Semisupervised Encrypted Traffic Identification Based on Auxiliary Classification Generative Adversarial Network

The rapidly increasing popularity of mobile devices has changed the methods with which people access various network services and increased network traffic markedly. Over the past few decades, network traffic identification has been a research hotspot in the field of network management and security monitoring. However, as more network services use encryption technology, network traffic identification faces many challenges. Although classic machine learning methods can solve many problems that cannot be solved by port- and payload-based methods, manually extract features that are frequently updated is time-consuming and labor-intensive. Deep learning has good automatic feature learning capabilities and is an ideal method for network traffic identification, particularly encrypted traffic identification; Existing recognition methods based on deep learning primarily use supervised learning methods and rely on many labeled samples. However, in real scenarios, labeled samples are often difficult to obtain. This paper adjusts the structure of the auxiliary classification generation adversarial network (ACGAN) so that it can use unlabeled samples for training, and use the wasserstein distance instead of the original cross entropy as the loss function to achieve semisupervised learning. Experimental results show that the identification accuracy of ISCX and USTC data sets using the proposed method yields markedly better performance when the number of labeled samples is small compared to that of convolutional neural network (CNN) based classifier.     

Parallel source separation system for heart and lung sounds

The Journal of Supercomputing - In this paper, we propose a parallel source separation system designed to extract heart and lung sounds from single-channel mixtures. The proposed system is based on...     

Trajectory tracking control for underactuated unmanned surface vehicle subject to uncertain dynamics and input saturation

Neural Computing and Applications - In this paper, one concerns with the problem of trajectory tracking control for an underactuated unmanned surface vehicle subject to uncertain dynamics and input...     

基于正切图像处理(TIP)模型的自适应图像增强算法

针对图像增强算法复杂度高、对噪声敏感等问题,在分析对数图像处理模型的基础上,提出了一种基于正切图像处理模型的自适应图像增强算法,该算法具有实现容易、运算速度快等特点,对噪声具有一定的抑制作用,可以增强和保留图像细节信息。既可以增强灰度图像,又可以增强彩色图像,实验和理论分析说明了该算法的优越性。     

Customer knowledge discovery from online reviews

The explosive growth of Chinese electronic market has made it possible for companies to better understand consumers?? opinion towards their products in a timely fashion through their online reviews. This study proposes a framework for extracting knowledge from online reviews through text mining and econometric analysis. Specifically, we extract product features, detect topics, and identify determinants of customer satisfaction. An experiment on the online reviews from a Chinese leading B2C (Business-to-Customer) website demonstrated the feasibility of the proposed method. We also present some findings about the characteristics of Chinese reviewers.     

The analysis of global input-to-state stability for piecewise affine systems with time-delay

In this paper, global input-to-state stability (ISS) for discrete-time piecewise affine systems with time-delay are considered. Piecewise quadratic ISS-Lyapunov functions are adopted. Both Lyapunov-Razumikhin and Lyapunov-Krasovskii methods are used. The theorems of Lyapunov-Razumikhin type and Lyapunov-Krasovskii type for piecewise affine systems with time-delay are shown, respectively.     

Hysteresis Compensation and Adaptive Controller Design for a Piezoceramic Actuator System in Atomic Force Microscopy

This paper presents an indirect adaptive controller combined with hysteresis compensation to achieve high accuracy positioning control of piezoceramic actuators and illustrates the results with an atomic force microscope (AFM) application. A dynamic model of a piezoceramic actuator system in AFM is derived and analyzed. A feedforward controller based on the Preisach model is proposed to compensate for the nonlinear hysteresis effects. Then an indirect adaptive controller is designed to achieve desired tracking performance as well as deal with the uncompensated nonlinearity from hysteresis and the system parameter variation due to creep. Experimental results indicate that the proposed controller can significantly improve the positioning control accuracy of the piezoceramic actuator as well as achieve high image quality of the AFM system. The maximum scanning error was reduced from 2µm to 0.3µm in comparison with a proportional‐integral‐derivative (PID) controller. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

New constructions of OSBE schemes and their applications in oblivious access control

Oblivious signature-based envelope (OSBE) schemes have demonstrated their potential applications in the protection of users privacy and rights. In an OSBE protocol, an encrypted message can only be decrypted by the receiver who holds a valid signature on a public message, while the sender (encrypter) does not know whether the receiver has the signature or not. Our major contributions in this work lie in the following aspects. We improve the notion of OSBE so that a valid credential holder cannot share his/her credential with other users (i.e., all-or-nothing non-transferability). We clarify the relationship between one-round OSBE and identity-based encryption (IBE) and show that one-round OSBE and semantically secure IBE against the adaptively chosen identity attack (IND-ID-CPA) are equivalent, if the signature in the OSBE scheme is existentially unforgeable against adaptively chosen message attacks. We propose an oblivious access control scheme to protect user privacy without the aid of any zero-knowledge proof. Finally, we also highlight some other novel applications of OSBE, such as attributed-based encryption.     

A Brief Introduction on Joint Radar and Communication Systems

Joint radar and communication(JRC) technology is gradually becoming an essential approach to alleviating spectral congestion. Radar and communications systems were designed with common spectral and hardware resources to reduce size, improve performance, reduce cost, and decongest the spectrum. Various approaches have been proposed to achieve the coexistence of radar and communication systems. This paper mainly focuses on the research directions of radar communication coexistence(RCC) and dual-function radar communication systems(DFRC) in JRC technology. We summarize and analyze the existing research problems in the JRC era. According to the characteristics and advantages of JRC technology, we highlight several potentials in military and commercial applications.