By Topic

Information Forensics and Security, IEEE Transactions on

Issue 8 • Date Aug. 2014

Filter Results

Displaying Results 1 - 19 of 19
  • [Front cover]

    Page(s): C1
    Save to Project icon | Request Permissions | PDF file iconPDF (337 KB)  
    Freely Available from IEEE
  • IEEE Transactions on Information Forensics and Security publication information

    Page(s): C2
    Save to Project icon | Request Permissions | PDF file iconPDF (131 KB)  
    Freely Available from IEEE
  • Table of contents

    Page(s): 1207 - 1208
    Save to Project icon | Request Permissions | PDF file iconPDF (129 KB)  
    Freely Available from IEEE
  • Table of contents

    Page(s): 1209 - 1210
    Save to Project icon | Request Permissions | PDF file iconPDF (126 KB)  
    Freely Available from IEEE
  • JPEG Anti-Forensics With Improved Tradeoff Between Forensic Undetectability and Image Quality

    Page(s): 1211 - 1226
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2845 KB) |  | HTML iconHTML  

    This paper proposes a JPEG anti-forensic method, which aims at removing from a given image the footprints left by JPEG compression, in both the spatial domain and DCT domain. With reasonable loss of image quality, the proposed method can defeat existing forensic detectors that attempt to identify traces of the image JPEG compression history or JPEG anti-forensic processing. In our framework, first because of a total variation-based deblocking operation, the partly recovered DCT information is thereafter used to build an adaptive local dithering signal model, which is able to bring the DCT histogram of the processed image close to that of the original one. Then, a perceptual DCT histogram smoothing is carried out by solving a simplified assignment problem, where the cost function is established as the total perceptual quality loss due to the DCT coefficient modification. The second-round deblocking and de-calibration operations successfully bring the image statistics that are used by the JPEG forensic detectors to the normal status. Experimental results show that the proposed method outperforms the state-of-the-art methods in a better tradeoff between the JPEG forensic undetectability and the visual quality of processed images. Moreover, the application of the proposed anti-forensic method in disguising double JPEG compression artifacts is proven to be feasible by experiments. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Collusion-Resistance in Optimistic Fair Exchange

    Page(s): 1227 - 1239
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1776 KB) |  | HTML iconHTML  

    Optimistic fair exchange (OFE) is a type of cryptographic protocols aimed at solving the fair exchange problem over open networks with the help of a third party to settle disputes between exchanging parties. It is well known that a third party is necessary in the realization of a fair exchange protocol. However, a fully trusted third party may not be available over open networks. In this paper, the security of most of the proposed OFE protocols depends on the assumption that the third party is semitrusted in the sense that it may misbehave on its own but does not conspire with either of the main parties. The existing security models of OFE have not taken into account the case where the potentially dishonest third party may collude with a signer in the sense of sharing its secret key with the signer. In this paper, to reduce the trust level of the arbitrator and increase the security of OFE, we propose an enhanced security model that, for the first time, captures this scenario. We also show a separation between the existing model and our enhanced model with a concrete counter example. Finally, we revisit two popular approaches in the construction of OFE protocols, which are based on verifiably encrypted signature and conventional signature plus ring signature, respectively. Our result shows that the conventional signature plus ring signature approach approach remains valid in our enhanced model. However, for schemes based on verifiably encrypted signature, slight modifications are needed to guarantee the security. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Joint Source-Relay Precoding and Power Allocation for Secure Amplify-and-Forward MIMO Relay Networks

    Page(s): 1240 - 1250
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1250 KB) |  | HTML iconHTML  

    In this paper, we investigate the security issue of a two-hop amplify-and-forward multiple-input multiple-output wireless relay network in the existence of a multiantenna eavesdropper. The optimal scheme to achieve the secrecy capacity involves a nonconvex optimization and is still an open problem. Aiming to find an efficient way to enhance the secrecy rate with a tractable complexity, we propose a suboptimal joint source and relay linear precoding and power allocation scheme. In the scheme, the source node adopts a generalized singular value decomposition (SVD)-based precoding to transmit the signal in the first phase, and the relay node forwards the received signal based on the SVD precoding in the null-space of the wiretap channel in the second phase. Power allocations in both phases are optimized to maximize the secrecy rate by an alternating iterative optimization algorithm. Each iteration involves two subproblems. One has a water-filling solution and the other has a closed-form solution or a water-filling-like solution as well, both of which are computationally very efficient. The iteration converges fast and we prove that it guarantees to find a stationary optimum. Furthermore, we show that when the eavesdropper has equal or more antennas than the source does, the secrecy rate is a quasi-concave function of the source power so that allocating all the source power is generally not optimal. Numerical evaluation results are provided to show the effectiveness of the iterative algorithm and the proposed secrecy scheme. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • On the Security of Trustee-Based Social Authentications

    Page(s): 1251 - 1263
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2291 KB) |  | HTML iconHTML  

    Recently, authenticating users with the help of their friends (i.e., trustee-based social authentication) has been shown to be a promising backup authentication mechanism. A user in this system is associated with a few trustees that were selected from the user's friends. When the user wants to regain access to the account, the service provider sends different verification codes to the user's trustees. The user must obtain at least k (i.e., recovery threshold) verification codes from the trustees before being directed to reset his or her password. In this paper, we provide the first systematic study about the security of trustee-based social authentications. In particular, we first introduce a novel framework of attacks, which we call forest fire attacks. In these attacks, an attacker initially obtains a small number of compromised users, and then the attacker iteratively attacks the rest of users by exploiting trustee-based social authentications. Then, we construct a probabilistic model to formalize the threats of forest fire attacks and their costs for attackers. Moreover, we introduce various defense strategies. Finally, we apply our framework to extensively evaluate various concrete attack and defense strategies using three real-world social network datasets. Our results have strong implications for the design of more secure trustee-based social authentications. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Investigation on Cost Assignment in Spatial Image Steganography

    Page(s): 1264 - 1277
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3066 KB) |  | HTML iconHTML  

    Relating the embedding cost in a distortion function to statistical detectability is an open vital problem in modern steganography. In this paper, we take one step forward by formulating the process of cost assignment into two phases: 1) determining a priority profile and 2) specifying a cost-value distribution. We analytically show that the cost-value distribution determines the change rate of cover elements. Furthermore, when the cost-values are specified to follow a uniform distribution, the change rate has a linear relation with the payload, which is a rare property for content-adaptive steganography. In addition, we propose some rules for ranking the priority profile for spatial images. Following such rules, we propose a five-step cost assignment scheme. Previous steganographic schemes, such as HUGO, WOW, S-UNIWARD, and MG, can be integrated into our scheme. Experimental results demonstrate that the proposed scheme is capable of better resisting steganalysis equipped with high-dimensional rich model features. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Incorporating Attack-Type Uncertainty Into Network Protection

    Page(s): 1278 - 1287
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2107 KB) |  | HTML iconHTML  

    Network security against possible attacks involves making decisions under uncertainty. Not only may one be ignorant of the place, the power, or the time of potential attacks, one may also be largely ignorant of the attacker's purpose. To illustrate this phenomenon, this paper proposes a simple Bayesian game-theoretic model of allocating defensive (scanning) effort among nodes of a network in which a network's defender does not know the adversary's motivation for intruding on the network, e.g., to bring the maximal damage to the network (for example, to steal credit card numbers or information on bank accounts stored there) or to infiltrate the network for other purposes (for example, to corrupt nodes for a further distributed denial of service botnet attack on servers). Due to limited defensive capabilities, the defender faces the dilemma of either: 1) focusing on increasing defense of the most valuable nodes, and in turn, increasing the chance for the adversary to sneak into the network through less valuable nodes or 2) taking care of defense of all the nodes, and in turn, reducing the level of defense of the most valuable ones. An explicit solution to this dilemma is suggested based on the information available to the defender, and it is shown how this information allows the authorities to increase the efficiency of a network's defense. Some interesting properties of the rivals' strategies are presented. Notably, the adversary's strategy has a node-sharing structure and the adversary's payoffs have a discontinuous dependence on the probability of the attack's type. This discontinuity implies that the defender has to take into account the human factor since some threshold values of this inclination in the adversary's behavior could make the defender's policy very sensitive to small perturbations, while in other situations it produces minimal impact. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Importance of Being Unique From Finger Dorsal Patterns: Exploring Minor Finger Knuckle Patterns in Verifying Human Identities

    Page(s): 1288 - 1298
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2376 KB) |  | HTML iconHTML  

    Automated biometrics identification using finger knuckle images has increasingly generated interest among researchers with emerging applications in human forensics and biometrics. Prior efforts in the biometrics literature have only investigated the major finger knuckle patterns that are formed on the finger surface joining proximal phalanx and middle phalanx bones. This paper investigates the possible use of minor finger knuckle patterns, which are formed on the finger surface joining distal phalanx and middle phalanx bones. The minor finger knuckle patterns can either be used as independent biometric patterns or employed to improve the performance from the major finger knuckle patterns. A completely automated approach for the minor finger knuckle identification is developed with key steps for region of interest segmentation, image normalization, enhancement, and robust matching to accommodate image variations. This paper also introduces a new or first publicly available database for minor (also major) finger knuckle images from 503 different subjects. The efforts to develop an automated minor finger knuckle pattern matching scheme achieve promising results and illustrate its simultaneous use to significantly improve the performance over the conventional finger knuckle identification. Several open questions on the stability and uniqueness of finger knuckle patterns should be addressed before knuckle pattern/image evidence can be admissible as supportive evidence in a court of law. Therefore, this paper also presents a study on the stability of finger knuckle patterns from images acquired with an interval of 4-7 years. The experimental results and the images presented in this paper provide new insights on the finger knuckle pattern and identify the need for further work to exploit finger knuckle patterns in forensics and biometrics applications. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • First Quantization Matrix Estimation From Double Compressed JPEG Images

    Page(s): 1299 - 1310
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2843 KB) |  | HTML iconHTML  

    One of the most common problems in the image forensics field is the reconstruction of the history of an image or a video. The data related to the characteristics of the camera that carried out the shooting, together with the reconstruction of the (possible) further processing, allow us to have some useful hints about the originality of the visual document under analysis. For example, if an image has been subjected to more than one JPEG compression, we can state that the considered image is not the exact bitstream generated by the camera at the time of shooting. It is then useful to estimate the quantization steps of the first compression, which, in case of JPEG images edited and then saved again in the same format, are no more available in the embedded metadata. In this paper, we present a novel algorithm to achieve this goal in case of double JPEG compressed images. The proposed approach copes with the case when the second quantization step is lower than the first one, exploiting the effects of successive quantizations followed by dequantizations. To improve the results of the estimation, a proper filtering strategy together with a function devoted to find the first quantization step, have been designed. Experimental results and comparisons with the state-of-the-art methods, confirm the effectiveness of the proposed approach. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Multiple Account Identity Deception Detection in Social Media Using Nonverbal Behavior

    Page(s): 1311 - 1321
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2372 KB) |  | HTML iconHTML  

    Identity deception has become an increasingly important issue in the social media environment. The case of blocked users initiating new accounts, often called sockpuppetry, is widely known and past efforts, which have attempted to detect such users, have been primarily based on verbal behavior (e.g., using profile data or lexical features in text). Although these methods yield a high detection accuracy rate, they are computationally inefficient for the social media environment, which often involves databases with large volumes of data. To date, little attention has been paid to detecting online deception using nonverbal behavior. We present a detection method based on nonverbal behavior for identity deception, which can be applied to many types of social media. Using Wikipedia as an experimental case, we demonstrate that our proposed method results in high detection accuracy over previous methods proposed while being computationally efficient for the social media environment. We also demonstrate the potential of nonverbal behavior data that exists in social media and how designers and developers can leverage such nonverbal information in detecting deception to safeguard their online communities. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Skull Identification via Correlation Measure Between Skull and Face Shape

    Page(s): 1322 - 1332
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2010 KB) |  | HTML iconHTML  

    Skull identification is an important subject for research in forensic medicine. Current research can be divided into two categories: 1) craniofacial superimposition and 2) craniofacial reconstruction. Both categories rely essentially on the accurate extraction and representation of the intrinsic relationship between the skull and face in terms of the morphology, which still remain unsolved. They have high uncertainty and a low identification capability. This paper proposes a novel skull identification method that matches an unknown skull with enrolled 3D faces, in which the mapping between the skull and face is obtained using canonical correlation analysis. Unlike existing techniques, this method needs no accurate relationship between the skull and face, and measures only the correlation between them. In order to measure the correlation more reliably and improve the identification capability of the correlation analysis model, a region fusion strategy is adopted. Experimental results validate the proposed method, and show that the region-based method can significantly boost the matching accuracy. The correct identification rate reaches 94% when using a CT data set. This paper can provide a theory support for research on craniofacial superimposition and craniofacial reconstruction. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • IEEE Transactions on Information Forensics and Security Edics

    Page(s): 1333
    Save to Project icon | Request Permissions | PDF file iconPDF (82 KB)  
    Freely Available from IEEE
  • IEEE Transactions on Information Forensics and Security information for authors

    Page(s): 1334 - 1335
    Save to Project icon | Request Permissions | PDF file iconPDF (135 KB)  
    Freely Available from IEEE
  • Special issue on Advances in Hyperspectral Data Processing and Analysis

    Page(s): 1336
    Save to Project icon | Request Permissions | PDF file iconPDF (236 KB)  
    Freely Available from IEEE
  • IEEE Signal Processing Society Information

    Page(s): C3
    Save to Project icon | Request Permissions | PDF file iconPDF (121 KB)  
    Freely Available from IEEE
  • [Blank page - back cover]

    Page(s): C4
    Save to Project icon | Request Permissions | PDF file iconPDF (5 KB)  
    Freely Available from IEEE

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
Chung C. Jay Kuo
University of Southern California