Journal of China Universities of Posts and Telecommunications最新文献

The software protection technology is the main component of modern software security technology. Generally, confusion and encryption methods are using in software protection technology to provide traditional desktop applications. But applications based on mobile devices are also faces with threats such as piracy and tampering. The security problem in existing applications for mobile devices will do far more harm to users than traditional virus, but there is no effective software protection security framework for them. A software application framework for mobile devices is proposed in this paper, and the white box decryption algorithm involved is improved. And it is analyzed in this paper the performance and security of the framework proposed, the operational efficiency of the improved encryption algorithm is verified.

A real-time method is proposed to detect faces in videos. First it uses frame difference method to extract the motion area. Next the clustering character of skin is used to get the general face area. AdaBoost algorithm is applied to make concrete detection of human face. Finally an improved CamShift algorithm method is used to keep the tracking and improving algorithm speed. The experiments demonstrate the robustness and high speed of the proposed algorithm.

High recognition rate of multi-class pattern recognition is difficult to obtain, especially when the feature extraction is not ideal. So achieving a high recognition rate with nonideal feature extraction makes great sense. Based on the early study of multiple-set-compete method (MSCM) and the algorithm of result reliability, this article proposes a new recognition method named group match competition method (GMCM). The GMCM precedes the early work with a larger scope of applications. Early work which the authors did can only deal with the recognition work with the number of powers of 2 classes, while GMCM can cope with the classes of any number. This article further illustrates the MSCM, the algorithm of result reliability and their functions in the GMCM. Three sets of cases are demonstrated and formats of grouping are discussed. The recognition results show that the GMCM is a robust method and it is capable of achieving the high recognition rate of the multi-class pattern recognition.

With the raising challenges of the Internet of things (IoT), e.g. the giant-scale heterogeneous network elements, and the uncertainty of sensing information and the dynamic environment that the system resides, there is no complete and widely accepted theory. In this paper, a hormone-based service detection algorithm (HSDA) for detecting the service requests generated randomly in the IoT is proposed. Inspired by the endocrine mechanism in human body, the nodes in the network without centralized command or sinks can tune themselves spontaneously by exchanging information among regional neighbors through different hormones. A dynamic activation scheme is realized as the HSDA to guarantee the rapidness of the network on responding the service requests. Simulation results show that the HSDA algorithm entitles the network with intelligent decision-making and cooperative working abilities, based on which the stability of the network and the effectiveness for detecting service requests generated randomly can be guaranteed simultaneously.

During recently years, several OpenFlow-enabled testbeds have been deployed in world-wide research community. Typically, these OpenFlow-enabled testbeds need to stitch to other testbeds to link to virtual servers and immit experimentation traffic. From the view point of researchers, these OpenFlow-enabled testbeds only provide OpenFlow networking resource, and they have to resort to other experiment infrastructure to provide computing and storage resource. Due to the OpenFlow networking and other resource belongs to different infrastructure provider and is managed by their own control software, it is difficult to coordinate these partners to provide a full programmable experiment environment. Meanwhile, the control software of these testbeds are tight coupling with their substrate resources, which means that these substrate resources, together with virtualization technologies, are permanently dedicated to the control software and difficult to be used by other services. In this paper, a new future Internet testbed architecture based on the open Infrastructure-as-a-service cloud and software defined network (SDN) paradigm is proposed. It extends the current virtual network service by adding programmable virtual switch and controller resources that can be controlled by the researcher. Its loose coupling model allows the testbed operator decouple the experiment service from the infrastructure provider, which is a more flexible way to build the testbed. The initial prototype implementation in this paper shows that this new testbed architecture built on IaaS cloud and SDN is feasible and flexible to provide programmable virtual network service.

A possible approach to cope with the diversity of future networks is to set up multiple isolated virtual networks on top of a single shared physical substrate, and each virtual network is customized to some specific purposes. However, in the current realization of virtualized infrastructure, the OpenStack infrastructure as a service (IaaS) cloud, whose isolation and programmability are limited in terms of scalability and performance. To overcome these limitations, we propose a solution based on software defined networking (SDN) which is composed of a centralized server and distributed agents. The server has complete view of the whole network substrate, and is responsible for the installation and management of virtual network through the distributed agents. Each agent has the local view of the substrate node. They can manage the local resources, dispatch and filter the inner- programmable virtual network (PVN) traffic based on MAC isolation which is more scalable than virtual local area network (VLAN) and more efficient than GRE. Our prototype implementation shows that this architecture is feasible and provides a better compromise between flexibility and performance than the solo centralized and distributed solutions.

Computer game (CG) is one of the most challenging research directions in the fields of computer science and artificial intelligence (AI). Relational techniques of computer game are discussed in this article. The main work is listed below as three aspects: First of all, we analyzed the characteristics of Surakarta and modeled the game process of Surakarta. Next then, we discussed the techniques of search engine, which include game state evaluation and game tree search. Lastly, a series of experiments for the search engine were done. And then, combined with the experiments we get the empirical equation. These techniques made the evaluation of the game state more accurate, and the performance of the search engine was more effective and intelligent. The results and conclusions of these experiments have some reference values to other computer game procedures. And they have been proved by a series of experiments and competitions.

Along with the development of human-computer interaction technology and improvement of people's living standards, study of Internet of things (IoT) has become the focus for years. Meanwhile, smart home system has drawn more and more attention in IoT. In correlative research, artificial psychology theory and the harmony of human-computer interaction play an important role in smart home of IoT. In this study, software platform of the management system in smart home is designed, and users are Chinese. So the language in the system is Chinese. To analyze the basic interaction between users and computer, calendar, weather forecast, internet browsing, several electrical models are designed. To deal with the humanized interaction between human and computers, some features are implemented such as: analysis of emotional models, creation of the emotional models, text emotion recognition, and other basic functions in human-computer interaction.

This article proposes a novel dynamic spectrum sharing scheme in distributed multi-band cognitive radio networks. A non-cooperative game has been utilized to model the spectrum sharing among secondary base stations (SBSs). A distributed joint spectrum detection and power allocation algorithm is designed for maximizing the downlink throughput of secondary networks. Simulation results demonstrate that the proposed algorithm converges fast and achieves a better throughput performance than uniform threshold case. Meanwhile, the convergence of algorithm is proved by Nikaido-Isoda (N-I) function method.

Governments, companies and research institutions are pressuring research and development of the cyber-physical systems. However, the development of cyber-physical systems is constrained by security and privacy threats. This paper summarizes security threats to cyber-physical systems to provide a theoretical reference for study of cyber-physical systems as well as useful security measures. The architecture of cyber-physical systems is used to classify threats for the perception-execution layer, transport layer and application-control layer. The perception-execution layer threats include security threats for the nodes such as sensors and actuators. Transport layer threats include data leakage or damage and security issues during massive data integration. Application-control layer threats include the loss of user privacy, incorrect access control policies and inadequate security standards. Finally, this paper gives security measures and recommendations for all types of security threats.