Privacy amplification (PA) is a vital step in the postprocessing stage of quantum key distribution, which can extract a secure key from a source partially leaked to the environment. We propose a PA scheme that uses th...
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Privacy amplification (PA) is a vital step in the postprocessing stage of quantum key distribution, which can extract a secure key from a source partially leaked to the environment. We propose a PA scheme that uses the square hash (SQH)–modular arithmetic hash (MH) function. In consideration of a potential quantum attacker, we use the trace distance as a metric to measure the closeness between two classical-quantum states. We transform a raw key state to a processed state using this scheme and derive the trace distance between the processed state and the ideal target state. It is proven that the trace distance can be reached as small as desired. Additionally, our approach accelerates the SQH-MH function through the number-theoretic transform, reducing the computational complexity to O(nlog n). On the basis of a CPU, a maximum throughput rate of 1.06 Gbit/s is achieved, and the results show that our algorithm demonstrates good stability of the throughput rate when handling tasks with different compression ratios.
Wideband spectrum sensing is a fundamental problem in cognitive radio networks. In this paper, a wideband spectrum sensing procedure which consists of four steps, i.e., coarse support recovery, fine binary detection, ...
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Cognitive Radio (CR) is considered as an effective technology for alleviating the spectrum shortage problem by enabling secondary users to utilize vacant spectrum allocated to a primary user (PU). IEEE 802.22 which is...
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The division property of a multiset,which is a generalization of the integral property,was proposed by Todo[1]at EUROCRYPT *** division property can precisely depict the implicit properties between ALL and BALANCE pro...
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The division property of a multiset,which is a generalization of the integral property,was proposed by Todo[1]at EUROCRYPT *** division property can precisely depict the implicit properties between ALL and BALANCE properties,it allows us to efficiently construct integral distinguisher even if the round function of the block cipher is non-bijective,bit-oriented,and low-degree.
Different from traditional secure communication that focuses on symbolic protection at the physical layer, semantic secure communication requires further attention to semantic-level task performance at the application...
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Packet analysis is very important in our digital life. But what protocol analyzers can do is limited because they can only process data in determined format. This paper puts forward a solution to decode raw data in an...
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Packet analysis is very important in our digital life. But what protocol analyzers can do is limited because they can only process data in determined format. This paper puts forward a solution to decode raw data in an unknown format. It is certain that data can be cut into packets because there are usually characteristic bit sequences in packet headers. The key to solve the problem is how to find out those characteristic sequences. We present an efficient way of bit sequence enumeration. Both Aho-Corasick (AC) algorithm and data mining method are used to reduce the cost of the process.
High frequency(HF) communication is widely spread due to some merits like easy deployment and wide communication coverage. Spectrum prediction is a promising technique to facilitate the working frequency selection and...
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High frequency(HF) communication is widely spread due to some merits like easy deployment and wide communication coverage. Spectrum prediction is a promising technique to facilitate the working frequency selection and enhance the function of automatic link establishment. Most of the existing spectrum prediction algorithms focus on predicting spectrum values in a slot-by-slot manner and therefore are lack of timeliness. Deep learning based spectrum prediction is developed in this paper by simultaneously predicting multi-slot ahead states of multiple spectrum points within a period of time. Specifically, we first employ supervised learning and construct samples depending on longterm and short-term HF spectrum data. Then, advanced residual units are introduced to build multiple residual network modules to respectively capture characteristics in these data with diverse time scales. Further, convolution neural network fuses the outputs of residual network modules above for temporal-spectral prediction, which is combined with residual network modules to construct the deep temporal-spectral residual network. Experiments have demonstrated that the approach proposed in this paper has a significant advantage over the benchmark schemes.
Full-duplex, which aims to simultaneously transmitting and receiving over the same band, together with phased array antennas play fundamental roles in next-generation wireless communication systems. The combination of...
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To deeply understand the essential relationship between two different-frequency signals and explore the phase synchronization law in frequency standard comparison, a novel modeling building method of Lissajous figure ...
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To deeply understand the essential relationship between two different-frequency signals and explore the phase synchronization law in frequency standard comparison, a novel modeling building method of Lissajous figure reversal period is proposed based on the group quantization phase processing. The relationships between the Lissajous figure reversal period and group period are revealed. The frequency deviation and nominal frequency of the measured signal are obtained using the group period and number of inflection point in the Lissajous figure. The results of a frequency standard comparison can accurately achieved using the frequency deviation. A lot of noise problems introduced by the frequency divider, frequency multiplier and frequency mixer are solved in the traditional frequency standard comparison, and the high-precision frequency standard comparison results can be quickly obtained using the proposed method. The experimental results show that a close relationship exists among the Lissajous figure reversal period, group period and frequency *** measured frequency can be precisely calculated using the relationship, and the frequency stability of system can reach the E-112/s level.
Bitcoin, which was initially introduced by Nakamoto, is the most disruptive and impactive cryptocurrency. The core Bitcoin technology is the so-called blockchain protocol. In recent years, several studies have focused...
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Bitcoin, which was initially introduced by Nakamoto, is the most disruptive and impactive cryptocurrency. The core Bitcoin technology is the so-called blockchain protocol. In recent years, several studies have focused on rigorous analyses of the security of Nakamoto’s blockchain protocol in an asynchronous network where network delay must be considered. Wei, Yuan, and Zheng investigated the effect of a long delay attack against Nakamoto’s blockchain protocol. However, their proof only holds in the honest miner setting. In this study, we improve Wei, Yuan and Zheng’s result using a stronger model where the adversary can perform long delay attacks and corrupt a certain fraction of the miners. We propose a method to analyze the converge event and demonstrate that the properties of chain growth, common prefix, and chain quality still hold with reasonable parameters in our stronger model.
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