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Information Forensics and Security, IEEE Transactions on

Issue 7 • Date July 2014

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Displaying Results 1 - 23 of 23
  • [Front cover]

    Publication Year: 2014 , Page(s): C1
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  • IEEE Transactions on Information Forensics and Security publication information

    Publication Year: 2014 , Page(s): C2
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  • Table of contents

    Publication Year: 2014 , Page(s): 1041 - 1042
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  • Table of contents

    Publication Year: 2014 , Page(s): 1043 - 1044
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  • A Dynamic Matching Algorithm for Audio Timestamp Identification Using the ENF Criterion

    Publication Year: 2014 , Page(s): 1045 - 1055
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    The electric network frequency (ENF) criterion is a recently developed technique for audio timestamp identification, which involves the matching between extracted ENF signal and reference data. For nearly a decade, conventional matching criterion has been based on the minimum mean squared error (MMSE) or maximum correlation coefficient. However, the corresponding performance is highly limited by low signal-to-noise ratio, short recording durations, frequency resolution problems, and so on. This paper presents a threshold-based dynamic matching algorithm (DMA), which is capable of autocorrecting the noise affected frequency estimates. The threshold is chosen according to the frequency resolution determined by the short-time Fourier transform (STFT) window size. A penalty coefficient is introduced to monitor the autocorrection process and finally determine the estimated timestamp. It is then shown that the DMA generalizes the conventional MMSE method. By considering the mainlobe width in the STFT caused by limited frequency resolution, the DMA achieves improved identification accuracy and robustness against higher levels of noise and the offset problem. Synthetic performance analysis and practical experimental results are provided to illustrate the advantages of the DMA. View full abstract»

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  • On Recognizing Faces in Videos Using Clustering-Based Re-Ranking and Fusion

    Publication Year: 2014 , Page(s): 1056 - 1068
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    Due to widespread applications, availability of large intra-personal variations in video and limited information content in still images, video-based face recognition has gained significant attention. Unlike still face images, videos provide abundant information that can be leveraged to address variations in pose, illumination, and expression as well as enhance the face recognition performance. This paper presents a video-based face recognition algorithm that computes a discriminative video signature as an ordered list of still face images from a large dictionary. A three-stage approach is proposed for optimizing ranked lists across multiple video frames and fusing them into a single composite ordered list to compute the video signature. This signature embeds diverse intra-personal variations and facilitates in matching two videos with large variations. For matching two videos, a discounted cumulative gain measure is utilized, which uses the ranking of images in the video signature as well as the usefulness of images in characterizing the individual in the video. The efficacy of the proposed algorithm is evaluated under different video-based face recognition scenarios such as matching still face images with videos and matching videos with videos. The efficacy of the proposed algorithm is demonstrated on the YouTube faces database and the MBGC v2 video challenge database that comprise different types of video-based face recognition challenges such as matching still face images with videos and matching videos with videos. Performance comparison with the benchmark results on both the databases and a commercial face recognition system shows the efficiency of the proposed algorithm for video-based face recognition. View full abstract»

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  • On a Mathematical Model for Low-Rate Shrew DDoS

    Publication Year: 2014 , Page(s): 1069 - 1083
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    The shrew distributed denial of service (DDoS) attack is very detrimental for many applications, since it can throttle TCP flows to a small fraction of their ideal rate at very low attack cost. Earlier works mainly focused on empirical studies of defending against the shrew DDoS, and very few of them provided analytic results about the attack itself. In this paper, we propose a mathematical model for estimating attack effect of this stealthy type of DDoS. By originally capturing the adjustment behaviors of victim TCPs congestion window, our model can comprehensively evaluate the combined impact of attack pattern (i.e., how the attack is configured) and network environment on attack effect (the existing models failed to consider the impact of network environment). Henceforth, our model has higher accuracy over a wider range of network environments. The relative error of our model remains around 10% for most attack patterns and network environments, whereas the relative error of the benchmark model in previous works has a mean value of 69.57%, and it could be more than 180% in some cases. More importantly, our model reveals some novel properties of the shrew attack from the interaction between attack pattern and network environment, such as the minimum cost formula to launch a successful attack, and the maximum effect formula of a shrew attack. With them, we are able to find out how to adaptively tune the attack parameters (e.g., the DoS burst length) to improve its attack effect in a given network environment, and how to reconfigure the network resource (e.g., the bottleneck buffer size) to mitigate the shrew DDoS with a given attack pattern. Finally, based on our theoretical results, we put forward a simple strategy to defend the shrew attack. The simulation results indicate that this strategy can remarkably increase TCP throughput by nearly half of the bottleneck bandwidth (and can be higher) for general attack patterns. View full abstract»

    Open Access
  • Spoofing Face Recognition With 3D Masks

    Publication Year: 2014 , Page(s): 1084 - 1097
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    Spoofing is the act of masquerading as a valid user by falsifying data to gain an illegitimate access. Vulnerability of recognition systems to spoofing attacks (presentation attacks) is still an open security issue in biometrics domain and among all biometric traits, face is exposed to the most serious threat, since it is particularly easy to access and reproduce. In this paper, many different types of face spoofing attacks have been examined and various algorithms have been proposed to detect them. Mainly focusing on 2D attacks forged by displaying printed photos or replaying recorded videos on mobile devices, a significant portion of these studies ground their arguments on the flatness of the spoofing material in front of the sensor. However, with the advancements in 3D reconstruction and printing technologies, this assumption can no longer be maintained. In this paper, we aim to inspect the spoofing potential of subject-specific 3D facial masks for different recognition systems and address the detection problem of this more complex attack type. In order to assess the spoofing performance of 3D masks against 2D, 2.5D, and 3D face recognition and to analyze various texture-based countermeasures using both 2D and 2.5D data, a parallel study with comprehensive experiments is performed on two data sets: the Morpho database which is not publicly available and the newly distributed 3D mask attack database. View full abstract»

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  • Subset Membership Encryption and Its Applications to Oblivious Transfer

    Publication Year: 2014 , Page(s): 1098 - 1107
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    In this paper, we propose a novel cryptographic notion called subset membership encryption (SME), and provide a very efficient SME scheme. Given a system parameter generated by an encryptor (Alice), a decryptor (Bob) generates a randomized privacy-preserved attribute token P(G) from a set of attributes G. A message is encrypted using an attribute set A chosen by Alice and P(G) provided by Bob. It requires that A is a subset of G for Bob to decrypt the message. We propose a very efficient SME scheme, where both the size of P(G) and ciphertext are short and independent of G and A. In particular, it has three useful and practical applications to oblivious transfer as follows. 1) k-Out-of-n Oblivious Transfer (OT): SME can be naturally applied to a two-round OT, which features a great communication efficiency especially for the receiver, where the receiver only sends two group elements to the message sender. 2) Priced Oblivious Transfer (POT): Our POT protocol allows a buyer to purchase any number of items in each transaction and hide selected items, price and balance from the vendor. In comparison with previous POT protocols, our protocol is more flexible and eliminates the restriction that a buyer can only purchase one item in a transaction. Our POT scheme is very efficient since it does not require any zero-knowledge proof or homomorphic encryption. 3) Restricted Priced Oblivious Transfer (RPOT): We introduce a novel POT named RPOT where a vendor can set restrictions on items or prices in POT. For example, a seller could offer a discounted price to those buyers who have purchased some specific items previously from the same seller. View full abstract»

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  • Perceptual DFT Watermarking With Improved Detection and Robustness to Geometrical Distortions

    Publication Year: 2014 , Page(s): 1108 - 1119
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3779 KB) |  | HTML iconHTML  

    More than ever, the growing amount of exchanged digital content calls for efficient and practical techniques to protect intellectual property rights. During the past two decades, watermarking techniques have been proposed to embed and detect information within these contents, with four key requirements at hand: robustness, security, capacity, and invisibility. So far, researchers mostly focused on the first three, but seldom addressed the invisibility from a perceptual perspective and instead mostly relied on objective quality metrics. In this paper, a novel DFT watermarking scheme featuring perceptually optimal visibility versus robustness is proposed. The watermark, a noise-like square patch of coefficients, is embedded by substitution within the Fourier domain; the amplitude component adjusts the watermark strength, and the phase component holds the information. A perceptual model of the human visual system (HVS) based on the contrast sensitivity function (CSF) and a local contrast pooling is used to determine the optimal strength at which the mark reaches the visibility threshold. A novel blind detection method is proposed to assess the presence of the watermark. The proposed approach exhibits high robustness to various kinds of attacks, including geometrical distortions. Experimental results show that the robustness of the proposed method is globally slightly better than state-of-the-art. A comparative study was conducted at the visibility threshold (from subjective data) and showed that the obtained performances are more stable across various kinds of content. View full abstract»

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  • Image Set-Based Collaborative Representation for Face Recognition

    Publication Year: 2014 , Page(s): 1120 - 1132
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    With the rapid development of digital imaging and communication technologies, image set-based face recognition (ISFR) is becoming increasingly important. One key issue of ISFR is how to effectively and efficiently represent the query face image set using the gallery face image sets. The set-to-set distance-based methods ignore the relationship between gallery sets, whereas representing the query set images individually over the gallery sets ignores the correlation between query set images. In this paper, we propose a novel image set-based collaborative representation and classification method for ISFR. By modeling the query set as a convex or regularized hull, we represent this hull collaboratively over all the gallery sets. With the resolved representation coefficients, the distance between the query set and each gallery set can then be calculated for classification. The proposed model naturally and effectively extends the image-based collaborative representation to an image set based one, and our extensive experiments on benchmark ISFR databases show the superiority of the proposed method to state-of-the-art ISFR methods under different set sizes in terms of both recognition rate and efficiency. View full abstract»

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  • A Non-Interactive Dual Channel Continuous Traffic Authentication Protocol

    Publication Year: 2014 , Page(s): 1133 - 1140
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    We introduce a non-interactive dual-channel protocol for continuous traffic authentication and analyze its security properties. We realize the proposed protocol by facilitating dual channels at the keyboard with the assistance of a lightweight hardware module. The proposed protocol does not require users' explicit engagement in the authentication process. Empirical results show that, for a 30-day period, the maximum false reject rate for all legitimate requests on a day is 6% (with a 30 day daily average of 2.4%) and the false accept rate on any given day is 0%. The daily maximum false reject rate of the user requests falls to 0% if the users are forced to engage explicitly in the protocol operation for a maximum of 1.2% of users' non-typed requests. View full abstract»

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  • Privacy-Preserving Optimal Meeting Location Determination on Mobile Devices

    Publication Year: 2014 , Page(s): 1141 - 1156
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3943 KB) |  | HTML iconHTML  

    Equipped with state-of-the-art smartphones and mobile devices, today's highly interconnected urban population is increasingly dependent on these gadgets to organize and plan their daily lives. These applications often rely on current (or preferred) locations of individual users or a group of users to provide the desired service, which jeopardizes their privacy; users do not necessarily want to reveal their current (or preferred) locations to the service provider or to other, possibly untrusted, users. In this paper, we propose privacy-preserving algorithms for determining an optimal meeting location for a group of users. We perform a thorough privacy evaluation by formally quantifying privacy-loss of the proposed approaches. In order to study the performance of our algorithms in a real deployment, we implement and test their execution efficiency on Nokia smartphones. By means of a targeted user-study, we attempt to get an insight into the privacy-awareness of users in location-based services and the usability of the proposed solutions. View full abstract»

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  • EasySMS: A Protocol for End-to-End Secure Transmission of SMS

    Publication Year: 2014 , Page(s): 1157 - 1168
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    Nowadays, short message service (SMS) is being used in many daily life applications, including healthcare monitoring, mobile banking, mobile commerce, and so on. But when we send an SMS from one mobile phone to another, the information contained in the SMS transmit as plain text. Sometimes this information may be confidential like account numbers, passwords, license numbers, and so on, and it is a major drawback to send such information through SMS while the traditional SMS service does not provide encryption to the information before its transmission. In this paper, we propose an efficient and secure protocol called EasySMS, which provides end-to-end secure communication through SMS between end users. The working of the protocol is presented by considering two different scenarios. The analysis of the proposed protocol shows that this protocol is able to prevent various attacks, including SMS disclosure, over the air modification, replay attack, man-in-the-middle attack, and impersonation attack. The EasySMS protocol generates minimum communication and computation overheads as compared with existing SMSSec and PK-SIM protocols. On an average, the EasySMS protocol reduces 51% and 31% of the bandwidth consumption and reduces 62% and 45% of message exchanged during the authentication process in comparison to SMSSec and PK-SIM protocols respectively. Authors claim that EasySMS is the first protocol completely based on the symmetric key cryptography and retain original architecture of cellular network. View full abstract»

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  • Discriminative Multimetric Learning for Kinship Verification

    Publication Year: 2014 , Page(s): 1169 - 1178
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3140 KB) |  | HTML iconHTML  

    In this paper, we propose a new discriminative multimetric learning method for kinship verification via facial image analysis. Given each face image, we first extract multiple features using different face descriptors to characterize face images from different aspects because different feature descriptors can provide complementary information. Then, we jointly learn multiple distance metrics with these extracted multiple features under which the probability of a pair of face image with a kinship relation having a smaller distance than that of the pair without a kinship relation is maximized, and the correlation of different features of the same face sample is maximized, simultaneously, so that complementary and discriminative information is exploited for verification. Experimental results on four face kinship data sets show the effectiveness of our proposed method over the existing single-metric and multimetric learning methods. View full abstract»

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  • A Delaunay Quadrangle-Based Fingerprint Authentication System With Template Protection Using Topology Code for Local Registration and Security Enhancement

    Publication Year: 2014 , Page(s): 1179 - 1192
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    Although some nice properties of the Delaunay triangle-based structure have been exploited in many fingerprint authentication systems and satisfactory outcomes have been reported, most of these systems operate without template protection. In addition, the feature sets and similarity measures utilized in these systems are not suitable for existing template protection techniques. Moreover, local structural change caused by nonlinear distortion is often not considered adequately in these systems. In this paper, we propose a Delaunay quadrangle-based fingerprint authentication system to deal with nonlinear distortion-induced local structural change that the Delaunay triangle-based structure suffers. Fixed-length and alignment-free feature vectors extracted from Delaunay quadrangles are less sensitive to nonlinear distortion and more discriminative than those from Delaunay triangles and can be applied to existing template protection directly. Furthermore, we propose to construct a unique topology code from each Delaunay quadrangle. Not only can this unique topology code help to carry out accurate local registration under distortion, but it also enhances the security of template data. Experimental results on public databases and security analysis show that the Delaunay quadrangle-based system with topology code can achieve better performance and higher security level than the Delaunay triangle-based system, the Delaunay quadrangle-based system without topology code, and some other similar systems. View full abstract»

    Open Access
  • Revocable Identity-Based Cryptosystem Revisited: Security Models and Constructions

    Publication Year: 2014 , Page(s): 1193 - 1205
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    Boneh and Franklin gave a naive revocation method in identity-based encryption (IBE) which imposes a huge overhead into the key generation center. Later, Boldyreva, Goyal, and Kumar proposed an elegant way of achieving an IBE with efficient revocation, called revocable IBE (RIBE). In this paper, we revisit RIBE from the viewpoint of both security models and constructions. First, we introduce a realistic threat, which we call decryption key exposure, and show that all prior RIBE constructions, except the Boneh-Franklin one, are vulnerable to decryption key exposure. Next, we propose the first scalable RIBE scheme with decryption key exposure resistance by combining the (adaptively secure) Waters IBE scheme and the (selectively secure) Boneh-Boyen IBE scheme, and show that our RIBE scheme is more efficient than all previous adaptively secure scalable RIBE schemes. In addition, we extend our interest into identity-based signatures; we introduce a new security definition of revocable identity-based signature (RIBS) with signing key exposure resistance, and propose the first scalable RIBS scheme based on the Paterson-Schuldt IBS. Finally, we provide implementation results of our schemes to adduce the feasibility of our schemes. View full abstract»

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  • [Blank page]

    Publication Year: 2014 , Page(s): B1206
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  • IEEE Transactions on Information Forensics and Security Edics

    Publication Year: 2014 , Page(s): 1207
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  • IEEE Transactions on Information Forensics and Security information for authors

    Publication Year: 2014 , Page(s): 1208 - 1209
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  • Special issue on Advances in Hyperspectral Data Processing and Analysis

    Publication Year: 2014 , Page(s): 1210
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  • IEEE Signal Processing Society Information

    Publication Year: 2014 , Page(s): C3
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  • [Blank page - back cover]

    Publication Year: 2014 , Page(s): C4
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Aims & Scope

The IEEE Transactions on Information Forensics and Security covers the sciences, technologies, and applications relating to information forensics, information security, biometrics, surveillance and systems applications that incorporate these features.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Mauro Barni
University of Siena, Italy