Abstract:The chaotic categories of hidden big data features, combined with the ignorance of the public key and key encapsulation of big data ciphertext, result in low extraction accuracy and high redundancy of traditional hidden big data feature extraction methods.Here, a secure extraction approach of hidden features of big data is proposed based on hybrid cryptosystem.First, the big data ciphertext is generated through public key encapsulation and cryptographic key encapsulation mechanisms in hybrid cryptosystem.Second, the hidden big data characteristics are categorized based on symmetric encryption and asymmetric encryption designed according to the content of big data ciphertext, which are then used to construct the phase space of big data hidden features and calculate the correlation dimension between big data, thus realize the secure extraction of hidden big data features.The experimental results show that, compared with traditional methods, the proposed approach has low redundancy, high accuracy of classification rate for big data hidden features up to 95%, and low error of feature extraction, verifying the feasibility and application prospect of the proposed approach.

Abstract:The spaceborne synthetic aperture radar (SAR) plays an important role in ocean observation owing to its capability of working all-day and being insusceptible to sunlight,cloudiness or rainfall.It has unique advantages in retrieval of ocean surface dynamic parameters and study of multi-scale ocean dynamic processes with high spatial resolution,multi-polarization,and multi-imaging modes.Since the late 1970s,spaceborne SAR technology has developed rapidly.When combined with big data and machine learning techniques,spaceborne SAR exhibits more powerful vitality in ocean observation.In this paper,the 5‘V’ characteristics of spaceborne SAR big data are elaborated.Then two typical cases,i.e.retrieval of the sea surface wind speed,and scientific recognition of mesoscale dynamic processes of ocean internal waves,are presented to demonstrate the integration of spaceborne SAR,machine learning,and big data in assistance of high-resolution inversion of ocean environmental factors and deep understanding of marine dynamic processes.Finally,the prospective of spaceborne SAR big data for ocean remote sensing is given.

Abstract:With the rapid development of Internet of things and cloud computing,big data and its related science have become the focus of industry and academia.In this paper,we analyzes big data science from the perspective of paradigm theory and expounds the difference and connection between big data and traditional research.Three major challenges brought by big data are proposed in perspective of machine learning,with the corresponding scientific problems following.In addition,this paper introduces several insights of big data science from the perspective of the forth paradigm and its positive significance.In the end,we summarize and look forward to the challenges of big data science in the future.

Abstract:With the fast growing number of images,especially the user-generated ones,the semantic content of images become richer,and labels become more complex.Therefore,the study on image multi-label learning is one of the hot research areas in both academia and industry,and a large number of efficient methods have emerged in recent years.This paper surveys the existing work on image multi-label learning in recent years.Firstly,we briefly describe the concept of multi-label learning and introduce two types of methods,that is,single-instance multi-label learning and multi-instance multi-label learning.Then,we summarize three challenges on multi-label learning caused by the big data characteristics,and provide related work which can handle these challenges.Finally,we elaborate two applications on image recognition and automatic drive to show that multi-label learning techniques can be effective for many application scenarios.

Abstract:The continuous improvement of information technology will inevitably promote the arrival of the era of big data.Cloud computing provides a powerful data processing platform for big data.However,data security and privacy issues have aroused great concern.In this paper,we propose a new certificateless public key encryption scheme with multiple keywords search and free of secure channel for big data.We also prove that the proposed scheme can resist chosen keyword attack in random oracle model.The performance analysis shows that,the proposed scheme reduces the computation cost as well as the communication cost compared with the scheme proposed by Peng et al.in 2014.

Abstract:In era of big data,how to make full use of data analysis and data mining to effectively detect the spread of infectious diseases is of great significance for epidemic prevention & control as well as for individual security.Voluntary vaccination is an effective way to achieve broad immunity and safety protection for the whole population.Previous research results have showed that an individuals decision on voluntary vaccination is mainly based upon tradeoff between the infection risk and the protective profit,in which the decision of the individuals neighbors in last season is of impact,indicating the influence of strategy-updating for the collective security and protection.This paper studies into the effect of different strategy updates on the voluntary vaccination.The average proportion of vaccination,epidemic scale and total social cost are compared between different strategy updates.Thereafter,a reasonable strategy-updatingisdesigned to achieve relatively big vaccination coverage and small disease outbreak scale with relatively low social cost.

Abstract:Although the cloud computing has more and more extensiveapplications,it is hindered by problems such as non-support of high mobility or geographical position information,high latencyand so on.To this end,fog computing has emerged,where cloud computing is extended to the edge of the network to decrease the latency and network congestion.This paper first introduces the concept,characteristics,and a reference architecture for fog computing,then discusses the application scenarios and the issue of fog computing security.Similar paradigmsto fog computing like in-situ computing and edge computing are also delineated.Finally,the distinctions and relations between cloud computing and fog calculation are given,and the future development direction of the fog is analyzed.Fog brings computing from the core tothe edge of the network,which expands the network computing paradigm characterized by cloud computing,thus will be applied to more and more extensive serviceforms and types.

Abstract:In the big data background,not only the uncertainty of data is getting increasingly apparent,but also the incompatibility of data is becoming more and more prominent.The bipolarity as well as the fuzziness,is the instinct nature of everything.Although fuzzy set is the powerful tool to handle uncertain information,it has always neglected the incompatible bipolarity.Bipolar-valued fuzzy set introduced the incompatible bipolarity into fuzzy set theory,providing anew way to analyze and solve big data with incompatible nature,which has become a research hotspot.In this research summary,the category and characteristics of bipolarity are illustrated,then some concepts and theories are reviewed,especially the difference between bipolar-valued fuzzy sets and other corresponding fuzzy sets.Secondly,the research situations on bipolar-valued fuzzy setindomestic and world circles are discussed.Lastbut not least,the future development trend of bipolar-valued fuzzy set is analyzed.The summary provides an overall insight,as well asconstructs solid foundation for further studyinto bipolar-valued fuzzy set.

Abstract:With the rapid development of internet of things,cloud computing,and mobile internet,the rise of Big Data has attracted more and more concern,which brings not only great benefits but also crucial challenges on how to manage and utilize Big Data better.This paper describes the main aspects of Big Data including definition,data sources,key technologies,data processing tools and applications,discusses the relationship between Big Data and cloud computing,internet of things and mobile internet technology.Furthermore,the paper analyzes the core technologies of Big Data,Big Data solutions from industrial circles,and discusses the application of Big Data.Finally,the general development trend on Big Data is summarized.The review on Big Data is helpful to understand the current development status of Big Data,and provides references to scientifically utilize key technologies of Big Data.