Abstract:User data security and privacy preserving has been becoming one of the most crucial issues in cloud computing environment, where cryptographic technologies are taken as a useful solution to achieve these goals. Nowadays, secure data searching and sharing and differential privacy preserving have attracted much more attention. This paper reviews the state-of-the-art in the field of ciphertext search, ciphertext sharing and differential privacy, and identifies their inappropriateness. Then, a series of recent research results in ciphertext search and ciphertext sharing are presented. In the respect of ciphertext search，this paper introduces the encrypted spatial keyword searth method, which achieves lightweight access control and efficient keyword search. In the respect of ciphertext sharing, this paper proposes the cross-cryptosystem fine-grained data sharing scheme, in which a data owner can formulate an access policy such that the part of encrypted data satisfying the access policy can be shared with the users in a different cryptosystem. Finally, this paper provides several open research issues and the trend in the future.

Abstract:Compressed sensing is a new signal processing theory focusing on data sampling compression and reconstruction. In recent years, researchers have applied deep learning to image compressed sensing algorithms, which significantly improves the quality of the recovered images. However, images are often associated with personal privacy, and high-quality recovered images often bring privacy protection problems while facilitating people's viewing. Based on deep neural network, this paper proposes an image compressed sensing algorithm with adversarial learning. This method integrates data compression and adversary sample technique into the compressed sensing algorithm. By training the neural network with a loss function combining reconstruction loss and classification loss, the output samples, i.e., the recovered images, become adversarial samples. The recovered images with our proposed algorithm can then be adversarial to image classifications algorithms, decreasing their recognition rate and achieving the performance of protecting image privacy while guaranteeing a reasonable image quality. Experimental results on Cifar-10 and MNIST show that, compared with the existing compressed sensing methods, the proposed adversarial algorithm achieves excellent adversarial performance, as the classification accuracy is decreased by 74% at the cost of 10% loss of image reconstruction quality.

Abstract:Steganography is one of the main methods for covert communication, while mobile phones are the most commonly used communication devices. The combination of the two has high practical significance. In recent years, steganography has developed rapidly with deep learning technologies. To improve the performance, networks evolve towards a more complex and large style, which gradually deviates from the real world scenarios with covert communication as the core, resulting in low practicability. For convenience and efficiency, a lightweight image steganography method is proposed for mobile phone. The network structure is designed in a light style, with depthwise separable convolutions utilized to reduce useless parameters and keeping a balance between accuracy and speed. Based on generative adversarial networks, the proposed method consists of a generator, a decoder, and a discriminator, which are trained together defiantly and finally advance in a spiral upward trend. To deal with various challenges in the real world, the model is deployed on mobile phones for tests. The networks used on smartphones are pruned, which indicates performance degradation. To ameliorate this problem and enhance decoding accuracy, BCH correcting codes are used in the method. The results show that the method can generate high-quality images with high speed, which meets the convenience requirements in today’s world. Besides，it’s worth noting that the method works without online requests. All the embedding and extracting tasks can be done by phone itself, which means this scheme is immune to eavesdropping attacks.

Abstract:Reversible data hiding for medical image contrast enhancement can not only store patient information imperceptibly, but also improve image contrast quality to facilitate the accurate diagnosis in the remote medical affairs. In this paper, a new reversible data hiding algorithm for medical image contrast enhancement is proposed. The medical image is segmented by the superpixel algorithm, and then the modifications on the region of the interest (ROI) of the image are optimized. Since the image is divided into blocks, the embedded regions can be selectively modified block by block according to their statistical characteristics. Subsequently, the modification of each pixel block applies the classical histogram modification manner, and embeds the payload into multiple embedding points at one time. We take the histogram equalization as the optimization goal, and then reduce the embedding distortion in the process of contrast enhancement. Experimental results show that when compared with the state-of-the-art methods, the proposed method is reversible and can improve the visual quality of medical images in terms of contrast enhancement.

Abstract:Aiming at the problems of low steganographic capacity, difficult information extraction, and poor security in existing information hiding algorithms, this paper proposes a high capacity information hiding algorithm based on GAN（HCGAN）. For secret information embedding, an Im-Residual structure-based encoder is applied to embed the secret information into the carrier image, avoiding the information loss caused by the feature extraction of the convolution layer. For secret information extraction, a dense structure-based decoder is utilized to extract secret information from the secret image, and feature reuse is used to increase the extraction rate of secret information. In terms of anti-steganalysis, the discriminator based on steganalysis and the encoder based on Im-Residual structure are used for adversarial training to improve the anti-steganalysis ability of the secret image. Experiments show that after adversarial training, HCGAN has a lower steganalysis detection rate at an embedding rate of 2bpp than the WOW and S-UNIWARD algorithms at an embedding rate of 0.4bpp.

Abstract:Existing research shows that although many cryptographic systems have passed the conventional security performance tests, they have been proved to be able to crack the sensitive information of the cryptographic system by side channel attacks. A chaotic cryptographic system is designed to resist side-channel attacks. Two chaotic maps are used to generate the round key and the random sequence number, respectively, and the intermediate data is generated by the plaintext, the round key, and the random sequence number through the XOR operation so as to enlarge the key space. In addition, the random sequence number also controls the randomization operation. The relationship between intermediate data and power consumption is hidden via the randomization operation. In this way, the leakage of side channel information is reduced, thus to resist the power analysis attack. In order to evaluate the security of the designed cryptographic system, first of all, it is routinely tested through character frequency test, information entropy test and dependency test. The experimental results show that the system has good security performance. In addition, the encryption algorithm is implemented on the Atmel XMEGA128 chip. Experimental results show that the proposed cryptosystem can defend against correlation power analysis.

Abstract:Most of the current source code vulnerability detection methods only rely on a single feature, and the single dimension of characterization results in inefficient methods. To address the above issues, a vulnerability detection method based on structured text and code metrics is proposed to detect vulnerabilities at the function-level granularity. Using source code structured text information and code metrics as features, long-term dependencies in structured text information are captured by constructing a self-attention based neural network to fit the relationship between structured text and the existence of vulnerabilities and translate them into the probability of vulnerabilities. The deep neural network is used to learn the characteristics of the results of code metrics to fit the relationship between code metrics and the existence of vulnerabilities, and the fitted results are transformed into the probability of vulnerabilities. Support Vector Machine (SVM) is used to further classify the probabilities of vulnerabilities obtained by the above two representations and obtain the final results of vulnerability detection. To verify the vulnerability detection performance of this method, 11 source code samples with different types of vulnerabilities are tested. The average detection accuracy of this method for each vulnerability is 97.96%. Compared with the existing vulnerability detection methods based on a single representation, this method improves the detection accuracy by 4.89%~12.21%, and at the same time. the false positive and false negative rates of this method are kept within 10%.

Abstract:：With the high integration of informatization and industrialization, the degree of intelligence and automation of the secondary system of substations has been continuously enhanced. While enjoying the convenience, we also need to face the challenges and threats brought by the Internet. In view of the confidentiality, integrity and other security threats that the secondary system applications or tools may face during the calculation and transmission process, the enhanced security terminal protection technology based on the USB interface has become a research hotspot. Although the traditional enhanced security terminal equipment is easy to produce, the algorithms in it have been specified by the manufacturer and downloaded to the corresponding equipment. Considering that the security requirements of different scenarios are quite different, and different users have multi-level security requirements, the AVR microcontroller is programmed through the Arduino IDE platform, and an enhanced security terminal equipment with general algorithms is designed and implemented, which not only realizes functions such as identity authentication and content encryption, but also meets the personalized needs of users' independent choices and improves the security and controllability of the entire secondary system. After the test, the usability and robustness of the terminal are preliminarily proved.

Abstract:To solve the problems that the existing software system abnormal status evaluation methods over depend on data labeling and pay less attention to the time dependence of time-series data, and then it is difficult to quantify the software system abnormal status. Thus, a software system abnormal status evaluation method based on the hybrid generative network is proposed. Firstly, by combining the long short-term memory network (LSTM) and the variational auto-encoder (VAE), an anomaly detection model based on LSTM-VAE hybrid generative network is designed. The features of the system time-series data are extracted by LSTM and its distribution is modeled by VAE. Then, the LSTM-VAE anomaly detection model detects the software system key feature parameters and obtains the anomaly metric value of system key feature parameters. Finally, the coupling degree method is used to optimize the linear weighted sum method. According to the weighted coupling degree method which is optimized, the software system abnormal status quantitative value is calculated, and the software system abnormal status is evaluated. The experimental results show that the proposed model has a better detection ability for the abnormal time-series data of the software system, and its system abnormal status evaluation result is more feasible and effective.

Abstract:System logs are used as the primary data source for system anomaly detection.??Existing log anomaly detection methods mainly use log event data extracted from historical logs to build detection models, that is, the distribution of log data is assumed to be stable over time.??However, in practice, log data often contains events or sequences that have not occurred before.??The instability comes from two sources: 1) conceptual drift occurs in logs;??2) noise is introduced during log processing.??In order to alleviate the problem of instability in logs, an anomaly detection model called Ensemble-Based Conformal Anomaly Detection (EBCAD) based on confidence degree and multiple algorithms is designed.??Firstly, the p-value statistics are used to measure the non-conformity between logs, and multiple appropriate ensemble algorithms are selected as the non-conformity measure functions to calculate the non-conformal scores for collaborative detection.??Then, an update mechanism based on confidence is designed to alleviate the problem of log instability. By adding scores of new logs into existing sets, the experiences of log anomaly detection are updated. Finally, according to the confidence degree and the preset significance level obtained by collaborative detection, the unstable log is judged to be abnormal.??The experimental results show that when the unstable data injection rate increases from 5% to 20% in HDFS log data set, the F1-score of EBCAD model only decreases from 0.996 to 0.985.??In the BGL_100K log data set, when the unstable data injection rate increases from 5% to 20%, the F1-score of EBCAD decreases only from 0.71 to 0.613.??This proves that EBCAD can effectively detect anomalies in unstable logs.

Abstract:：Aiming at the problem of fatigue driving state recognition in traffic safety, the recognition rate of using a single fatigue driving feature is low. This paper studies and proposes a fatigue recognition method based on the weighted sum of facial multi-features. The eye fatigue parameters, such as continuous eye closing time, eye closing frame ratio and blink frequency, are extracted by human eye state detection algorithm. The number and duration of yawning are obtained through yawning state detection, the nodding frequency is obtained through head motion state analysis, and a driving fatigue state detection model integrating the above six characteristics is established to evaluate the driver’s fatigue level and give the corresponding early warning. The experimental test data are selected from part of the NTHU driver fatigue detection video data set. After experimental adjustment, it is found that this method has high recognition accuracy and provide a good recognition effect.

Abstract:Aiming at the problem of limited available energy and serious information leakage risks faced by the relay nodes in the multi-antenna relay system, a physical layer secure transmission scheme of joint relay beamforming and multi-antenna friendly jammer cooperative jamming based on energy harvesting technology is proposed. Firstly, a multi-antenna cooperative relay network based on the amplify-and-forward (AF) mode is constructed. Secondly, the relay nodes and friendly jammers perform energy harvesting and confidentiality signal transmission based on the time switching (TS) strategy. Then, with the goal of the system secrecy rate maximization（SRM），the optimal relay signal transmission beamforming matrix，artificial noise（AN） covariance and time switching coefficient are jointly designed under the condition of meeting the energy harvesting constraints of the relay and the friendly jammers. However, due to conditional constraints, the SRM problem is a non-convex. Therefore, a Bi-level optimization algorithm is designed to obtain the optimal solution by combining semi-definite relaxation（SDR） technology and Lagrange duality theory, and in order to reduce the complexity and compare the performance of the proposed scheme, a suboptimal transmission scheme based on zero-forcing precoding is given. Finally, the simulation results show that the proposed scheme can significantly improve the security performance of the system and has a certain anti-eavesdropping attack capability.

Abstract:Given the low quality and efficiency of situation element extraction in network security situation awareness techniques, this paper proposes a situation element identification model incorporating particle swarm optimization and simulated annealing (PSO-TSA). In the position update module, the Metropolis criterion is utilized to optimize the individual and global extremum in the PSO algorithm to increase the selectivity of the particles and improve the quality of the situation elements extraction. In the parameter optimization module, the parameters in the PSO algorithm are optimized using the Metropolis criterion, and the parameter optimization process and particle fitness are evaluated simultaneously to rid the local optimum and improve the efficiency of the situation element recognition. Due to the actual needs of the current network state, this paper selects 37 network security data fields and establishes a small network environment to obtain a more realistic network security dataset SDS-W. This paper conducts experiments of the situation element recognition on the open cybersecurity dataset and the SDS-W, respectively. Experiments show that PSO-TSA improves the accuracy of situation element recognition by an average of 5% to 7% while the time cost remains the same or even less.

Abstract:Virtual synchronous control is widely studied in port shore power sources to enhance system inertia and damping, but there may be control interaction between the port shore power source and the ship PWM rectifier load. Thus, firstly, according to the multi-time scale control characteristics, a frequency-division dq-frame impe- dance model of the port shore power source with virtual synchronous control is proposed. Secondly, the stability analyses based on the established dq-frame impedance and generalized Nyquist stability criterion show that there is a control interaction between the AC voltage loop of port shore power source and the DC voltage loop of ship PWM rectifier load, inducing the system oscillation. Increasing the AC voltage proportional and resonance gain of port shore power source or reducing the DC voltage proportional gain of ship PWM rectifier load can enhance the stability of the port shore power supply system. Finally, the effectiveness of the impedance model and stability analysis results are verified by the experimental results based on the hardware in the loop experimental platform.

Abstract:Ice and snow accretion on transmission lines seriously threatens the secure and stable operation of the power system. Current research focuses on the discharge development and flashover characteristics of snow-covered insulators. Due to the complexity of the insulator, the growth of snow accumulation remains a lack of systematic analysis. In this paper, based on computational fluid dynamics (CFD), the local impact characteristics of snow particles on XP-70 insulator were simulated and analyzed under different environmental parameters, subsequently, a three-dimensional numerical calculation model was established. The results show that there are two opposite processes during flow around an insulator, namely, the pressure decrease accompanied by the increase of the velocity as well as the increase of the pressure with the decreasing velocity. Local collision coefficient on the windward side of the insulator gradually decreases along with the steel or the shed from the front stagnation point to both sides. The coefficient at the edge of the shed and the steel cap of the windward side of the insulator is much higher than that of other positions, and the maximum value can reach 0.74. Snow accumulation on the insulator increases with the increase of v，liquid water content (LWC) and median volume diameter (MVD). Its maximum is 2.19 kg. It is verified by the simulation and test that snow accretion is the heaviest at the location where the local collision coefficient is the largest, and the error between the two is less than 17%.

Abstract:The high power microwave (HPM) can entered into the equipment by the antennas of radar and electronic warfare equipment . A good coupling ability and large peak amplitude of this coupling method lead to a greater probability to cause electromagnetic interference or damage to the equipment. As a result, it is necessary to investigate the HPM damage effects to electronic devices as well as the protective measures. In this paper, as there are few researches on high-power microwave effects at the equipment level, an X-band microwave receiver front-end is taken as an equipment under test (EUT), and the injection experiment is carried out to study the high power microwave damage effects. The effect phenomena and data are obtained. The results show that when the limiter is protected, a single HPM pulse with an amplitude of 48.8 dBm can cause damage to the low-noise amplifier of the microwave receiver front-end. If an amplitude limiter is employed in the receiving circuit, the threshold of damage HPM power needs to be increased to 60.7 dBm and the number of pulses can be increased to 100. It also reveals that energy deposition is the necessary condition for performing damage. Both a narrow microwave pulse with relatively high peak power and a series of wide pulses with relatively low high peak power can cause fatal damage to the sensitive devices. The damage effect can be enhanced if the key parameters of the HPM weapon are optimized, i.e., the peak power, the pulse width and the number of pulses. Furthermore, the attacking distance and mechanism of the typical HPM power weapons are also discussed, which is helpful for effect evaluation as well as protection design for radar and electronic warfare equipment.

Abstract:The visual remote sensing monitoring system of tidal flat resources is conductive to their scientific monitoring and protection. However, the current remote sensing monitoring system of tidal flat resources has some problems, such as insufficient correlation of spatial and attribute information, low system reusability and scalability. Combined with the visual display requirements of tidal flat resources, this study optimizes the system. In the aspect of GIS entity management, this paper puts forward the mapping design idea and object-oriented design principle based on GML, which realizes the dynamic management of GIS objects and attributes. In the aspect of layer management, a GIS entity presentation based on MapObject component is proposed to realize the conversion of various vector data and grid data. In the aspect of system design, the plug-in technology is used to realize the encapsulation and reuse of system functions. The dynamic monitoring and visual display of Jiangsu coastal tidal flat resources are well realized, which is of great significance for the protection and the high-quality development of marine tidal flat resources.

Abstract:In order to control the surface quality of arc edge of the cemented carbide blade, a grinding mechanical model was established by analyzing the relationship between the contact length of a single abrasive particle and the work-piece and the maximum thickness of undeformed chip. Based on the orthogonal experiment method, the machining experiments of the carbide tool with different grinding parameters were carried out, and the saw tooth depth and surface roughness of the tool arc surface were observed by VHX-600 ultra-deep field optical microscope and other observation instruments. Based on the grinding mechanical model and experimental machining results of the arc blade, as well as the saw tooth forming mechanism, the saw tooth and roughness of the arc blade affected by different grinding parameters, blade material and structure were analyzed. The results show that the surface quality and tool durability can be improved by increasing wheel speed, reducing arc rotation speed, reducing grinding depth, controlling the quality of blade material and designing blade structure reasonably. The grinding effect is better when the grinding speed of the wheel is 24m/s, the speed of the wheel is 8°/s, and the grinding depth is 0.05mm, and meanwhile, the grinding force, serrations and surface roughness are smaller.

Abstract:A new type of vibration isolator is proposed by using a two-layer variable-bar length X-type mechanism in order to achieve the design objectives of the isolator with low dynamic stiffness and high damping. Firstly, the harmonic balance method is used to obtain the stationary analytical solution of the established mechanical model for the vibration isolation system, and the amplitude-frequency response, phase-frequency response, equivalent stiffness, equivalent damping and force transfer rate of the vibration isolation system are given respectively. Then, according to the force transmissibility, the vibration isolation performance is compared with conventional linear vibration isolator and quasi-zero stiffness vibration isolator. At the same time, the finite element analysis is carried out to verify the validity of the analytical solution. Finally, the influence law of the system parameters on the vibration isolation performance of the new type vibration isolator is analyzed and given. The results show that when compared with the conventional linear isolators, the new isolators have smaller dynamic stiffness and higher damping output, and when compared with the quasi-zero stiffness isolators, the new isolator not only can guarantee low stiffness and high damping output, but also has better stability and static bearing capacity. The design parameters of the vibration isolation system have a greater impact on the vibration isolation performance. Various design parameters of the vibration isolation system can be flexibly adjusted to meet different vibration isolation requirements.

Abstract:In order to solve the problem of poor heat dissipation effect of a certain type of truck crane, the principle of its hydraulic system was studied. According to the heat generation and heat dissipation characteristics of the main components, the mathematical model of heat balance of the hydraulic system was established. Based on the software AMESim, a simulation model of the thermal hydraulic system of the truck crane in the no-load state of the engine was established, and the accuracy of the simulation model was verified by comparing the temperature of the radiator inlet and outlet. The pressure loss characteristics of four pumps under high speed no-load condition were analyzed. The results show that the energy loss of No. 2 pump is the largest, about 38%. The heat generated by the energy loss of the multi-way valve and the center rotating body is the main heat source of the hydraulic system. No. 3 pump and No. 4 pump return oil heat production are also large, but because the original design of the return oil is not cooled, resulting in a poor overall heat dissipation effect of the hydraulic system of the truck crane. By introducing the return oil of the rotary system and the control system into the radiator, the improved multi-way valve outlet temperature is reduced, and the outlet temperature of the oil tank is also significantly reduced, which improves the heat dissipation effect of the hydraulic system. The improvement is reasonable and effective, and provides guidance for improving the thermal management and control strategy of the hydraulic system of the truck crane in the future.

Abstract:The mathematical simulation of gas-liquid two-phase flow of the proton exchange membrane (PEM) fuel cell under mechanical stress was studied. In this study, a two-dimensional, non-isothermal two-phase flow Multiphysics steady-state model of PEM fuel cells was established. The model comprehensively considered the solid mechanics, electrochemistry, heat and mass transfer and gas-liquid two-phase flow. The two-phase flow distribution of PEM fuel cells under mechanical stress was studied. The computational results showed that the stress of the porous medium under ribs was significantly greater than the stress under the flow channel. Stress concentration obviously occurred at the junction of the ribs and the flow channel. Liquid water was only condensed at the cathode and mainly formed in the porous medium under the ribs. As the current density increased, the cathode relative humidity gradually increased, however, the relative humidity of the anode decreased. Cathode liquid water saturation increased when current density increased.

Abstract:In order to accelerate the landing of the autonomous valet parking system, a novel autonomous valet parking path planning method is proposed based on the improved fast marching tree algorithm. Firstly, a breadth-first-search-like strategy is used to establish the "path field" of the environmental map, and an obstacle avoidance detection strategy with high computational efficiency is proposed. A selection principle of the far and near reference points and an update principle of the path node based on the "path field" of environmental map are proposed to conform to the vehicle non-holonomic constraint. According to the above proposed strategies and principles, the path node is gradually close to the target node to complete the autonomous valet parking guidance path planning task. Then, on the basis of the Dubins curve, the parking path which meets the arbitrary requirement of the initial vehicle parking azimuth and the non-uniqueness requirement of the parking space azimuth angle is planned to guide the vehicle to enter the parking space safely. Finally, the feasibility of the proposed method is verified by simulation, and the results show that when compared with the traditional fast marching algorithm, the planned autonomous valet parking path based on the proposed method meets the requirement of the vehicle non-holonomic constraint and can guide the vehicle to complete the task of autonomous valet parking.

Abstract:Building type and built year are critical parameters to infer archetype buildings for urban building en? ergy modeling（UBEM）. Currently，it is difficult to directly obtain these data for most cities. For the building type identification，taking 21 538 building footprints（without a point of interest and community boundary information）in Changsha City as an example，this paper used the random forest algorithm to successfully identify low-rise resi? dences，apartment residences，and other types based on the geometric characteristics，with an overall accuracy of 81.7%. For the determination of built year，7 900 building footprints in the downtown area of Changsha were selected as a case study，and this paper applied the convolutional neural network algorithm to automatically extract building footprints from different historical satellite imageries，with an average precision of 80%. Then，the intersection analy? sis showed that 5 077 buildings were built before 2005，1 606 buildings were built from 2005 to 2014，and 1 217 buildings were built from 2015 to 2017. The proposed method can be easily applied to other cities，and provide data support for UBEM in the future.

Abstract:Personal comfort systems（PCS）are commonly used in residential buildings in hot summer and cold winter zone，such as infrared heaters，foot warmers，local air heaters and so on. In order to explore the characteris? tics of thermal comfort under the action of personal comfort system，Hangzhou City was selected as the object，and the questionnaire survey，field test and laboratory test. The results showed that the PCS was used more than 50% of the characteristics of thermal comfort of residents under the action of personal comfort system in winter were studied bytime from late December to early February，with peak use between 18：00 and 20：00 on a typical day. Local operating temperature around the human body can be increased by 2.7℃ on average by the PCS. Under the action of the PCS，neutral operating temperature is 15.8 ℃. From the perspective of comfort and energy saving，the operating tem? perature around the human body is suggested to controlled at 13.9 ~ 20 ℃. The body parts with significant sensation of heat feeling under the action of PCS are the head，hands and feet. The optimal skin temperature of each part was obtained as 33℃ for the head，37℃ for the front chest，35℃ for the upper arm，36℃ for the back，37℃ for the abdo? men，36℃ for the lower arm，31℃ for the hand，36℃ for the thigh，38℃ for the calf，and 35℃ for the foot. It pro? vided a basis for the quantitative demand study of the residents′ personal heating equipment to improve their thermal comfort in winter.