White-box cryptographic implementations often use masking and shuffling as countermeasures against key extraction attacks. To counter these defenses, higher-order Differential Computation Analysis (HO-DCA) and its variants have been developed. These methods aim to breach these countermeasures without needing reverse engineering. However, these non-invasive attacks are expensive and can be thwarted by updating the masking and shuffling techniques. This paper introduces a simple binary injection attack, aptly named clear & return, designed to bypass advanced masking and shuffling defenses employed in white-box cryptography. The attack involves injecting a small amount of assembly code, which effectively disables run-time random sources. This loss of randomness exposes the unprotected lookup value within white-box implementations, making them vulnerable to simple statistical analysis. In experiments targeting open-source white-box cryptographic implementations, the attack strategy of hijacking entries in the Global Offset Table (GOT) or function calls shows effectiveness in circumventing run-time countermeasures.

In this article, we propose a method called “continuous noise masking (cNM)” that allows eliminating residual buzziness in a continuous vocoder, i.e. of which all parameters are continuous and offers a simple and flexible speech analysis and synthesis system. Traditional parametric vocoders generally show a perceptible deterioration in the quality of the synthesized speech due to different processing algorithms. Furthermore, an inaccurate noise resynthesis (e.g. in breathiness or hoarseness) is also considered to be one of the main underlying causes of performance degradation, leading to noisy transients and temporal discontinuity in the synthesized speech. To overcome these issues, a new cNM is developed based on the phase distortion deviation in order to reduce the perceptual effect of the residual noise, allowing a proper reconstruction of noise characteristics, and model better the creaky voice segments that may happen in natural speech. To this end, the cNM is designed to keep only voice components under a condition of the cNM threshold while discarding others. We evaluate the proposed approach and compare with state-of-the-art vocoders using objective and subjective listening tests. Experimental results show that the proposed method can reduce the effect of residual noise and can reach the quality of other sophisticated approaches like STRAIGHT and log domain pulse model (PML).

This paper presents a low-power small-area-overhead physical random number generator utilizing SAR ADC embedded in sensor SoCs. An unpredictable random bit sequence is produced by an existing comparator in typical SAR ADCs, which results in little area overhead. Unlike the other comparator-based physical random number generator, this proposed technique does not require an offset calibration scheme since SAR binary search algorithm automatically converges the two input voltages of the comparator to balance the differential circuit pair. Although the randomness slightly depends on an quantization error due to sharing AD conversion scheme, the input signal distribution enhances the quality of random number bit sequence which can use for various security countermeasures such as masking techniques. Fabricated in 180nm CMOS, 1Mb/s random bit generator achieves high efficiency of 0.72pJ/bit with only 400μm2 area overhead, which occupies less than 0.5% of SAR ADC, while remaining 10-bit AD conversion function.

This paper proposes an address power reduction method for plasma display panels (PDPs) using subfield data smoothing based on a visual masking effect. High-resolution, high-frame-rate PDPs have large address power loss caused by parasitic capacitance. Although the address power is reduced by smoothing the subfield data, noise is generated. The proposed method reduces the address power while maintaining the image quality by choosing the smoothing area of the address data based on the visual masking effect. The results of subjective assessment for the images based on smoothed address data indicate that image quality is maintained.

As technology nodes continue to shrink, the impact of radiation-induced soft error on processor reliability increases. Estimation of processor reliability and identification of vulnerable flip-flops requires accurate soft error rate (SER) analysis techniques. This paper presents a proposal for a soft error propagation analysis technique. We specifically examine single event upset (SEU) occurring at a flip-flop in sequential circuits. When SEUs propagate in sequential circuits, the faults can be masked temporally and logically. Conventional soft error propagation analysis techniques do not consider error convergent timing on re-convergent paths. The proposed technique can analyze soft error propagation while considering error-convergent timing on a re-convergent path by combinational analysis of temporal and logical effects. The proposed technique also considers the case in which the temporal masking is disabled with an enable signal of the erroneous flip-flop negated. Experimental results show that the proposed technique improves inaccuracy by 70.5%, on average, compared with conventional techniques using ITC 99 and ISCAS 89 benchmark circuits when the enable probability is 1/3, while the runtime overhead is only 1.7% on average.

In this letter, a novel perceptually motivated single channel speech enhancement approach based on Deep Neural Network (DNN) is presented. Taking into account the good masking properties of the human auditory system, a new DNN architecture is proposed to reduce the perceptual effect of the residual noise. This new DNN architecture is directly trained to learn a gain function which is used to estimate the power spectrum of clean speech and shape the spectrum of the residual noise at the same time. Experimental results demonstrate that the proposed perceptually motivated speech enhancement approach could achieve better objective speech quality when tested with TIMIT sentences corrupted by various types of noise, no matter whether the noise conditions are included in the training set or not.

This letter presents a two-stage method to extend the degenerate unmixing estimation technique (DUET) for reverberant speech separation. First, frequency-bin-wise attenuation and delay parameters are introduced and estimated by online update rules, to handle early reflections. Next, a mask reestimation algorithm based on the precedence effect is developed to detect and fix the errors on binary masks caused by late reflections. Experimental results demonstrate that the proposed method improves separation performance significantly.

We propose an unsharp-masking technique which preserves the hue of colors in images. This method magnifies the contrast of colors and spatially sharpens textures in images. The contrast magnification ratio is adaptively controlled. We show by experiments that this method enhances the color tone of photographs while keeping their perceptual scene depth.

The applicability of at-speed scan-based logic built-in self-test (BIST) is being severely challenged by excessive capture power that may cause erroneous test responses even for good circuits. Different from conventional low-power BIST, this paper is the first to explicitly focus on achieving capture power safety with a novel and practical scheme, called capture-power-safe logic BIST (CPS-LBIST). The basic idea is to identify all possibly-erroneous test responses caused by excessive capture power and use the well-known approach of masking (bit-masking, slice-masking,vector-masking) to block them from reaching the multiple-input signature register(MISR). Experiments with large benchmark circuits and a large industrial circuit demonstrate that CPS-LBIST can achieve capture power safety with negligible impact on test quality and circuit overhead.

This paper presents a chosen-IV (Initial Vector) correlation power analysis on the international standard stream cipher KCipher-2 together with an effective countermeasure. First, we describe a power analysis technique which can reveal the secret key (initial key) of KCipher-2 and then evaluate the validity of the CPA with experiments using both FPGA and ASIC implementations of KCipher-2 processors. This paper also proposes a masking-based countermeasure against the CPA. The concept of the proposed countermeasure is to mask intermediate data which pass through the non-linear function part including integer addition, substitution functions, and internal registers L1 and L2. We design two types of masked integer adders and two types of masked substitution circuits in order to minimize circuit area and delay, respectively. The effectiveness of the countermeasure is demonstrated through an experiment on the same FPGA platform. The performance of the proposed method is evaluated through the ASIC fabricated by TSMC 65nm CMOS process technology. In comparison with the conventional design, the design with the countermeasure can be achieved by the area increase of 1.6 times at most.

NROM is one of the emerging non-volatile-memory technologies, which is promising for replacing current floating-gate-based non-volatile memory such as flash memory. In order to raise the fabrication yield and enhance its reliability, a novel test and repair flow is proposed in this paper. Instead of the conventional fault replacement techniques, a novel fault masking technique is also exploited by considering the logical effects of physical defects when the customer's code is to be programmed. In order to maximize the possibilities of fault masking, a novel data inversion technique is proposed. The corresponding BIST architectures are also presented. According to experimental results, the repair rate and fabrication yield can be improved significantly. Moreover, the incurred hardware overhead is almost negligible.

Fault-based attacks are very powerful to recover the secret key for cryptographic implementations. In this work, we consider the faulty output value under a certain fault injection intensity as a new type of leakage called faulty behavior. We examine the data-dependency of the faulty behavior and propose a related side-channel attack called fault behavior analysis (FBA). To verify the validity of the proposed attack, we first show that our attack can work effectively on AES-COMP of SASEBO-R. Then we show how to apply the similar attack on two AES implementations with masking countermeasures, i.e., AES-MAO and AES-TI. Finally we compare the proposed FBA attack with the DFA attack and the FSA attack, trying to complete the research map for the fault-based attack based on setup-time violations.

Incorporating insights from human visual perception into 3D object processing has become an important research field in computer graphics during the past decades. Many computational models for different applications have been proposed, such as mesh saliency, mesh roughness and mesh skeleton. In this letter, we present a novel Skeleton Modulated Topological Visual Perception Map (SMTPM) integrated with visual attention and visual masking mechanism. A new skeletonisation map is presented and used to modulate the weight of saliency and roughness. Inspired by salient viewpoint selection, a new Loop subdivision stencil decision based rapid viewpoint selection algorithm using our new visual perception is also proposed. Experimental results show that the SMTPM scheme can capture more richer visual perception information and our rapid viewpoint selection achieves high efficiency.

Mel Frequency Cepstral Coefficients (MFCC) are the most popular acoustic features used in automatic speech recognition (ASR), mainly because the coefficients capture the most useful information of the speech and fit well with the assumptions used in hidden Markov models. As is well known, MFCCs already employ several principles which have known counterparts in the peripheral properties of human hearing: decoupling across frequency, mel-warping of the frequency axis, log-compression of energy, etc. It is natural to introduce more mechanisms in the auditory periphery to improve the noise robustness of MFCC. In this paper, a k-nearest neighbors based frequency masking filter is proposed to reduce the audibility of spectra valleys which are sensitive to noise. Besides, Moore and Glasberg's critical band equivalent rectangular bandwidth (ERB) expression is utilized to determine the filter bandwidth. Furthermore, a new bandpass infinite impulse response (IIR) filter is proposed to imitate the temporal masking phenomenon of the human auditory system. These three auditory perceptual mechanisms are combined with the standard MFCC algorithm in order to investigate their effects on ASR performance, and a revised MFCC extraction scheme is presented. Recognition performances with the standard MFCC, RASTA perceptual linear prediction (RASTA-PLP) and the proposed feature extraction scheme are evaluated on a medium-vocabulary isolated-word recognition task and a more complex large vocabulary continuous speech recognition (LVCSR) task. Experimental results show that consistent robustness against background noise is achieved on these two tasks, and the proposed method outperforms both the standard MFCC and RASTA-PLP.

We present a simple technique for enhancing multi-modal images. The unsharp masking (UM) is at first nonlinearized to prevent halos around large edges. This edge-preserving UM is then extended to cross-sharpening of multi-modal images where a component image is sharpened with the aid of more clear edges in another component image.

This paper shows two power analysis attacks against a software implementation of a first-order DPA resistant S-box algorithm that is based on the discrete Fourier Transform (DFT). The DPA resistant S-box algorithm based on DFT was proposed by Prouff et al. in 2006 and improved by Coron et al. in 2008, respectively. In our attacks against the improved one, we pre-process the power traces by separating them into two subgroups, so that each has a biased mask. For the separated power traces, two post analysis methods are proposed to identify the key. One is based on DPA attack against one subgroup, and the other utilizes the difference of means for two subgroups and a pattern matching. Finally, we compare these two attack methods and propose an algorithm-level countermeasure to enhance the security of S-box calculation based on the DFT.

This paper presents a novel X-handling technique, which removes the effect of unknowns on compacted test response with maximal compaction ratio. The proposed method combines with the current X-tolerant compactors and inserts masking cells on scan paths to selectively mask X's. By doing this, the number of unknown responses in each scan-out cycle could be reduced to a reasonable level such that the target X-tolerant compactor would tolerate with guaranteed possible error detection. It guarantees no test loss due to the effect of X's, and achieves the maximal compaction that the target response compactor could provide as well. Moreover, because the masking cells are only inserted on the scan paths, it has no performance degradation of the designs. Experimental results demonstrate the effectiveness of the proposed method.

In this letter, we propose a speech reinforcement technique based on soft decision under both the far-end and near-end noise environments. We amplify the estimated clean speech signal at the far-end based on the estimated ambient noise spectrum at the near-end, as opposed to reinforcing the noisy far-end speech signal, so that it can be heard more intelligibly in far-end noisy environments. To obtain an effective reinforcement technique, we adopt the soft decision scheme incorporating a speech absence probability (SAP) in the frequency dependent signal-to-noise ratio (SNR) recovery method where the clean speech spectrum is estimated and the reinforcement gain is inherently derived and modified within the unified framework. Performance of the proposed method is evaluated by a subjective testing under various noisy environments. This is an improvement over previous approaches.

Cognitive radio (CR) is an adaptive spectrum sharing paradigm targeted to provide opportunistic spectrum access to secondary users for whom the frequency bands have not been licensed. The key tasks in a CR are to sense the spectral environment over a wide frequency band and allow unlicensed secondary users (CR users) to dynamically transmit/receive data over frequency bands unutilized by licensed primary users. Thus the CR transceiver should dynamically adapt its channel (frequency band) in response to the time-varying frequencies of wideband signal for seamless communication. In this paper, we present a low complexity reconfigurable filter architecture based on multi-band filtering and frequency masking techniques for dynamic channel adaptation in CR terminal. The proposed multi-standard architecture is capable of adapting to channels having different bandwidths corresponding to the channel spacing of time-varying channels. Design examples show that proposed architecture offers 12.2% power reduction and 26.5% average gate count reduction over conventional Per-Channel based architecture.

In this paper, a perceptually adaptive watermarking scheme for color images is proposed in order to achieve robustness and transparency. A new just noticeable distortion (JND) estimator for color images is first designed in the wavelet domain. The key issue of the JND model is to effectively integrate visual masking effects. The estimator is an extension to the perceptual model that is used in image coding for grayscale images. Except for the visual masking effects given coefficient by coefficient by taking into account the luminance content and the texture of grayscale images, the crossed masking effect given by the interaction between luminance and chrominance components and the effect given by the variance within the local region of the target coefficient are investigated such that the visibility threshold for the human visual system (HVS) can be evaluated. In a locally adaptive fashion based on the wavelet decomposition, the estimator applies to all subbands of luminance and chrominance components of color images and is used to measure the visibility of wavelet quantization errors. The subband JND profiles are then incorporated into the proposed color image watermarking scheme. Performance in terms of robustness and transparency of the watermarking scheme is obtained by means of the proposed approach to embed the maximum strength watermark while maintaining the perceptually lossless quality of the watermarked color image. Simulation results show that the proposed scheme with inserting watermarks into luminance and chrominance components is more robust than the existing scheme while retaining the watermark transparency.