Network traffic flow can be represented as time series. Outliers of these time series is important for the computer network security. The existing methods for the time series anomaly detection mainly operate on the en...
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ISBN:
(数字)9781728160924
ISBN:
(纸本)9781728160931
Network traffic flow can be represented as time series. Outliers of these time series is important for the computer network security. The existing methods for the time series anomaly detection mainly operate on the entire time series to detect the abnormal series, seldom find out the position of the abnormal point. To solve this defect, we propose a method to discover the location of the outliers in time series based on a full convolutional network. We first map the time series into two-dimensional grayscale images by sliding window approach, and then feed them into the full convolutional network. In the classified stage, the feature maps of the last convolution layer are restored to the same size as the input image by up-sampling. Finally, we predict the class for each pixel and calculate the loss on a pixel-by-pixel basis. We tested the model on Yahoo Webscope S5 anomaly benchmark dataset, and the results show that our proposed method can achieve a mean pixel accuracy of 99.4% and mean IOU of 97% on the test dataset.
Comparing with the classic redundancy policy of multi-replica technology, Erasure code is preferred due to its higher utilization rate of storage space in distributed storage system. As one kind of the important Erasu...
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ISBN:
(数字)9781728160924
ISBN:
(纸本)9781728160931
Comparing with the classic redundancy policy of multi-replica technology, Erasure code is preferred due to its higher utilization rate of storage space in distributed storage system. As one kind of the important Erasure code, the traditional regeneration code with star recovery topology cost more time and more network bandwidth in the data recovery process. An efficient approach to reduce the delay time and network consumption is to construct an optimal recovery tree with the best possible bottleneck bandwidth, which is proved to be a Non-deterministic Polynomial problem. To solve this problem, this paper proposed a hybrid genetic algorithm which utilizes the designed crossover operation and mutation operation according to the problem property. A series of experiments have been conducted and the results show that our proposed method has good convergent ability and reduce the regeneration time.
Quantum key Distribution (QKD), based on fundamental principles of quantum mechanics, plays an irreplaceable role in national defense, financial and government affairs. Security analysis of QKD system is of great impo...
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A complex fuzzy set is a set whose membership grades are complex values in the unit circle in the complex plane. This paper introduces the concept of approximate parallelity between complex fuzzy sets based on the pha...
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In recent years, with the rapid development of the Internet, the data scale of application behavior and application traffic have exploded. How to classify the real-time traffic of network becomes a big challenge. How ...
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Due to the limitation of hardware resources, the traditional people flow monitoring system based on computer vision in public places can't meet different crowd-scale scenarios. Therefore, a people flow monitoring ...
Due to the limitation of hardware resources, the traditional people flow monitoring system based on computer vision in public places can't meet different crowd-scale scenarios. Therefore, a people flow monitoring system based on MD-MCNN algorithm is designed, which is an application system combining the improved SSD object detection algorithm MNSSD and MCNN density map regression algorithm. In the initial stage, the system uses MNSSD for accurate detection and counting. If the people flow gradually reaches a certain threshold, the system automatically uses MCNN to estimate people flow until the people flow falls below the threshold. Through the experimental verification, the system can realize the people flow statistics of low-density and high-density people in different scenarios, and can be applied on the existing embedded platform. This scheme can be extended to smart cities, smart scenic spots, smart transportation and other fields.
The mobile robot adapts to the more complicated indoor and outdoor environments, and can expand its scope of application. In order to reduce the influence of the cumulative error caused by navigation in complex enviro...
The mobile robot adapts to the more complicated indoor and outdoor environments, and can expand its scope of application. In order to reduce the influence of the cumulative error caused by navigation in complex environments, the indoor mobile robot that combines Inertial Measurement Unit (IMU) and encoder fusion is designed and implemented. In view of the limitations of the traditional single lidar scheme, a Multi-sensor Fusion scheme is proposed to achieve indoor map construction, path planning, multi-point navigation and other functions, and a MSIF KartoSLAM (Multi-sensor Information Fusion) algorithm is proposed, which combines the KartoSLAM algorithm and Multi-sensor information to achieve map construction in complex environments. Through comprehensive testing in the indoor environment, the results show that the Multi-sensor Fusion scheme is superior to the traditional single lidar scheme, and can achieve higher accuracy in mapping and navigation. At the same time, the robot platform can also be combined with the Internet of Things technology and integrated into intelligent housing system.
This treatise proposes a new algorithm of encrypting images by combining Sine map with generalized Arnold transformation. The algorithm adds a shift transformation link to the common permutation-diffusion structure. F...
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Synchronization of networked phase oscillators depends essentially on the correlation between the topological structure of the graph and the dynamical property of the elements. We propose the concept of ＇reduced freq...
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Synchronization of networked phase oscillators depends essentially on the correlation between the topological structure of the graph and the dynamical property of the elements. We propose the concept of ＇reduced frequency＇, a measure which can quantify natural frequencies of each pair of oscillators. Then we introduce an evolving network whose linking rules are controlled by its own dynamical property. The simulation results indicate that when the linking probability positively correlates with the reduced frequency, the network undergoes a first-order phase transition. Meanwhile, we discuss the circumstance under which an explosive synchronization can be ignited. The numerical results show that the peculiar butterfly shape correlation between frequencies and degrees of the nodes contributes to an explosive synchronization transition.
This paper is concerned with a stochastic HBV infection model with logistic growth. First, by constructing suitable stochastic Lyapunov functions, we establish sufficient conditions for the existence of ergodic statio...
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This paper is concerned with a stochastic HBV infection model with logistic growth. First, by constructing suitable stochastic Lyapunov functions, we establish sufficient conditions for the existence of ergodic stationary distribution of the solution to the HBV infection model. Then we obtain sufficient conditions for extinction of the disease. The stationary distribution shows that the disease can become persistent in vivo.
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