A novel quantum information hiding protocol based on entanglement swapping of high-level Bell states

Using entanglement swapping of high-level Bell states, we first derive a covert layer between the secret message and the possible output results of the entanglement swapping between any two generalized Bell states, and then propose a novel high-efficiency quantum information hiding protocol based on the covert layer. In the proposed scheme, a covert channel can be built up under the cover of a high-level quantum secure direct communication （QSDC） channel for securely transmitting secret messages without consuming any auxiliary quantum state or any extra communication resource. It is shown that this protocol not only has a high embedding efficiency but also achieves a good imperceptibility as well as a high security.

Application of Big Data in Agricultural Informationization in Shandong Province under the Background of "Internet +"

This paper explains the basic concepts of " Internet + " and big data,analyzes the main problems in the application of big data technology in agricultural informationization of Shandong Province,summarizes corresponding solutions from the aspects of government guidance,financial input,open sharing of agricultural big data,big data storage and processing,data mining,etc.,and prospects the application trend of big data technology in agricultural informationization to achieve the connotative development of agriculture in Shandong Province.

Empirical Evaluation of Information Leakage Detection Using Net-flow Analysis

Because of the widespread of Trojans,organizations and Internet users become more vulnerable to the threat of information leakage.This paper describes an information leakage detection system( ILDS) to detect sensitive information leakage caused by Trojan.In particular,the principles of the system are based on the analysis of net-flows in four perspectives: heartbeat behavior analysis,DNS abnormal analysis,uploaddownload ratio and content analysis.Heartbeat behavior analysis and DNS abnormal analysis are used to detect the existence of Trojans while upload-download ratio and content analysis can quickly detect when the information leakage happens.Experiments indicate that the system is reliable and efficient in detecting information leakage.The system can also help to collect and preserve digital evidence when information leakage incident occurs.

Physiological Analysis of Drought Resistance of Seven Cultivars Spring Wheat in Northern Regions of China

In order to determine the physiological mechanism of drought resistance of northern wheat in China,six drought resistant wheat and one sensitivity to drought wheat were planted in pots.They were subjected to drought treatment and normal water when the plants grew to the 3-leaf stage.Samples were collected at 10,20,30,and 40 days after the drought treatment,respectively.The electrical conductivity,photosynthetic parameters,chlorophyll fluorescence parameters,sugar content,proline content,protein content,and active oxygen scavenging enzyme activity of the plants were detected,and the agronomic traits of the wheat varieties were investigated at maturity.The results indicated that the phenotype and yield-related factors of Darkhan 144 changed little under the drought stress.The relative electrical conductivity of Kefeng 6 and Darkhan 166 was lower under the drought stress,and their cell membrane was less damaged.The Darkhan 144 and Darkhan 166 had higher drought resistance coefficients,and were the wheat varieties with stronger drought resistance.However,the physiological mechanisms of drought resistance of these three wheat were different:Darkhan 144 maintained a higher photosynthetic activity under the drought stress;Darkhan 166 maintained a higher protein content,photosynthetic activity and active oxygen scavenging enzyme activity.In addition,other drought-resistant varieties Kefeng 6,Kefeng 10 and Longmai 26 had a higher content of osmoregulatory substances under the drought stress.

Walsh Spectral Characteristics and the Auto-Correlation Function Characteristics of Forming Orthomorphic Permutations of Multi-Output Functions

Orthomorphic permutations have good characteristics in cryptosystems. In this paper, by using of knowledge about relation between orthomorphic permutations and multi-output functions, and conceptions of the generalized Walsh spectrum of multi-output functions and the auto-correlation function of multi-output functions to investigate the Walsh spectral characteristics and the auto-correlation function characteristics of orthormophic permutations, several results are obtained.

Moving target defense of routing randomization with deep reinforcement learning against eavesdropping attack

Eavesdropping attacks have become one of the most common attacks on networks because of their easy implementation. Eavesdropping attacks not only lead to transmission data leakage but also develop into other more harmful attacks. Routing randomization is a relevant research direction for moving target defense, which has been proven to be an effective method to resist eavesdropping attacks. To counter eavesdropping attacks, in this study, we analyzed the existing routing randomization methods and found that their security and usability need to be further improved. According to the characteristics of eavesdropping attacks, which are “latent and transferable”, a routing randomization defense method based on deep reinforcement learning is proposed. The proposed method realizes routing randomization on packet-level granularity using programmable switches. To improve the security and quality of service of legitimate services in networks, we use the deep deterministic policy gradient to generate random routing schemes with support from powerful network state awareness. In-band network telemetry provides real-time, accurate, and comprehensive network state awareness for the proposed method. Various experiments show that compared with other typical routing randomization defense methods, the proposed method has obvious advantages in security and usability against eavesdropping attacks.

2-D DIRECTION FINDING OF COHERENT SIGNALS VIA TEMPORO-SPATIAL PROCESSING

In most wireless communication systems, two-dimensional Directions-Of-Arrival (DOA) of multipath signals need to be found for spatial selective transmission. However, it is quite difficult to find their DOAs due to the coherent nature of multipath signals and considerable computations when performing 2-D searches. In this paper, a new algorithm to estimate 2-D DOA of multiple narrow-band signals is proposed. A DOA cyclic matrix is constructed whose eigenvalues and eigenvectors can be simultaneously used to extract 2-D DOA without 2-D searches. By exploiting the temporal property of cyclostationarity, the signal detection capability is significantly improved. Besides, based on the decorrelation model for mobile terminal signals, the algorithm can be effectively extended to the coherent case without spatial smoothing and the loss of array aperture. Simulation results are given to illustrate the performance of the new algorithm.

A Practical Intrusion Detection System for Internet of Vehicles

Internet of Vehicles(henceforth called IoV) is a public network system and high-value target for intrusions that may cause efficiency issues, privacy leakages or even physical damage. Conventional intrusion detection methods are normally designed for the Internet infrastructures which cannot directly apply in the context of IoV. This work proposes an FPGA based intrusion detection method that can not only achieve real-time scanning performance but also be applied in vehicular environment. We evaluate our scheme on a Xilinx FPGA based platform. Experiments show that the proposed system can achieve a throughput of more than 39 Gbps on existing FPGA platform which is about 15% higher than state-of-the-art techniques,and the total power consumption for the prototype is about 7.5 w. Moreover, the processing latency of the prototype is about 4 us and is about one sixtieth part of the popular software IDS systems.

40 Hz Auditory Steady State Response to Linguistic Features of Stimuli during Auditory Hallucinations

The auditory steady state response （ASSR） may reflect activity from different regions of the brain, depending on the modulation frequency used. In general, responses induced by low rates （_〈40 Hz） emanate mostly from central structures of the brain, and responses from high rates （〉80 Hz） emanate mostly from the peripheral auditory nerve or brainstem structures. Besides, it was reported that the gamma band ASSR （30-90 Hz） played an important role in working memory, speech understanding and recognition. This paper investigated the 40 Hz ASSR evoked by modulated speech and reversed speech. The speech was Chinese phrase voice, and the noise-like reversed speech was obtained by temporally reversing the speech. Both auditory stimuli were modulated with a frequency of 40 Hz. Ten healthy subjects and 5 patients with hallucination symptom participated in the experiment. Results showed re- duction in left auditory cortex response when healthy subjects listened to the reversed speech compared with the speech. In contrast, when the patients who experienced auditory hallucinations listened to the reversed speech, the auditory cortex of left hemispheric responded more actively. The ASSR results were consistent with the behavior results of patients. Therefore, the gamma band ASSR is expected to be helpful for rapid and objective diagnosis of hallucination in clinic.

Walsh Spectrum Properties of Rotation Symmetric Boolean Function

Rotation symmetric function was presented by Pieprzyk. The algebraic configuration of rotation symmetric（RotS） function is special. For a Rots n variables function f（x1, x2, …, xn） we have f（ρn^k （x1, x2, …xn））=f（x1, x2, …, xn） for k=0, 1, …, n-1. In this paper, useing probability method we find that when the parameters of RotS function is under circular translation of indices, its walsh spectrum is invariant. And we prove the result is both sufficient and necessary.

Spatio-Temporal Distribution of Individual Filaments in a Square Superlattice Pattern in Atmospheric Dielectric Barrier Discharge

Spatio-temporal distribution of individual filament in a square superlattice pattern, which consists of large and small spots （filaments）, is studied in atmospheric dielectric barrier discharges. The spatial distributions of the two discharges for individual large filament along the direction perpendicular to the electrode are estimated by the distributions of light signals along the electrode. It is found that the discharge at the rising edge of the applied voltage is with a wider column, weaker current, and longer current pulse duration in comparison with that at the falling edge

Construction of General (k, n) Probabilistic Visual Cryptography Scheme

Visual cryptography scheme （VCS） is a secure method that encrypts a secret image by subdividing it into shadow images. Due to the nature of encryption VCS is categorized into two types： the deterministic VCS （DVCS） and the probabilistie VCS （PVCS）. For the DVCS, we use m （known as the pixel expansion） subpixels to represent a secret pixel. The PVCS uses only one subpixel to represent a secret pixel, while the quality of reconstructed image is degraded. A well-known construction of （k, n）-PVCS is obtained from the （k, n）-DVCS. In this paper, we show another construction of （k, n）-PVCS by extending the （k, k）-PVCS.

An Effective Differential Fault Analysis on the Serpent Cryptosystem in the Internet of Things

Due to the strong attacking ability, fast speed, simple implementation and other characteristics, differential fault analysis has become an important method to evaluate the security of cryptosystem in the Internet of Things. As one of the AES finalists, the Serpent is a 128-bit Substitution-Permutation Network(SPN) cryptosystem. It has 32 rounds with the variable key length between 0 and 256 bits, which is flexible to provide security in the Internet of Things. On the basis of the byte-oriented model and the differential analysis, we propose an effective differential fault attack on the Serpent cryptosystem. Mathematical analysis and simulating experiment show that the attack could recover its secret key by introducing 48 faulty ciphertexts. The result in this study describes that the Serpent is vulnerable to differential fault analysis in detail. It will be beneficial to the analysis of the same type of other iterated cryptosystems.

Detection of Coal Mine Spontaneous Combustion by Fuzzy Inference System

The spontaneous combustion is a smoldering process and characterized by a slow burning speed and a long duration. Therefore, it is a hazard to coal mines. Early detection of coal mine spontaneous combustion is quite difficult because of the complexity of different coal mines. And the traditional threshold discriminance is not suitable for spontaneous combustion detection due to the uncertainty of coalmine combustion. Restrictions of the single detection method will also affect the detection precision in the early time of spontaneous combustion. Although multiple detection methods can be adopted as a complementarity to improve the accuracy of detection, the synthesized method will in- crease the complicacy of criterion, making it difficult to estimate the combustion. To solve this problem, a fuzzy inference system based on CRI （Compositional Rule of Inference） and fuzzy reasoning method FITA （First Infer Then Aggregate） are presented. And the neural network is also developed to realize the fuzzy inference system. Finally, the effectiveness of the inference system is demonstrated bv means of an experiment.

L^2(R^n) BOUNDEDNESS FOR COMMUTATORS OF OSCILLATORY SINGULAR INTEGRAL OPERATORS

The commutators of oscillatory singular integral operators with homogeneous kernel $\frac{{\Omega (x)}}{{\left| x \right|^n }}$ are studied, where Ω is homogeneous of degree zero, has mean value zero on the unit sphere. It is proved that Ω∈L (logL)K+1(Sn-1) is a sufficient condition under which the k-th order commutator is bounded on L2(Rn).

A brief overview of traditional Chinese medicine prescription powered by artificial intelligence

Traditional Chinese medicine prescription is one of the treasures of traditional Chinese medicine(TCM).There are tens of thousands TCM prescriptions accumulated in the past thousands of years,corresponding to different diseases,symptoms and therapeutic goals.The correspondences are so complicated that there is an urgent need to leverage new technologies such as artificial intelligence(AI)to analyze,understand and utilize them effectively.In this paper,we present a brief overview of this direction,where current research progress on TCM prescription powered by AI is summarized.Our summarization focuses on three aspects,TCM prescription mining that aims at understanding the TCM prescription,TCM prescription or herb knowledge base construction that aims at extracting knowledge to support the TCM prescription-related study,and TCM prescription discovery that aims at utilizing AI technologies to further energize TCM.It is encouraging to see that steady progress in this direction has been made recently.Besides,a toy experiment on image-based TCM herb recognition by using convolutional neural networks is also conducted.It basically verifies that it is promising to use AI technologies to address challenging tasks in TCM.We also point out several research topics that could be cooperatively performed by researchers from the two disciplines.

The Study of Image Segmentation Based on the Combination of the Wavelet Multi-scale Edge Detection and the Entropy Iterative Threshold Selection

This paper proposes an image segmentation method based on the combination of the wavelet multi-scale edge detection and the entropy iterative threshold selection.Image for segmentation is divided into two parts by high- and low-frequency.In the high-frequency part the wavelet multiscale was used for the edge detection,and the low-frequency part conducted on segmentation using the entropy iterative threshold selection method.Through the consideration of the image edge and region,a CT image of the thorax was chosen to test the proposed method for the segmentation of the lungs.Experimental results show that the method is efficient to segment the interesting region of an image compared with conventional methods.

Cluster Observation of Eelectrostatic Solitary Waves around Magnetic Null Point in Thin Current Sheet

Electrostatic solitary waves （ESWs） are observed in the vicinity of the magnetic null of the widely studied magnetic reconnection taking place at the near-earth tail when current sheet becomes dramatic thinning during substorm time on 1 October 2001. We use the Imada method for the 2-D reconnection model and study the characteristics of ESWs near the X-line region and the magnetic null points. The result shows that the amplitude of the observed ESWs in the vicinity of X-line region ranges from 0.1mV/m to 5mV/m, and the amplitude is larger near the magnetic null points. The generation mechanism and the role of ESWs associated with magnetic reconnection are also discussed.