This letter presents a new blind audio watermarking scheme using eigenvalue decomposition (EVD). Initially, the original audio is divided into frames and the samples of each frame are arranged into a square matrix. EVD is applied to each of these matrices. Watermark data is embedded into the largest eigenvalue of each diagonal matrix by quantization. Data embedding rate of the proposed scheme is 172.39bps. Simulation results confirm the imperceptibility of the proposed scheme and its higher robustness against various attacks compared to the state-of-the-art watermarking methods available in the literature.

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We present a dynamic key generation method, KeyQ, for establishing shared secret keys in EPCglobal Generation 2 (Gen2) compliant systems. Widespread adoption of Gen2 technologies has increased the need for protecting communications in these systems. The highly constrained resources on Gen2 tags limit the usability of traditional key distribution techniques. Dynamic key generation provides a secure method to protect communications with limited key distribution requirements. Our KeyQ method dynamically generates fresh secret keys based on the Gen2 adaptive Q algorithm. We show that the KeyQ method generates fresh and unique secret keys that cannot be predicted with probability greater than 10^-250 when the number of tags exceeds 100.

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The stability theory of stream ciphers plays an important role in designing good stream cipher systems. Two algorithms are presented, to determine the optimal shift and the minimum linear complexity of the sequence, that differs from a given sequence over F_q with period qⁿ-1 by one digit. We also describe how the linear complexity changes with respect to one digit differing from a given sequence.

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A method of round addition attack on substitution-permutation network (SPN) block ciphers using differential fault analysis (DFA) is presented. For the 128-bit advanced encryption standard (AES), we show that secret keys can be extracted using one correct ciphertext and two faulty ciphertexts. Furthermore, we evaluate the success rate of a round addition DFA attack, experimentally. The proposed method can also be applied to lightweight SPN block cipher such as KLEIN and LED.

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Misbehaving nodes intrinsic to the physical vulnerabilities of ad-hoc sensor networks pose a challenging constraint on the designing of data fusion. To address this issue, a statistics-based reputation method for reliable data fusion is proposed in this study. Different from traditional reputation methods that only compute the general reputation of a node, the proposed method modeled by negative binomial reputation consists of two separated reputation metrics: fusion reputation and sensing reputation. Fusion reputation aims to select data fusion points and sensing reputation is used to weigh the data reported by sensor nodes to the fusion point. So, this method can prevent a compromised node from covering its misbehavior in the process of sensing or fusion by behaving well in the fusion or sensing. To tackle the unexpected facts such as packet loss, a discounting factor is introduced into the proposed method. Additionally, Local Outlier Factor (LOF) based outlier detection is applied to evaluate the behavior result of sensor nodes. Simulations show that the proposed method can enhance the reliability of data fusion and is more accurate than the general reputation method when applied in reputation evaluation.

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As an ongoing video compression standard, High Efficiency Video Coding (HEVC) has achieved better rate distortion performance than H.264, but it also leads to enormous encoding complexity. In this paper, we propose a novel fast coding unit partition algorithm in the intra prediction of HEVC. Firstly, instead of the time-consuming rate distortion optimization for coding mode decision, just-noticeable-difference (JND) values can be exploited to partition the coding unit according to human visual system characteristics. Furthermore, coding bits in HEVC can also be considered as assisted information to refine the partition results. Compared with HEVC test model HM10.1, the experimental results show that the fast intra mode decision algorithm provides over 28% encoding time saving on average with comparable rate distortion performance.

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This image sharing method is a secure way of protecting the security of the secret images. In 2011, Wang et al. proposed an image sharing method with verification. The idea of the method is to embed the secret and the watermark images into two shares by two equations to achieve the goal of the secret sharing. However, the constructed shares are meaningless images which are difficult to manage. Authors utilize the algorithm of the torus automorphism to increase the security of the shares. However, the algorithm of the torus automorphism must take much time to encrypt and decrypt an image. This paper proposes a friendly image sharing method to improve the above problem. Experimental results show the significant efficiency of the proposed method.

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This paper proposes a method of improving the performance of blind reverberation time (RT) estimation in noisy environments. RT estimation is conducted using a maximum likelihood (ML) method based on the autocorrelation function of the linear predictive residual signal. To reduce the effect of environmental noise, a noise reduction technique is applied to the noisy speech signal. In addition, a frequency coefficient selection is performed to eliminate signal components with low signal-to-noise ratio (SNR). Experimental results confirm that the proposed method improves the accuracy of RT measures, particularly when the speech signal is corrupted by a colored noise with a narrow bandwidth.

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It is shown that an infinite lumped-element LC- ladder network generates all Bessel functions J_n(t) of the first kind as a response to a single non-zero initial condition. Closed-form expressions for the voltage responses in the time domain are presented if the LC- ladder is driven by a step-like input voltage.

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