individual landmark detectors and searches for a configuration of optimal landmark locations based on appropriate shape constraints. We design two configuration search approaches: (i) a multivariate conditional Gaussian-based model, and (ii) a MRF-based formulation with higher-order potentials. We evaluated the performance of our proposed methods using several state-of-the-art detectors, and consistently obtained improved performance.","PeriodicalId":396789,"journal":{"name":"2012 IEEE International Workshop on Information Forensics and Security (WIFS)","volume":"699 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122866142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-01DOI: 10.1109/WIFS.2012.6412628
Yannis Panagakis, Constantine Kotropoulos
Speech signals convey information not only for the speakers' identity and the spoken language, but also for the acquisition devices used during their recording. Therefore, it is reasonable to perform acquisition device identification by analyzing the recorded speech signal. To this end, the random spectral features (RSFs) and the labeled spectral features (LSFs) are proposed as intrinsic fingerprints suitable for device identification. The RSFs and the LSFs are extracted by applying unsupervised and supervised feature selection to the mean spectrogram of each speech signal, respectively. State-of-the-art identification accuracy of 97.58% has been obtained by employing LSFs on a set of 8 telephone handsets, from Lincoln-Labs Handset Database (LLHDB).
{"title":"Telephone handset identification by feature selection and sparse representations","authors":"Yannis Panagakis, Constantine Kotropoulos","doi":"10.1109/WIFS.2012.6412628","DOIUrl":"https://doi.org/10.1109/WIFS.2012.6412628","url":null,"abstract":"Speech signals convey information not only for the speakers' identity and the spoken language, but also for the acquisition devices used during their recording. Therefore, it is reasonable to perform acquisition device identification by analyzing the recorded speech signal. To this end, the random spectral features (RSFs) and the labeled spectral features (LSFs) are proposed as intrinsic fingerprints suitable for device identification. The RSFs and the LSFs are extracted by applying unsupervised and supervised feature selection to the mean spectrogram of each speech signal, respectively. State-of-the-art identification accuracy of 97.58% has been obtained by employing LSFs on a set of 8 telephone handsets, from Lincoln-Labs Handset Database (LLHDB).","PeriodicalId":396789,"journal":{"name":"2012 IEEE International Workshop on Information Forensics and Security (WIFS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130516595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-01DOI: 10.1109/WIFS.2012.6412619
J. Metzler
The objective of human re-identification is to recognize a specific individual on different locations and to determine whether an individual has already appeared. This is especially in multi-camera networks with non-overlapping fields of view of interest. However, this is still an unsolved computer vision task due to several challenges, e.g. significant changes of appearance of humans as well as different illumination, camera parameters etc. In addition, for instance, in surveillance scenarios only low-resolution videos are usually available, so that biometric approaches may not be applied. This paper presents a whole-body appearance-based human re-identification approach for low-resolution videos. The method is divided in two stages: first, an appearance model is computed from several images of an individual and pairwise compared to each other. The model is based on means of covariance descriptors determined by spectral clustering techniques. In the second stage, the result is refined by learning the appearance manifolds of the best matches. The proposed approach is tested on a multi-camera data set of a typical surveillance scenario and compared to a color histogram based method.
{"title":"Two-stage appearance-based re-identification of humans in low-resolution videos","authors":"J. Metzler","doi":"10.1109/WIFS.2012.6412619","DOIUrl":"https://doi.org/10.1109/WIFS.2012.6412619","url":null,"abstract":"The objective of human re-identification is to recognize a specific individual on different locations and to determine whether an individual has already appeared. This is especially in multi-camera networks with non-overlapping fields of view of interest. However, this is still an unsolved computer vision task due to several challenges, e.g. significant changes of appearance of humans as well as different illumination, camera parameters etc. In addition, for instance, in surveillance scenarios only low-resolution videos are usually available, so that biometric approaches may not be applied. This paper presents a whole-body appearance-based human re-identification approach for low-resolution videos. The method is divided in two stages: first, an appearance model is computed from several images of an individual and pairwise compared to each other. The model is based on means of covariance descriptors determined by spectral clustering techniques. In the second stage, the result is refined by learning the appearance manifolds of the best matches. The proposed approach is tested on a multi-camera data set of a typical surveillance scenario and compared to a color histogram based method.","PeriodicalId":396789,"journal":{"name":"2012 IEEE International Workshop on Information Forensics and Security (WIFS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124851778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-01DOI: 10.1109/WIFS.2012.6412637
T. Bianchi, A. Piva
In this paper, we propose a forensic technique for the reverse engineering of double JPEG compression in the presence of image resizing between the two compressions. Our approach is based on the fact that previously JPEG compressed images tend to have a near lattice distribution property (NLDP), and that this property is usually maintained after a simple image processing step and subsequent recompression. The proposed approach represents an improvement with respect to existing techniques analyzing double JPEG compression. Moreover, compared to forensic techniques aiming at the detection of resampling in JPEG images, the proposed approach moves a step further, since it also provides an estimation of both the resize factor and the quality factor of the previous JPEG compression. Such additional information can be used to reconstruct the history of an image and perform more detailed forensic analyses.
{"title":"Reverse engineering of double JPEG compression in the presence of image resizing","authors":"T. Bianchi, A. Piva","doi":"10.1109/WIFS.2012.6412637","DOIUrl":"https://doi.org/10.1109/WIFS.2012.6412637","url":null,"abstract":"In this paper, we propose a forensic technique for the reverse engineering of double JPEG compression in the presence of image resizing between the two compressions. Our approach is based on the fact that previously JPEG compressed images tend to have a near lattice distribution property (NLDP), and that this property is usually maintained after a simple image processing step and subsequent recompression. The proposed approach represents an improvement with respect to existing techniques analyzing double JPEG compression. Moreover, compared to forensic techniques aiming at the detection of resampling in JPEG images, the proposed approach moves a step further, since it also provides an estimation of both the resize factor and the quality factor of the previous JPEG compression. Such additional information can be used to reconstruct the history of an image and perform more detailed forensic analyses.","PeriodicalId":396789,"journal":{"name":"2012 IEEE International Workshop on Information Forensics and Security (WIFS)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117190622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-01DOI: 10.1109/WIFS.2012.6412658
Duc-Tien Dang-Nguyen, G. Boato, F. D. Natale
Significant improvements have been recently achieved in both quality and realism of computer generated characters, which are nowadays often very difficult to be distinguished from real ones. However, generating highly realistic facial expressions is still a challenging issue, since synthetic expressions usually follow a repetitive pattern, while in natural faces the same expression is usually produced in similar but not equal ways. In this paper, we propose a method to distinguish between computer generated and natural faces based on facial expressions analysis. In particular, small variations of the facial shape models corresponding to the same expression are used as evidence of synthetic characters.
{"title":"Identify computer generated characters by analysing facial expressions variation","authors":"Duc-Tien Dang-Nguyen, G. Boato, F. D. Natale","doi":"10.1109/WIFS.2012.6412658","DOIUrl":"https://doi.org/10.1109/WIFS.2012.6412658","url":null,"abstract":"Significant improvements have been recently achieved in both quality and realism of computer generated characters, which are nowadays often very difficult to be distinguished from real ones. However, generating highly realistic facial expressions is still a challenging issue, since synthetic expressions usually follow a repetitive pattern, while in natural faces the same expression is usually produced in similar but not equal ways. In this paper, we propose a method to distinguish between computer generated and natural faces based on facial expressions analysis. In particular, small variations of the facial shape models corresponding to the same expression are used as evidence of synthetic characters.","PeriodicalId":396789,"journal":{"name":"2012 IEEE International Workshop on Information Forensics and Security (WIFS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117075973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-01DOI: 10.1109/WIFS.2012.6412640
Takayuki Yamada, S. Gohshi, I. Echizen
A method is described for preventing unauthorized copying of information shown on a display. It utilizes the difference in spectral sensitivity between humans and imaging devices. A near-infrared light source, which has no effect on human vision, is installed in front of an existing display to corrupt the content of photographs taken of the display. Testing using a prototype implementation demonstrated that this method effectively prevents the unauthorized copying of displayed information. In addition to preventing the disclosure of confidential and personal information through the unauthorized photographing of displays, the proposed method has broad application to the unauthorized photographing of works of art, factory equipment, and other objects subject to photographic restrictions.
{"title":"Preventing unauthorized copying of displayed information by utilizing differences in spectral sensitivity between humans and imaging devices","authors":"Takayuki Yamada, S. Gohshi, I. Echizen","doi":"10.1109/WIFS.2012.6412640","DOIUrl":"https://doi.org/10.1109/WIFS.2012.6412640","url":null,"abstract":"A method is described for preventing unauthorized copying of information shown on a display. It utilizes the difference in spectral sensitivity between humans and imaging devices. A near-infrared light source, which has no effect on human vision, is installed in front of an existing display to corrupt the content of photographs taken of the display. Testing using a prototype implementation demonstrated that this method effectively prevents the unauthorized copying of displayed information. In addition to preventing the disclosure of confidential and personal information through the unauthorized photographing of displays, the proposed method has broad application to the unauthorized photographing of works of art, factory equipment, and other objects subject to photographic restrictions.","PeriodicalId":396789,"journal":{"name":"2012 IEEE International Workshop on Information Forensics and Security (WIFS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127701077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-01DOI: 10.1109/WIFS.2012.6412633
T. Pevný, M. Rehák, Martin Grill
This paper focuses on the identification of anomalous hosts within a computer network with the motivation to detect attacks and/or other unwanted and suspicious traffic. The proposed detection method does not use content of packets, which enables the method to be used on encrypted networks. Moreover, the method has very low computational complexity allowing fast detection and response important for limitation of potential damages. The proposed method uses entropies of IP addresses and ports to build two complementary models of host's traffic based on principal component analysis. These two models are coupled with two orthogonal anomaly definitions, which gives four different detectors. The methods are evaluated and compared to prior art on one week long capture of traffic on university network. The experiments reveals that no single detector can detect all types of anomalies, which is expected and stresses the importance of ensemble approach towards intrusion detection.
{"title":"Detecting anomalous network hosts by means of PCA","authors":"T. Pevný, M. Rehák, Martin Grill","doi":"10.1109/WIFS.2012.6412633","DOIUrl":"https://doi.org/10.1109/WIFS.2012.6412633","url":null,"abstract":"This paper focuses on the identification of anomalous hosts within a computer network with the motivation to detect attacks and/or other unwanted and suspicious traffic. The proposed detection method does not use content of packets, which enables the method to be used on encrypted networks. Moreover, the method has very low computational complexity allowing fast detection and response important for limitation of potential damages. The proposed method uses entropies of IP addresses and ports to build two complementary models of host's traffic based on principal component analysis. These two models are coupled with two orthogonal anomaly definitions, which gives four different detectors. The methods are evaluated and compared to prior art on one week long capture of traffic on university network. The experiments reveals that no single detector can detect all types of anomalies, which is expected and stresses the importance of ensemble approach towards intrusion detection.","PeriodicalId":396789,"journal":{"name":"2012 IEEE International Workshop on Information Forensics and Security (WIFS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129864774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-12-01DOI: 10.1109/WIFS.2012.6412644
Linjie Guo, J. Ni, Y. Shi
Steganography is the science and art of covert communication. Its objective is to hide the most secret messages into a cover object with the least possible statistical detectability. In practice, this is generally realized by a framework of minimal distortion embedding. This paper presents an efficient JPEG steganographic scheme based on syndrome trellis coding (STC) and a uniform embedding strategy, which, instead of random modification, tries to modify nonzero quantized DCT coefficients of different magnitude with equal probability, leading to possible minimal artifacts for statistics of DCT coefficients as a whole. The distortion metric corresponding to the uniform embedding is based on the magnitude of the DCT coefficients and both their intra- and inter-block neighborhood coefficients and known as uniform embedding distortion metric (UED). With the proposed scheme, the STC provides multiple codewords for a given message, while the UED determines the best one with minimal distortion. In this way, the average statistics change in each bin is significantly reduced, which corresponds to less detectability of steganalysis. Compared with prior arts, experimental results demonstrate the superior performance of the proposed scheme in terms of secure embedding capacity against steganalysis.
{"title":"An efficient JPEG steganographic scheme using uniform embedding","authors":"Linjie Guo, J. Ni, Y. Shi","doi":"10.1109/WIFS.2012.6412644","DOIUrl":"https://doi.org/10.1109/WIFS.2012.6412644","url":null,"abstract":"Steganography is the science and art of covert communication. Its objective is to hide the most secret messages into a cover object with the least possible statistical detectability. In practice, this is generally realized by a framework of minimal distortion embedding. This paper presents an efficient JPEG steganographic scheme based on syndrome trellis coding (STC) and a uniform embedding strategy, which, instead of random modification, tries to modify nonzero quantized DCT coefficients of different magnitude with equal probability, leading to possible minimal artifacts for statistics of DCT coefficients as a whole. The distortion metric corresponding to the uniform embedding is based on the magnitude of the DCT coefficients and both their intra- and inter-block neighborhood coefficients and known as uniform embedding distortion metric (UED). With the proposed scheme, the STC provides multiple codewords for a given message, while the UED determines the best one with minimal distortion. In this way, the average statistics change in each bin is significantly reduced, which corresponds to less detectability of steganalysis. Compared with prior arts, experimental results demonstrate the superior performance of the proposed scheme in terms of secure embedding capacity against steganalysis.","PeriodicalId":396789,"journal":{"name":"2012 IEEE International Workshop on Information Forensics and Security (WIFS)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130620864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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