nils-herrmann/clean_scirepeval huggingface dataset:
DCT-domain watermarking techniques for still images: detector performance analysis and a new structure

In this paper, a spread-spectrum-like discrete cosine transform (DCT) domain watermarking technique for copyright protection of still digital images is analyzed. The DCT is applied in blocks of 8x8 pixels, as in the JPEG algorithm. The watermark can encode information to track illegal misuses. For flexibility purposes, the original image is not necessary during the ownership verification process, so it must be modeled by noise. Two tests are involved in the ownership verification stage: watermark decoding, in which the message carried by the watermark is extracted, and watermark detection, which decides whether a given image contains a watermark generated with a certain key. We apply generalized Gaussian distributions to statistically model the DCT coefficients of the original image and show how the resulting detector structures lead to considerable improvements in performance with respect to the correlation receiver, which has been widely considered in the literature and makes use of the Gaussian noise assumption. As a result of our work, analytical expressions for performance measures, such as the probability of errors in watermark decoding and the probabilities of false alarms and of detection in watermark detection, are derived and contrasted with experimental results.
Fully homomorphic faces

Face recognition is a prominent application of image processing. It is also a very sensitive application, and privacy concerns have been lately raised and tackled in several recent papers dealing with privacy-preserving face recognition systems. Nevertheless, the presented systems either use the knowledge of some information derived from the database templates in order to perform the recognition or require several interaction rounds between client and server. In this paper, we propose a private system that can cope with a simple verification algorithm executed in the server without interaction (using a quasi-fully homomorphic encryption and an efficient face features representation with Lloyd-Max quantized Gabor jets), in which both the templates and the queried face are encrypted; we show its performance in terms of time complexity and size of transferred encryptions, as well as in verification accuracy with respect to the non-private system. This opens the door to completely private and noninteractive outsourcing of face recognition.
Rational dither modulation: a high-rate data-hiding method invariant to gain attacks

A novel quantization-based data-hiding method, called Rational Dither Modulation (RDM), is presented. This method retains most of the simplicity of the conventional dither modulation (DM) scheme, which is largely vulnerable to amplitude scalings and modifies it in such a way that the result becomes invariant to gain attacks. RDM is based on using a gain-invariant adaptive quantization step-size at both embedder and decoder. This causes the watermarked signal to be asymptotically stationary. Mathematical tools are used to determine the stationary probability density function, which is later used to assess the performance of RDM in Gaussian channels. It is also shown that by increasing the memory of the system, it is possible to asymptotically approach the performance of DM, still keeping invariance against gain attacks. RDM is compared with improved spread-spectrum methods, showing that the former can achieve much higher rates for the same bit error probability. Experimental results confirm the validity of the theoretical analyses given in the paper. Finally, a broader class of methods, that extends gain-invariance to quantization index modulation (QIM) methods, is also presented.
Hyperstable polyphase adaptive IIR filters

This work considers the implementation of recursive identification algorithms based on hyperstability concepts with polyphase structures. It is shown that the strictly positive real (SPR) condition required for convergence of these schemes can always be met by using a sufficiently high polyphase expansion factor M. For a given M, the degree of persistent excitation required for parameter convergence is obtained. When a priori knowledge about the unknown system is available, a compensating filter can be designed to avoid the need for a high M.
A Benford-Fourier JPEG compression detector

Intrinsic statistical properties of natural uncompressed images can be used in image forensics for detecting traces of previous processing operations. In this paper, we extend the recent theoretical analysis of Benford-Fourier coefficients and propose a novel forensic detector of JPEG compression traces in images stored in an uncompressed format. The classification is based on a binary hypothesis test for which we can derive theoretically the confidence intervals, thus avoiding any training phase. Experiments on real images and comparisons with state-of-art techniques show that the proposed detector outperforms existing ones and overcomes issues due to dataset-dependency.
A subspace-based policy enforcement method in dynamic spectrum leasing schemes

This paper proposes a real-time autonomous mechanism to enforce the fulfillment of the license by secondary users with spectrum sharing agreement in terms of throughput. Under a dynamic spectrum leasing (DSL) scenario where a primary user sublicenses spectrum usage to secondary users, in a dynamical fashion, it would be possible to find users that do not obey the specifications of their license. We propose a mechanism to enforce the policy determined by the primary, that limits and controls the throughput of a non-compliant secondary user, in such a way that his SINR will not grow if he transmits over the power it has been awarded to him by the legit owner. Assuming the primary assigns mutually orthogonal subspaces to compliant secondaries, punishment occurs through “de-orthogonalization”, increasing the cross-correlation in an asymmetrical way with the dishonest user subspace.
Quantization-Based Data Hiding Robust to Linear-Time-Invariant Filtering

Quantization-based methods, such as dither modulation (DM), have gained wide acceptance due to their host rejection capabilities which afford significant performance gains over spread-spectrum-based methods in additive white Gaussian channels. Unfortunately, existing quantization-based schemes are not robust against simple linear-time-invariant (LTI) filtering, which is a common operation with multimedia signals. We propose a new algorithm, named discrete Fourier transform-rational dither modulation (DFT-RDM) which is robust against LTI filtering and yet does not assume any prior knowledge of the filter at either the embedder or the detector. DFT-RDM basically combines a DFT operation with a quantization-based scheme robust to amplitude scaling. Two easily implementable improvements over the basic DFT-RDM are proposed: windowing and spreading. In particular, the latter leads to performance gains that are much larger than those achieved with spreading in regular DM. We also provide a thorough analysis of our scheme which leads to both accurate predictions and bounds on the per-DFT-channel bit-error rate, for the basic DFT-RDM and its combination with spreading and windowing. These tools let the designer choose the main embedding parameters without actually requiring any simulation. The results of several simulations for practical filters validating our analysis are presented as well. The benefits of combining DFT-RDM with windowing, spreading, and Reed-Solomon channel coding are illustrated with an example.
Analytical bounds on the error performance of the DVB-T system in time-invariant channels

We present an upper bound on the BER performance of the DVB-T system for time-invariant channels. A unified approach is taken comprising all feasible combinations of convolutional encoder rates and constellations, for both non-hierarchical and hierarchical transmission modes. The validity of the estimated BER is compared thoroughly with the simulated BER obtained with BerbeX, a DVB-T compliant software, for the three channels specified in the DVB-T standard.
Scheme for the integration of the evaluation of computer security for the recognition phase. Case study: Company in the Colombian accounting sector

Currently it is a relevant and public domain topic to companies, the serie of worldwide computer attacks against them which have impacted by theft of information and affected company's image. At this context, companies should implement actions to build their technological platform up. Among the strategies for this implementation are detection and analysis of possible vulnerabilities of information system. Several worldwide establishments have formulated initiatives such as guides and methodologies which establish guidelines for a methodical application of security tests; in this way, any company could have a course of action through validation of its exposure level of information assets. The objective of this paper is to present a security evaluation scheme which can be applied by small and medium companies. This is proposed from reviewing of security-analysis area references; the steps, techniques and tools are presented too. Then, the scheme is applied to an accounting advisory company and the obtained results are presented and discussed.
On the role of differentiation for resampling detection

Detection of resampling traces for digital image blind authentication has been addressed recently by A. C. Gallagher and later extended by B. Mahdian and S. Saic. On the other side, it is well known from the synchronization area in communications that prefiltering is an appropriate tool to improve the performance of those schemes exploiting the underlying cyclostationarity of communication signals. Thus, the detection of resampling manipulations improves significantly when the derivative of the interpolated signal is used for covariance computation. This work focuses on the role of prefiltering as a way of boosting resampling traces and, in particular, on the use of derivation.
Benford's Lawin Image Processing

We present a generalization of Benford's law for the first significant digit. This generalization is based on keeping two terms of the Fourier expansion of the probability density function of the data in the modular logarithmic domain. We prove that images in the discrete cosine transform domain closely follow this generalization. We use this property to propose an application in image steganalysis, namely, detecting that a given image carries a hidden message.
Gain-Invariant Dirty Paper Coding for Hierarchical OFDM

A novel approach is here presented to superimpose a low-priority data stream on a high-priority data stream for OFDM systems. The main improvement with respect to conventional hierarchical modulation, which is included with the same purpose in various wireless technologies, is that the low-priority data stream can be decoded from the received subcarrier symbols without any previous equalization for multipath fading channels. As a consequence, the expected performance is nearly invariant of the channel estimation method used to equalize the channel. The low-priority stream is inserted adopting a gain-invariant dirty paper coding based on Rational Dither Modulation, which was proposed for data hiding applications. In this paper an analysis of the developed system is presented and several simulations have been carried out using DVB-T system parameters to verify the validity of the proposed approach. The experimental results show the better performance of the proposed method with respect to that of a conventional hierarchical modulation, particularly when the accuracy of the estimated channel response decreases.
Two-dimensional statistical test for the presence of almost cyclostationarity on images

In this work, we study the presence of almost cyclostationary fields in images for the detection and estimation of digital forgeries. The almost periodically correlated fields in the two-dimensional space are introduced by the necessary interpolation operation associated with the applied spatial transformation. In this theoretical context, we extend a statistical time-domain test for presence of cyclostationarity to the two-dimensional space. The proposed method allows us to estimate the scaling factor and the rotation angle of resized and rotated images, respectively. Examples of the output of our method are shown and comparative results are presented to evaluate the performance of the two-dimensional extension.
Locating Tor hidden services through an interval-based traffic-correlation attack

Lately, research on low-latency communication systems has mainly focused on sender anonymity in order to bypass censorship. But we cannot disregard server anonymity, as it is a necessity to guarantee freedom-of-speech in many countries. For instance, the Electronic Frontier Foundation and Reporters Without Borders advise the use of Tor hidden services (HSes) to protect the safety of dissidents.
A Dirty Paper Scheme for Hierarchical OFDM

A novel approach is here presented to embed a low-priority data stream into a high-priority data stream for OFDM wireless communications. The main improvement with respect to conventional hierarchical modulations is that the low-priority data stream can be decoded from the received subcarrier symbols without any previous equalization in case of multipath fading channel. As a consequence, the expected performance is independent of the channel estimation method used to equalize the channel. The low-priority signal is superimposed on the high-priority symbols using a dirty paper coding technique. As a result of the analysis of the proposed method, several improvements to reduce the interference on the high-priority symbols are introduced. The performance of our scheme has been compared with that of a conventional hierarchical modulation using DVB-T system parameters, showing a considerable improvement for multipath fading channels.
Multiple JPEG compression detection by means of Benford-Fourier coefficients

The analysis of JPEG compressed images is one of the most studied problems in image forensics, because of the extensive use and the characteristic traces left by such coding operation. In this paper, we propose a novel statistical framework for the identification of previous multiple aligned compressions in JPEG images and the estimation of the quality factors applied. The method has been tested on different datasets and forensic scenarios, where up to three JPEG compressions are considered. Moreover, both in the case of double and triple JPEG encoding with different quality factors, the compression history of each image is estimated. The experiments show good performance and, in most cases, higher accuracies with respect to state-of-the-art methods.
Multivariate lattices for encrypted image processing

Images are inherently sensitive signals that require privacy-preserving solutions when processed in an untrusted environment, but their efficient encrypted processing is particularly challenging due to their structure and size. This work introduces a new cryptographic hard problem called m-RLWE (multivariate Ring Learning with Errors) extending RLWE. It gives support to lattice cryptosystems that allow for encrypted processing of multidimensional signals. We show an example cryptosystem and prove that it outperforms its RLWE counterpart in terms of security against basis-reduction attacks, efficiency and cipher expansion for encrypted image processing.
Rational dither modulation: a novel data-hiding method robust to value-metric scaling attacks

A novel quantization-based data-hiding method, named rational dither modulation (RDM), is presented. This method amounts to simple modifications of the well-known dither modulation (DM) scheme, which is largely vulnerable to scaling attacks. With such modifications, RDM becomes invariant to those attacks. Since RDM does not work by trying to estimate the step-size of the quantizers, it does not need any pilot-sequence. Moreover, RDM is suitable for a scalar operation, thus avoiding the cumbersome constructions of spherical codes. It is also shown that RDM approaches the performance of DM asymptotically with the size of the memory needed for the method to operate. Simulation results show the accuracy of our theoretical analysis and the superiority of RDM compared to the improved spread spectrum method.
Secure genomic susceptibility testing based on lattice encryption

Recent advances in Next Generation Sequencing have increased the availability of genomic data for more accurate analyses, like testing for the genetic susceptibility to a disease. Current laboratories' facilities cannot cope with this data growth, and genomic processing needs to be outsourced, comprising serious privacy risks. This work proposes an encrypted genomic susceptibility test protocol based on lattice homomorphic cryptosystems, and introduces optimizations like data packing and transformed processing to achieve considerable gains in performance, bandwidth and storage needs.
Performance analysis of a 2-D-multipulse amplitude modulation scheme for data hiding and watermarking of still images

A watermarking scheme for copyright protection of still images is modeled and analyzed. In this scheme a signal following a key-dependent two-dimensional multipulse modulation is added to the image for ownership enforcement purposes. The main contribution of this paper is the introduction of an analytical point of view to the estimation of performance measurements. Two topics are covered in the analysis: the ownership verification process, also called watermark detection test, and the data hiding process. In the first case, bounds and approximations to the receiver operating characteristic are derived. These results can be used to determine the threshold associated to a required probability of false alarm and the corresponding probability of detection. The data hiding process is modeled as a communications system and approximations for the bit error rate are derived. Finally, analytical expressions are contrasted with experimental results.
Statistical Analysis of a Linear Algebra Asymmetricwatermarking Scheme

We introduce a novel asymmetric watermarking scheme, involving a private key for embedding and a public key for detection, and we detail its statistical analysis, relying on Neyman-Pearson criterion. The proposed scheme solves part of the problems connected to previous watermarking approaches based on linear algebra. In particular, special attention is paid at reducing the side information required at the detector, as well as at achieving higher robustness by enphasizing the contribution of the watermark in the detection phase.
Understanding the effects of real-world behavior in statistical disclosure attacks

High-latency anonymous communication systems prevent passive eavesdroppers from inferring communicating partners with certainty. However, disclosure attacks allow an adversary to recover users' behavioral profiles when communications are persistent. Understanding how the system parameters affect the privacy of the users against such attacks is crucial. Earlier work in the area analyzes the performance of disclosure attacks in controlled scenarios, where a certain model about the users' behavior is assumed. In this paper, we analyze the profiling accuracy of one of the most efficient disclosure attack, the least squares disclosure attack, in realistic scenarios. We generate real traffic observations from datasets of different nature and find that the models considered in previous work do not fit this realistic behavior. We relax previous hypotheses on the behavior of the users and extend previous performance analyses, validating our results with real data and providing new insights into the parameters that affect the protection of the users in the real world.
Image denoising in the encrypted domain

The increasing advance of Cloud-based solutions brings about serious privacy problems when outsourcing images for their processing in untrusted environments. One of the fundamental privacy-aware image manipulations that can be outsourced is denoising, an ubiquitous signal processing primitive with a broad set of applications. Traditional Signal Processing in the Encrypted Domain solutions cannot efficiently address this problem, as they require interactive protocols in order to cope with polynomial operations and comparisons at the same time. We propose methods based on 2-RLWE (Ring Learning with Errors) to efficiently perform the whole image denoising operation on encrypted images in a fully non-interactive way; we show how to combine homomorphic polynomial operations and thresholding without involving decryption or interaction, therefore enabling fully unattended encrypted image processing. We evaluate our solutions for real image sizes and strict security parameters, showing their practicality and feasibility.
The Mystery Curve: A Signal Processing Point of View [Lecture Notes]

In the first chapter of a recently published book on artful mathematics , a linear combination of harmonic signals called mystery curves were introduced. Although their Fourier-based analysis brings interesting results, this lecture note provides a different and important perspective, especially useful for our signal processing community. Based on polar coordinate systems and low-pass filtering approaches, the patterns of the curves can be designed by locally curve tracing instead of trial and error, including not only two-dimensional (2-D) but also three-dimensional (3-D) modeling. Concrete examples and online MATLAB codes are provided so that applications from art and logo design to amplitude modulation (AM)-frequency modulation (FM) signal analysis are realizable.
Closed-form design of allpass fractional delay filters

In this paper, we propose a novel allpass (AP) fractional delay (FD) filter whose denominator polynomial is obtained by truncating the power series of a certain function. This function is derived from the frequency response of the denominator whose magnitude response is related to the desired. phase response through the Hilbert transform since the denominator of a stable AP filter is of minimum phase. The target function and corresponding power series are calculated. analytically and expressed in closed form. The closed-form expressions facilitate the analysis of stability. According to the properties for the coefficients of the denominator polynomial, we show that the proposed AP filter is stable for positive delay. Numerical examples indicate that the phase delays of the proposed filters are flat around ω = 0.
Tunable FIR and IIR Fractional-Delay Filter Design and Structure Based on Complex Cepstrum

A cepstrum-based approach is proposed to design finite- and infinite-impulse-response (IIR) fractional-delay (FD) filters. The maximal-flatness criteria on frequency responses are formulated as a system of linear equations to solve the truncated complex cepstrum. The closed-form solutions to cepstrum sequences can be derived. Moreover, it is very attractive that the resultant cepstrum coefficients are directly proportional to the desired FD. Under a fixed filter order, the set of normalized complex cepstra needs to be computed once and stored, and the specific set for an arbitrary FD is obtained by simply multiplying the stored set with the delay value. According to this observation, we also design two kinds of tunable filter structures consisting of several linear-phase filters, in which it is more flexible to obtain better performance by adding the extra substructure without modifying the present one. Moreover, the tunable FD is simply controlled by a single parameter, and the usage of linear-phase filters saves half of the multipliers, largely reducing the cost of hardware implementation. In addition, we obtain an IIR all-pass filter with a wider useful band than that based on Thiran's design.