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Information Forensics and Security, IEEE Transactions on

Issue 3 • Date March 2013

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Displaying Results 1 - 25 of 26
  • Front Cover

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

    Page(s): C2
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  • Table of contents

    Page(s): 425 - 426
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  • Table of contents

    Page(s): 427 - 428
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  • Unreconciled Collisions Uncover Cloning Attacks in Anonymous RFID Systems

    Page(s): 429 - 439
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1587 KB) |  | HTML iconHTML  

    Cloning attacks threaten radio-frequency identification (RFID) applications but are hard to prevent. Existing cloning attack detection methods are enslaved to the knowledge of tag identifiers (IDs). Tag IDs, however, should be protected to enable and secure privacy-sensitive applications in anonymous RFID systems. In a first step, this paper tackles cloning attack detection in anonymous RFID systems without requiring tag IDs as a priori. To this end, we leverage unreconciled collisions to uncover cloning attacks. An unreconciled collision is probably due to responses from multiple tags with the same ID, exactly the evidence of cloning attacks. This insight inspires GREAT, our pioneer protocol for cloning attack detection in anonymous RFID systems. We evaluate the performance of GREAT through theoretical analysis and extensive simulations. The results show that GREAT can detect cloning attacks in anonymous RFID systems fairly fast with required accuracy. For example, when only six out of 50,000 tags are cloned, GREAT can detect the cloning attack in 75.5 s with a probability of at least 0.99. View full abstract»

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  • Increasing Security Degree of Freedom in Multiuser and Multieve Systems

    Page(s): 440 - 449
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2147 KB) |  | HTML iconHTML  

    Secure communication in the multiuser and multieavesdropper (MUME) scenario is considered in this paper. It has be shown that secrecy can be improved when the transmitter simultaneously transmits an information-bearing signal to the intended receivers and artificial noise to confuse the eavesdroppers. Several processing schemes have been proposed to limit the cochannel interference (CCI). In this paper, we propose the increasing security degree of freedom (ISDF) method, which takes an idea from dirty-paper coding (DPC) and ZF beam-forming. By means of known interference precancellation at the transmitter, we design each precoder according to the previously designed precoding matrices, rather than other users' channels, which in return provides extra freedom for the design of precoders. Simulations demonstrate that the proposed method achieves the better performance and relatively low complexity. View full abstract»

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  • The Source Identification Game: An Information-Theoretic Perspective

    Page(s): 450 - 463
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2785 KB) |  | HTML iconHTML  

    We introduce a theoretical framework in which to cast the source identification problem. Thanks to the adoption of a game-theoretic approach, the proposed framework permits us to derive the ultimate achievable performance of the forensic analysis in the presence of an adversary aiming at deceiving it. The asymptotic Nash equilibrium of the source identification game is derived under an assumption on the resources on which the forensic analyst may rely. The payoff at the equilibrium is analyzed, deriving the conditions under which a successful forensic analysis is possible and the error exponent of the false-negative error probability in such a case. The difficulty of deriving a closed-form solution for general instances of the game is alleviated by the introduction of an efficient numerical procedure for the derivation of the optimum attacking strategy. The numerical analysis is applied to a case study to show the kind of information it can provide. View full abstract»

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  • An Asymptotically Uniformly Most Powerful Test for LSB Matching Detection

    Page(s): 464 - 476
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3344 KB) |  | HTML iconHTML  

    This paper investigates the detection of information hidden in digital media by the least significant bit (LSB) matching scheme. In a theoretical context of known medium parameters, two important results are presented. First, based on the likelihood ratio test, we present a test that asymptotically maximizes the detection power whatever the embedding rate might be. Second, the statistical properties of this test are analytically calculated; it is particularly shown that the decision threshold which warrants a given probability of false-alarm is independent of inspected medium parameters. This provides an asymptotic upper-bound for the detection power of any test that aims at detecting data hidden with the LSB matching method. In practice, when detecting LSB matching, the unknown medium parameters have to be estimated. Based on a local model of digital media, a generalized likelihood ratio test is presented by replacing the unknown parameters by their estimation. Numerical results on large databases highlight the relevance of the proposed methodology and comparison with state-of-the-art detectors shows that the proposed tests perform well. View full abstract»

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  • A Timing Channel Spyware for the CSMA/CA Protocol

    Page(s): 477 - 487
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1281 KB) |  | HTML iconHTML  

    This paper presents the design and implementation of spyware communication circuits built into the widely used carrier sense multiple access with collision avoidance (CSMA/CA) protocol. The spyware components are embedded within the sequential and combinational communication circuit structure during synthesis, rendering the distinction or dissociation of the spyware from the original circuit impossible. We take advantage of the timing channel resulting from transmission of packets to implement a new practical coding scheme that covertly transfers the spied data. Our codes are robust against the CSMA/CA's random retransmission time for collision avoidance and in fact take advantage of it to disguise the covert communication. The data snooping may be sporadically triggered, either externally or internally. The occasional trigger and the real-time traffic's variability make the spyware timing covert channel detection a challenge. The spyware is implemented and tested on a widely used open-source wireless CSMA/CA radio platform. We identify the following performance metrics and evaluate them on our architecture: 1) efficiency of implementation of the encoder; 2) robustness of the communication scheme to heterogeneous CSMA/CA effects; and 3) difficulty of covert channel detection. We evaluate criterion 1) completely theoretically. Criterion 2) is evaluated by simulating a wireless CSMA/CA architecture and testing the robustness of the decoder in different heterogeneous wireless conditions. Criterion 3) is confirmed experimentally using the state-of-the-art covert timing channel detection methods. View full abstract»

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  • Gender Classification Based on Fusion of Different Spatial Scale Features Selected by Mutual Information From Histogram of LBP, Intensity, and Shape

    Page(s): 488 - 499
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2785 KB) |  | HTML iconHTML  

    In this paper, we report our extension of the use of feature selection based on mutual information and feature fusion to improve gender classification of face images. We compare the results of fusing three groups of features, three spatial scales, and four different mutual information measures to select features. We also showed improved results by fusion of LBP features with different radii and spatial scales, and the selection of features using mutual information. As measures of mutual information we use minimum redundancy and maximal relevance (mRMR), normalized mutual information feature selection (NMIFS), conditional mutual information feature selection (CMIFS), and conditional mutual information maximization (CMIM). We tested the results on four databases: FERET and UND, under controlled conditions, the LFW database under unconstrained scenarios, and AR for occlusions. It is shown that selection of features together with fusion of LBP features significantly improved gender classification accuracy compared to previously published results. We also show a significant reduction in processing time because of the feature selection, which makes real-time applications of gender classification feasible. View full abstract»

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  • SVM Training Phase Reduction Using Dataset Feature Filtering for Malware Detection

    Page(s): 500 - 509
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1546 KB) |  | HTML iconHTML  

    N-gram analysis is an approach that investigates the structure of a program using bytes, characters, or text strings. A key issue with N-gram analysis is feature selection amidst the explosion of features that occurs when N is increased. The experiments within this paper represent programs as operational code (opcode) density histograms gained through dynamic analysis. A support vector machine is used to create a reference model, which is used to evaluate two methods of feature reduction, which are “area of intersect” and “subspace analysis using eigenvectors.” The findings show that the relationships between features are complex and simple statistics filtering approaches do not provide a viable approach. However, eigenvector subspace analysis produces a suitable filter. View full abstract»

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  • Cost-Sensitive Subspace Analysis and Extensions for Face Recognition

    Page(s): 510 - 519
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1602 KB) |  | HTML iconHTML  

    Conventional subspace-based face recognition methods seek low-dimensional feature subspaces to achieve high classification accuracy and assume the same loss from different types of misclassification. This assumption, however, may not hold in many practical face recognition systems as different types of misclassification could lead to different losses. Motivated by this concern, this paper proposes a cost-sensitive subspace analysis approach for face recognition. Our approach uses a cost matrix specifying different costs corresponding to different types of misclassifications, into two popular and widely used discriminative subspace analysis methods and devises the cost-sensitive linear discriminant analysis (CSLDA) and cost-sensitive marginal fisher analysis (CSMFA) methods, to achieve a minimum overall recognition loss by performing recognition in these learned low-dimensional subspaces. To better exploit the complementary information from multiple features for improved face recognition, we further propose a multiview cost-sensitive subspace analysis approach by seeking a common feature subspace to fuse multiple face features to improve the recognition performance. Extensive experimental results demonstrate the effectiveness of our proposed methods. View full abstract»

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  • A New Method for EEG-Based Concealed Information Test

    Page(s): 520 - 527
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1352 KB) |  | HTML iconHTML  

    Forensic electroencephalogram (EEG)-based lie detection has recently begun using the concealed information test (CIT) as a potentially more robust alternative to the classical comparative questions test. The main problem with using CIT is that it requires an objective and fast decision algorithm under the constraint of limited available information. In this study, we developed a simple and feasible hierarchical knowledge base construction and test method for efficient concealed information detection based on objective EEG measures. We describe how a hierarchical feature space was formed and which level of the feature space was sufficient to accurately predict concealed information from the raw EEG signal in a short time. A total of 11 subjects went through an autobiographical paradigm test. A high accuracy of 95.23% in recognizing concealed information with a single EEG electrode within about 20 seconds demonstrates effectiveness of the method. View full abstract»

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  • Snoop-Forge-Replay Attacks on Continuous Verification With Keystrokes

    Page(s): 528 - 541
    Multimedia
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    We present a new attack called the snoop-forge-replay attack on keystroke-based continuous verification systems. The snoop-forge-replay is a sample-level forgery attack and is not specific to any particular keystroke-based continuous verification method or system. It can be launched with easily available keyloggers and APIs for keystroke synthesis. Our results from 2640 experiments show that: 1) the snoop-forge-replay attacks achieve alarmingly high error rates compared to zero-effort impostor attacks, which have been the de facto standard for evaluating keystroke-based continuous verification systems; 2) four state-of-the-art verification methods, three types of keystroke latencies, and 11 matching-pair settings (-a key parameter in continuous verification with keystrokes) that we examined in this paper were susceptible to the attack; 3) the attack is effective even when as low as 20 to 100 keystrokes were snooped to create forgeries. In light of our results, we question the security offered by current keystroke-based continuous verification systems. Additionally, in our experiments, we harnessed virtualization technology to generate thousands of keystroke forgeries within a short time span. We point out that virtualization setup such as the one used in our experiments can also be exploited by an attacker to scale and speedup the attack. View full abstract»

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  • A Study on Reconstruction of Linear Scrambler Using Dual Words of Channel Encoder

    Page(s): 542 - 552
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (2688 KB) |  | HTML iconHTML  

    In this paper, the reconstruction of the feedback polynomial as well as the initial state of a linear feedback shift register (LFSR) in a synchronous scrambler placed after a channel encoder is studied. The study is first based on the assumption that the channel is noiseless and then extended to the noisy channel condition. The dual words, which are orthogonal to the codewords generated by the channel encoder, are used in the reconstruction algorithm. The number of bits required by the new algorithm is compared with another recently proposed algorithm and results show that the number of bits required to do the reconstruction can be significantly reduced. View full abstract»

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  • Reversible Data Hiding in Encrypted Images by Reserving Room Before Encryption

    Page(s): 553 - 562
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2659 KB) |  | HTML iconHTML  

    Recently, more and more attention is paid to reversible data hiding (RDH) in encrypted images, since it maintains the excellent property that the original cover can be losslessly recovered after embedded data is extracted while protecting the image content's confidentiality. All previous methods embed data by reversibly vacating room from the encrypted images, which may be subject to some errors on data extraction and/or image restoration. In this paper, we propose a novel method by reserving room before encryption with a traditional RDH algorithm, and thus it is easy for the data hider to reversibly embed data in the encrypted image. The proposed method can achieve real reversibility, that is, data extraction and image recovery are free of any error. Experiments show that this novel method can embed more than 10 times as large payloads for the same image quality as the previous methods, such as for PSNR=40 dB. View full abstract»

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  • Acoustic Eavesdropping Attacks on Constrained Wireless Device Pairing

    Page(s): 563 - 577
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1274 KB) |  | HTML iconHTML  

    Secure “pairing” of wireless devices based on auxiliary or out-of-band (OOB)-audio, visual, or tactile-communication is a well-established research direction. Specifically, authenticated as well as secret OOB (AS-OOB) channels have been shown to be quite useful for this purpose. Pairing can be achieved by simply transmitting the key or short password over the AS-OOB channel, avoiding potential serious human errors. This paper analyzes the security of AS-OOB pairing. Specifically, we take a closer look at three notable prior AS-OOB pairing proposals and challenge the assumptions upon which the security of these proposals relies, i.e., the secrecy of underlying audio channels. The first proposal (IMD Pairing) uses a low frequency audio channel to pair an implanted RFID tag with an external reader. The second proposal (PIN-Vibra) uses an automated vibrational channel to pair a mobile phone with a personal RFID tag. The third proposal (BEDA) uses vibration (or blinking) on one device and manually synchronized button pressing on another device or simultaneous button pressing on two devices. We demonstrate the feasibility of eavesdropping over acoustic emanations associated with these methods and conclude that they provide a weaker level of security than was originally assumed or desired for the pairing operation. View full abstract»

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  • JPEG Image Steganalysis Using Multivariate PDF Estimates With MRF Cliques

    Page(s): 578 - 587
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1252 KB) |  | HTML iconHTML  

    Blind steganalysis of JPEG images is addressed by modeling the correlations among the DCT coefficients using K -variate (K ≥ 2) p.d.f. estimates (p.d.f.s) constructed by means of Markov random field (MRF) cliques. The reasoning of using high variate p.d.f.s together with MRF cliques for image steganalysis is explained via a classical detection problem. Although our approach has many improvements over the current state-of-the-art, it suffers from the high dimensionality and the sparseness of the high variate p.d.f.s. The dimensionality problem as well as the sparseness problem are solved heuristically by means of dimensionality reduction and feature selection algorithms. The detection accuracy of the proposed method(s) is evaluated over Memon's (30.000 images) and Goljan's (1912 images) image sets. It is shown that practically applicable steganalysis systems are possible with a suitable dimensionality reduction technique and these systems can provide, in general, improved detection accuracy over the current state-of-the-art. Experimental results also justify this assertion. View full abstract»

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    Page(s): 588
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  • IEEE Transactions on Information Forensics and Security - EDICS

    Page(s): 589
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  • IEEE Transactions on Information Forensics and Security information for authors

    Page(s): 590 - 591
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  • J-STSP call for special issue proposals

    Page(s): 592
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  • IEEE Xplore Digital Library

    Page(s): 593
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  • Open Access

    Page(s): 594
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  • IEEE Signal Processing Society Information

    Page(s): C3
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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.

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Meet Our Editors

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