Big Data possesses profound information of our society, and therefore, it impacts numerous aspects of human society, with a large amount of data from large-scale heterogeneous network environments, we should analyze some special issues of network security monitoring on Big Data environments. This paper propose data cleaning for various types of data sources and analysis Big Data on network security through security event on multiple associations rules. This study provides some ideas for network security monitoring on Big Data environments.
The amount of data in our world has been exploding, and analyzing large data sets—so-called big data— will become a key basis of competition, underpinning new waves of productivity growth, innovation, and consumer surplus, according to research by MGI and McKinsey's Business Technology Office. Leaders in every sector will have to grapple with the implications of big data, not just a few data-oriented managers. The increasing volume and detail of information captured by enterprises, the rise of multimedia, social media, and the Internet of Things will fuel exponential growth in data for the foreseeable future.
Context ::: Biodiversity monitoring programs require fast, reliable and cost-effective methods for biodiversity assessment in landscapes. Sampling pollinators across entire landscapes is challenging, as trapping needs to cover many habitat types.