Intellectualization has become a new trend for telecom industry, driven by intelligent technology including cloud computing, big data, and Internet of things. In order to satisfy the service demand of intelligent logi...Intellectualization has become a new trend for telecom industry, driven by intelligent technology including cloud computing, big data, and Internet of things. In order to satisfy the service demand of intelligent logistics, this paper designed an intelligent logistics platform containing the main applications such as e-commerce, self-service transceiver, big data analysis, path location and distribution optimization. The intelligent logistics service platform has been built based on cloud computing to collect, store and handling multi-source heterogeneous mass data from sensors, RFID electronic tag, vehicle terminals and APP, so that the open-access cloud services including distribution, positioning, navigation, scheduling and other data services can be provided for the logistics distribution applications. And then the architecture of intelligent logistics cloud platform containing software layer(SaaS), platform layer(PaaS) and infrastructure(IaaS) has been constructed accordance with the core technology relative high concurrent processing technique, heterogeneous terminal data access, encapsulation and data mining. Therefore, intelligent logistics cloud platform can be carried out by the service mode for implementation to accelerate the construction of the symbiotic win-winlogistics ecological system and the benign development of the ICT industry in the trend of intellectualization in China.展开更多
Cloud computing is a type of emerging computing technology that relies on shared computing resources rather than having local servers or personal devices to handle applications. It is an emerging technology that provi...Cloud computing is a type of emerging computing technology that relies on shared computing resources rather than having local servers or personal devices to handle applications. It is an emerging technology that provides services over the internet: Utilizing the online services of different software. Many works have been carried out and various security frameworks relating to the security issues of cloud computing have been proposed in numerous ways. But they do not propose a quantitative approach to analyze and evaluate privacy and security in cloud computing systems. In this research, we try to introduce top security concerns of cloud computing systems, analyze the threats and propose some countermeasures for them. We use a quantitative security risk assessment model to present a multilayer security framework for the solution of the security threats of cloud computing systems. For evaluating the performance of the proposed security framework we have utilized an Own-Cloud platform using a 64-bit quad-core processor based embedded system. Own-Cloud platform is quite literally as any analytics, machine learning algorithms or signal processing techniques can be implemented using the vast variety of Python libraries built for those purposes. In addition, we have proposed two algorithms, which have been deployed in the Own-Cloud for mitigating the attacks and threats to cloud-like reply attacks, DoS/DDoS, back door attacks, Zombie, etc. Moreover, unbalanced RSA based encryption is used to reduce the risk of authentication and authorization. This framework is able to mitigate the targeted attacks satisfactorily.展开更多
基金supported in part by National Key Research and Development Program under Grant No. 2016YFC0803206China Postdoctoral Science Foundation under Grant No.2016M600972
文摘Intellectualization has become a new trend for telecom industry, driven by intelligent technology including cloud computing, big data, and Internet of things. In order to satisfy the service demand of intelligent logistics, this paper designed an intelligent logistics platform containing the main applications such as e-commerce, self-service transceiver, big data analysis, path location and distribution optimization. The intelligent logistics service platform has been built based on cloud computing to collect, store and handling multi-source heterogeneous mass data from sensors, RFID electronic tag, vehicle terminals and APP, so that the open-access cloud services including distribution, positioning, navigation, scheduling and other data services can be provided for the logistics distribution applications. And then the architecture of intelligent logistics cloud platform containing software layer(SaaS), platform layer(PaaS) and infrastructure(IaaS) has been constructed accordance with the core technology relative high concurrent processing technique, heterogeneous terminal data access, encapsulation and data mining. Therefore, intelligent logistics cloud platform can be carried out by the service mode for implementation to accelerate the construction of the symbiotic win-winlogistics ecological system and the benign development of the ICT industry in the trend of intellectualization in China.
文摘Cloud computing is a type of emerging computing technology that relies on shared computing resources rather than having local servers or personal devices to handle applications. It is an emerging technology that provides services over the internet: Utilizing the online services of different software. Many works have been carried out and various security frameworks relating to the security issues of cloud computing have been proposed in numerous ways. But they do not propose a quantitative approach to analyze and evaluate privacy and security in cloud computing systems. In this research, we try to introduce top security concerns of cloud computing systems, analyze the threats and propose some countermeasures for them. We use a quantitative security risk assessment model to present a multilayer security framework for the solution of the security threats of cloud computing systems. For evaluating the performance of the proposed security framework we have utilized an Own-Cloud platform using a 64-bit quad-core processor based embedded system. Own-Cloud platform is quite literally as any analytics, machine learning algorithms or signal processing techniques can be implemented using the vast variety of Python libraries built for those purposes. In addition, we have proposed two algorithms, which have been deployed in the Own-Cloud for mitigating the attacks and threats to cloud-like reply attacks, DoS/DDoS, back door attacks, Zombie, etc. Moreover, unbalanced RSA based encryption is used to reduce the risk of authentication and authorization. This framework is able to mitigate the targeted attacks satisfactorily.
